Understanding protein structure and dynamics is crucial for investigating numerous biological processes. This however requires proper description of molecular interactions, most notably hydrogen bonds, which are the driving force behind the folding of protein sequences into working molecules. Due to the multi-body character of this interaction, proper mathematical formulation has been a matter of long debate in the literature. This description becomes even more complex in reduced protein models. In this contribution, we propose a novel hydrogen bond energy function definition that is based only on Cα positions and used for coarse-grained simulations. We show that this new method has the capability to recognize hydrogen bonds with over 80% accuracy and can successfully identify β-sheet in β-amyloid peptide simulations.

To meet the needs of dehydrated skin, molecules with a high hygroscopic potential are necessary to hydrate it effectively and durably. In this context, we were interested in pectins, and more precisely in apiogalacturonans (AGA), a singular one that is currently only found in a few species of aquatic plants. As key structures in water regulation of these aquatic plants and thanks to their molecular composition and conformations, we hypothesized that they could have beneficial role for skin hydration. Spirodela polyrhiza is a duckweed known to be naturally rich in AGA. The aim of this study was to investigate the hygroscopic potential of AGA. Firstly, AGA models were built based on structural information obtained from previous experimental studies. Molecular dynamics (MD) simulations were performed, and the hygroscopic potential was predicted in silico by analyzing the frequency of interaction of water molecules with each AGA residue. Quantification of interactions identified the presence of 23 water molecules on average in contact with each residue of AGA. Secondly, the hygroscopic properties were investigated directly in vivo. Indeed, the water capture in the skin was measured in vivo by Raman microspectroscopy thanks to the deuterated water (D20) tracking. Investigations revealed that AGA significantly capture and retain more water in the epidermis and deeper than a placebo control. Not only do these original natural molecules interact with water molecules, but they capture and retain them efficiently in the skin.

The recent advancement in group VA monolayer and few-layer materials leads to fascinating applications. In this mini-review, we present the state-of-the-art in the synthesis of antimonene, its properties and various applications. Besides, the electronic properties of antimonene depend on its allotropes. Furthermore, we studied the electronic properties of δ, ε, and twisted-θ antimonene nanosheets, nanoribbons, and nanoring, and the results are reported. Moreover, the structural stability and electronic properties of antimonene is influenced by its allotrope and nanostructure. The report will give insights into the synthesis, properties, applications, and future outlook of antimonene.

Results of the recent Critical Assessment of Protein Structure (CASP) competitions demonstrate that protein backbones can be predicted with very high accuracy. In particular, the artificial intelligence methods of AlphaFold 2 from DeepMind were able to produce structures that were similar enough to experimental structures that many described the problem of protein prediction solved. However, for such structures to be used for drug docking studies requires precision in the placement of side chain atoms as well. Here we built a library of 1334 small molecules and examined how reproducibly they bound to the same site on a protein using QuickVina-W, a branch of the program Autodock that is optimized for blind searches. We discovered that the higher the backbone quality of the homology model the greater the similarity between the small molecule docking to the experimental and modeled structures. Furthermore, we found that specific subsets of this library were particularly useful for identifying small differences between the best of the best modeled structures. Specifically, when the number of rotatable bonds in the small molecule increased, differences in binding sites became more apparent.

G protein-coupled receptors (GPCR) are integral membrane proteins of considerable interest as targets for drug development due to their role in transmitting cellular signals in a multitude of biological processes. Of the six classes categorizing GPCR (A, B, C, D, E, and F), class A contains the largest number of therapeutically relevant GPCR. Despite their importance as drug targets, many challenges exist for the discovery of novel class A GPCR ligands serving as drug precursors. Though knowledge of the structural and functional characteristics of GPCR has grown significantly over the past 20 years, a large portion of GPCR lack reported, experimentally determined structures. Furthermore, many GPCR have no known endogenous and/or synthetic ligands, limiting further exploration of their biochemical, cellular, and physiological roles. While many successes in GPCR ligand discovery have resulted from experimental high-throughput screening, computational methods have played an increasingly important role in GPCR ligand identification in the past decade. Here we discuss computational techniques applied to GPCR ligand discovery. This review summarizes class A GPCR structure/function and provides an overview of many obstacles currently faced in GPCR ligand discovery. Furthermore, we discuss applications and recent successes of computational techniques used to predict GPCR structure as well as present a summary of ligand- and structure-based methods used to identify potential GPCR ligands. Finally, we discuss computational hit list generation and refinement and provide comprehensive workflows for GPCR ligand identification.

Malaria is a life-threatening parasitic disease that affects millions of people worldwide, especially in developing countries. Despite advances in conventional therapies, drug resistance in malaria parasites has become a significant concern. Hence, there is a need for a new therapeutic approach. To combat the disease effectively means eliminating vectors and discovering potent treatments. The nanotechnology research efforts in nanomedicine show promise by exploring the potential use of nanomaterials that can surmount these limitations occurring with antimalarial drugs, which include multidrug resistance or lack of specificity when targeting parasites directly. Utilizing nanomaterials would possess unique advantages over conventional chemotherapy systems by increasing the efficacy levels while reducing side effects significantly by delivering medications precisely within the diseased area. It also provides cheap yet safe measures against Malaria infections worldwide-ultimately improving treatment efficiency holistically without reinventing new methods therapeutically. This review is an effort to provide an overview of the various stages of malaria parasites, pathogenesis, and conventional therapies, as well as the treatment gap existing with available formulations. It explores different types of nanocarriers, such as liposomes, ethosomal cataplasm, solid lipid nanoparticles, nanostructured lipid carriers, polymeric nanocarriers, and metallic nanoparticles, which are frequently employed to boost the efficiency of antimalarial drugs to overcome the challenges and develop effective and safe therapies. The study also highlights the improved pharmacokinetics, enhanced drug bioavailability, and reduced toxicity associated with nanocarriers, making them a promising therapeutic approach for treating malaria.

In this work, molecular dynamics simulations of complexes composed of single strand DNA (ssDNA) sequences and cationic oligothiophenes are performed to understand experimental findings and the sensing ability of polythiophene electrolytes toward ssDNA. The simulation results exhibit no significant structural effect for replacing the cationic amine moiety with imidazole derivative on the side group of the oligomer. Adding a homopurine strand elongates the oligomer backbone; on the contrary, mixing up the homopyrimidine strand causes compression. On the other hand, these ssDNAs do not notably affect the compactness of the oligomer backbones. The anion-cation interactions play an essential role in the structural and spectroscopic change of cationic polythiophenes (CPTs) upon complexation with ssDNAs. The red shift of CPTs in the UV-VIS spectra with the addition of homopurine strands might be explained by the strong anion-cation, weak π -cation interactions, and high binding affinities. Nonpolar interactions (vdW and SA) and complex solvation energies dominate binding free energies. Hydrogen interaction analyses show that oligomers most likely approach the ssDNAs from their backbone upon complexation except for the duplex containing homopyrimidine strand and oligothiophene possessing imidazole derivative side chain.

Molecular properties prediction and new material discovery are significant for the pharmaceutical industry, food, chemistry, and other fields. The popular methods are theoretical mechanism calculation and machine learning. There is a deviation between the theoretical mechanism calculation results and the experimental data. Machine learning method provides a promising solution. However, the process is lack of interpretability, and the reliability and the generalization depend on the training data. In this paper, a mechanism correction model combined with graph neural network (GNN) model which is based on the fusion of graph embedding and descriptors vector is proposed as backbone network to proceed molecule properties prediction and new material discovery. The molecular structure is input to graph neural network and the abstracted features are fused with numerical features together for training. The experiment data and computing data are designed as label constructor, and then the theoretical computation (mechanism driven model) is fused with the output of GNN (data-driven model) to form a fused model to modulate the output for the molecular property prediction. Experiments for public data set are executed and the results show that Mechanism-Data-Driven Graph Neural Network (MD-GNN) can effectively make the predicted results more accurate. Nineteen molecules by different construction are designed for potential drug discovery, the prediction from the proposed MD-GNN model shows that there are 9 candidates are discovered.

Several properties of silymarin (SM) extract have been attributed to their three major flavonolignans (silybin, silychristin, and silydianin) and their 2,3-dehydro derivatives (2,3-dehydrosilybin, 2,3-dehydrosilychristin, and 2,3-dehydrosilydianin). Experimental findings have suggested that the antioxidative and protective activities of these compounds could be due to their ability to activate nuclear factor erythroid 2-related factor 2 (Nrf2). The mechanism by which SM compounds exert their effect has been suggested to be by disrupting the complex between Nrf2 and Kelch-like ECH-associated protein 1 (Keap1). However, information about the structural and energetic basis of the inhibitory mechanism of SM compounds on the Nrf2-Keap1 pathway is lacking. We evaluated the binding properties of SM compounds because experimental findings have pointed to them as potential activators of Nrf2. Our study combined docking and molecular dynamics (MD) simulations with the Poisson-Boltzmann and generalized Born and surface area (MMPBSA and MMGBSA) methods and quantum mechanics-molecular mechanics (QMMM) calculations to investigate Keap1-ligand interactions. Our results predicted that silybinA and 2,3-dehydrosilybin bind to Keap1, forming interactions with the same pockets as those observed for the cocrystallized Keap1-Cpd16 complex but with more favorable binding free energies. These findings indicate that both natural compounds are potential activators of Nrf2.

An intense absorption, phosphorescence, a long triplet excited state lifetime and singlet oxygen generation capabilities are characteristics of pyranoflavylium cations, analogues to pyranoanthocyanidins originated in the maturation process of red wine. Such properties make these compounds potential photosensitizers to be applied in photodynamic therapy. In this context, the photophysical processes underlying that treatment critically depend on the electronic structure of the pyranoflavylium molecules. When employing density functional theory to describe the electronic structure of molecules, the choice of the most suitable functional is not trivial, and benchmark studies are needed to orient practitioners in the field. In this work, a benchmark of seven of the most commonly used density functionals in addressing the photophysical properties of a set of eight pyranoflavylium cations is reported. Ground and excited state geometries, molecular orbitals, and absorption, fluorescence and phosphorescence transition energies were calculated using density functional theory approaches, and evaluated and compared to experimental data and monoreferential wave function-based methodologies. Statistical analysis of the results indicates that global-hybrid functionals allow an excellent description of absorption and emission energies, with errors around 0.05 eV, while range-separated variants led to somewhat larger errors in the range 0.1-0.2 eV. In contrast, range-separated functionals display excellent phosphorescence energies with errors close to 0.05 eV, in this case global-hybrids showing increased discrepancies around 0.5-0.1 eV.

The binding affinity of the SARS-CoV-2 spike (S)-protein to the human membrane protein ACE2 is critical for virus function. Computational structure-based screening of new S-protein mutations for ACE2 binding lends promise to rationalize virus function directly from protein structure and ideally aid early detection of potentially concerning variants. We used a computational protocol based on cryo-electron microscopy structures of the S-protein to estimate the change in ACE2-affinity due to S-protein mutation (ΔΔGbind) in good trend agreement with experimental ACE2 affinities. We then expanded predictions to all possible S-protein mutations in 21 different S-protein-ACE2 complexes (400,000 ΔΔGbind data points in total), using mutation group comparisons to reduce systematic errors. The results suggest that mutations that have arisen in major variants as a group maintain ACE2 affinity significantly more than random mutations in the total protein, at the interface, and at evolvable sites. Omicron mutations as a group had a modest change in binding affinity compared to mutations in other major variants. The single-mutation effects seem consistent with ACE2 binding being optimized and maintained in omicron, despite increased importance of other selection pressures (antigenic drift), however, epistasis, glycosylation and in vivo conditions will modulate these effects. Computational prediction of SARS-CoV-2 evolution remains far from achieved, but the feasibility of large-scale computation is substantially aided by using many structures and mutation groups rather than single mutation effects, which are very uncertain. Our results demonstrate substantial challenges but indicate ways forward to improve the quality of computer models for assessing SARS-CoV-2 mutation effects.

Ongoing global pandemic caused by coronavirus (COVID-19) requires urgent development of vaccines, treatments, and diagnostic tools. Open reading frame 3a (ORF3a) from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is considered to be a potential drug target for COVID-19 treatment. ORF3a is an accessory protein that plays a significant role in virus-host interactions and in facilitating host immune responses. Using putrescine, spermidine and spermine, an aliphatic polyamine for the activity suppression of ORF3a appears to be a promising approach in finding new targets for drug design. In this study, we explored the possible binding poses of polyamines to the ORF3a protein using a combination of various computational approaches i.e. pocket prediction, blind and site-specific molecular docking, molecular dynamics and ligand flooding simulations. The results showed that the tip of cytoplasmic domain and the upper tunnel of transmembrane domain of ORF3a provide a suitable binding site specific for the polyamines. MD simulations revealed the stability of spermidine binding in the upper tunnel pocket of ORF3a through salt bridge and hydrogen bond interactions between the amine groups of the ligand and negatively charged residues of ORF3a. These findings can be helpful in designing new therapeutic drugs.

Overexpression of the Phosphatidylinositol 3-kinase (PI3K) proteins have been observed in cancer cells. Targeting the phosphatidylinositol 3-kinase (PI3K) signaling transduction pathway by inhibition of the PI3K substrate recognition sites has been proved to be an effective approach to block cancer progression. Many PI3K inhibitors have been developed. Seven drugs have been approved by the US FDA with a mechanism of targeting the phosphatidylinositol 3-kinase/protein kinase-B/mammalian target of rapamycin (PI3K/AKT/mTOR) signaling pathway. In this study, we used docking tools to investigate selective binding of ligands toward four different subtypes of PI3Ks (PI3Kα, PI3Kβ, PI3Kγ and PI3Kδ). The affinity predicted from both the Glide dock and the Movable-Type (MT)-based free energy calculations agreed well with the experimental data. The validation of our predicted methods with a large dataset of 147 ligands showed very small mean errors. We identified residues that may dictate the subtype-specific binding. Particularly, residues Asp964, Ser806, Lys890 and Thr886 of PI3Kγ might be utilized for PI3Kγ-selective inhibitor design. Residues Val828, Trp760, Glu826 and Tyr813 may be important for PI3Kδ-selective inhibitor binding.

An in silico consensus molecular docking approach and in vitro evaluations were adopted in the present study to explore a dataset of FDA-approved drugs as novel multitarget MAO-B/AChE agents in the treatment of Alzheimer's disease (AD). GOLD 5.3 and Glide were employed in the virtual assessments and consensus superimpositions of the obtained poses were applied to increase the reliability of the docking protocols. Furthermore, the top ranked molecules were subjected to binding free energy calculations using MM/GBSA, Induced fit docking (IFD) simulations, and a literature review. Consequently, the top four multitarget drugs were examined for their in vitro MAO-B and AChE inhibition effects. The consensus molecular docking identified Dolutegravir, Rebamipide, Loracarbef and Diflunisal as potential multitarget drugs. The biological data demonstrated that most of the docking scores were in good correlation with the in vitro experiments, however the theoretical simulations in the active site of MAO-B identified two false-positives - Rebamipide and Diflunisal. Dolutegravir and Loracarbef were accessed as active MAO-B inhibitors, while Dolutegravir, Rebamapide and Diflunisal as potential AChE inhibitors. The antiretroviral agent Dolutegravir exhibited the most potent multitarget activity - 41% inhibition of MAO-B (1 μM) and 68% inhibition of AChE (10 μM). Visualizations of the intermolecular interactions of Dolutegravir in the active sites of MAO-B and AChE revealed the formation of several stable hydrogen bonds. Overall, Dolutegravir was identified as a potential anti-AD drug, however further in vivo evaluations should be considered.

The search of new materials having suitable characteristics to trap hydrogen for fuel applications is greatly challenging due to the stringent requirements that such materials must meet. In this sense, with the aid of computational chemistry, significant advances can be achieved. The present work explores the adsorption of hydrogen molecules by lithium clusters (Lin, where n = 1-6) coordinated to a graphitic carbon nitride (heptazine, gC3N4) cavity. The study was conducted using the density functional theory (M06-2X-D3) in combination with the def2-TZVP basis set. Our results suggest that lithium atoms in the gC3N4-cavity can coordinate up to 10 hydrogen molecules with bond energies in the range -0.10 to -0.19 eV. The [gC3N4Li5]+ and [gC3N4Li6] systems resulted to be the most promising in terms of lithium coordination. They feature the highest stabilization energies for hydrogen adsorption. According to the calculated Gibbs free energies for these systems, H2 adsorption remains a spontaneous process even at 400 K.

Type IV (T4) pilus is among the virulence factors with a key role in serious bacterial diseases. Specifically, in Neisseria meningitidis and Pseudomonas aeruginosa, it determines pathogenicity and causes infection. Here, a computational approach has been pursued to find piperidine-based inhibitor molecules against the elongation ATPase of T4 pili in these two selected pathogens. Using the modeled structures of the PilF and PilB ATPases of N. meningitidis and P. aeruginosa, virtual library screening via molecular docking has returned inhibitor molecule candidates. The dynamics of the best three binders have further been investigated in detail via molecular dynamic simulations. Among these, ligands with COCONUT IDs CNP0030078 and CNP0051517 were found to have higher potential in the inhibition of ATPases based on molecular dynamic simulation analysis and biological activity information. The obtained results will guide future efforts in antivirulence drug development against T4 pili of N. meningitidis and P. aeruginosa.

Via molecular dynamics (MD) simulations we find the existence of the new allotrope of two-dimensional (2D) germanene, i.e. 2D tetra-germanene (tetra-Ge) which contains entirely tetragons. We compress 2D hexa-germanene (hexa-Ge) step by step over a broad density range at constant temperature and hexa-tetra Ge phase transition occurs. We find that the compression of hexa-Ge at 2000 K (not far above the melting point of hexa-Ge) leads to the formation of tetra-Ge with the highest quality. Atomic structure of the obtained tetra-Ge at 300 K is analyzed in details. Although fraction of tetragons in the tetra-Ge is very high (larger than 0.99), some defects are found in addition to the skew tetragons. Due to containing almost entirely tetragons, tetra-Ge may exhibit new behaviors unlike those of the hexa-Ge. Subsequent studies in this direction for 2D tetra-Ge. In addition, first-principles calculations under density functional theory confirm the existence of stable tetra-Ge.

Toxicity has been a significant concern for many materials used in the production of solar cells and generally conflicts with its efficacy. Therefore, it is crucial to develop alternative, non-toxic materials to improve the sustainability and safety of solar cell technology. In recent years, computational methods such as Conceptual density functional theory (CDFT) have been increasingly used to study the electronic structure and optical properties of toxic molecules such as dyes, with the goal of designing and modifying these molecules to enhance solar cell efficiency and reduce toxicity. By applying CDFT-based chemical reactivity parameters and electronic structure rules, researchers can gain valuable insights into the performance of solar cells and optimize their design accordingly. In silico studies have been used to screen and design non-toxic dye molecules, which can improve the sustainability and safety of solar cell technology. This review article discusses the applications of CDFT in the analysis of toxic dye molecules for use in solar cells. This review also highlights the importance of using alternative, non-toxic materials in the production of solar cells. The review also discusses the limitations of CDFT and in silico studies and their potential for future research. Finally, the article concludes by emphasizing the potential of in silico/DFT investigations for accelerating the discovery of new and efficient dye molecules for enhancing solar cells' efficiency.

Modelling metalloproteins using the classical force fields is challenging. Several methods have been devised to model metalloproteins in force fields. Of these methods, the bonded model, combined with Restrained Electrostatic Potential (RESP) charge fitting, proved its superiority. The latter method was facilitated by the development of the python-based Metal Centre Parameter Builder (MCPB.py) AmberTool. However, the standard bonded model method offered by the MCPB.py tool may not be appropriate for validating and refining the binding modes predicted by docking when crystal structures are lacking. That is because the representation of coordination interactions between any bound ligand and metal ions by covalent bonds can hinder the flexibility of the ligand. Therefore, a new modification to the standard bonded model approach is proposed here. Molecular dynamics (MD) simulations based on the new modified bonded model (MBM) approach avoid the bias caused by coordination bonds and, unlike hybrid QM/MM MD, allow for sufficient sampling of the binding mode given the currently available computational power. The MBM MD approach reproduced the studied crystal structure conformations of New Delhi Metallo-β-lactamase 1 (NDM-1). Furthermore, the MBM approach described the binding interactions of intact β-lactams with NDM-1 reasonably, and predicted a non-productive binding mode for the poor NDM-1 substrate aztreonam whilst predicting productive binding modes for known good substrates. This study presents a useful MD method for metallo-β-lactamases and provides better understanding of β-lactam substrates recognition by NDM-1. The proposed MBM approach might also be useful in the investigation of other metal-containing protein targets.

This study focuses on the creation of 5 small donor molecules (A102W1-A102W5) by substituting the one-sided methoxy group of model (A102R) with different thiophene bridged acceptor moieties. B3LYP/6-31**G (d,p) model has been employed for computational analysis. The best miscibility was found for A102W3 in dichloromethane (DCM) solvent, where its λmax was also found to be at 753 nm, its Eg was found to be 1.55 eV as well as dipole moment in DCM was 21.47 D. The percentage of PCE among all the variants was greatest for A102W2 (25.31%). The electron reorganization energy shown by A102W4 was 0.00470 eV, whereas the hole reorganization energy investigated in A102W2 was 0.00586 eV representing their maximum electron and hole mobility respectively amongst all. Results validate the value of specified techniques, opening a new door to create efficient small donors for OSCs and HTMs for PSCs.

Through this research, functionalized graphene nanopores are used to verify how effective such an apparatus for DNA sequencing is. The circular symmetric pores are functionalized with hydrogen and a hydroxyl group bonded with carbon atoms of the pore rim. Plus, two adenine bases are also put at the rim perimeter to verify whether such a combination would lead to base detection. A homopolymer of single-stranded DNA (ssDNA) is pulled through a nanopore using steered molecular dynamics (SMD) simulation. Pulling force profile, moving fashion of ssDNA in irreversible DNA pulling as well as the base orientation during translocation relative to the graphene plane, called beta angle, are assessed. Based on the studied parameters, SMD force, and base orientation, the hydrogenated and hydroxylated pores do not show a clear distinction between bases, while the adenine-functionalized pore can distinguish between adenine and cytosine. Therefore, there may be some hope for achieving single-base sequencing, while further research is needed.

The first oral drug for the treatment of COVID-19, Paxlovid, has been authorized; however, nirmatrelvir, a major component of the drug, is reported to be associated with some side effects. Moreover, the appearance of many novel variants raises concerns about drug resistance, and designing new potent inhibitors to prevent viral replication is thus urgent. In this context, using a hybrid approach combining machine learning (ML) and free energy simulations, 6 compounds obtained by modifying nirmatrelvir were proposed to bind strongly to SARS-CoV-2 Mpro. The structural modification of nirmatrelvir significantly enhances the electrostatic interaction free energy between the protein and ligand and slightly decreases the vdW term. However, the vdW term is the most important factor in controlling the ligand-binding affinity. In addition, the modified nirmatrelvir might be less toxic to the human body than the original inhibitor.

Filarial infections are among the world's most disturbing diseases caused by 3 major parasitic worms; Onchocerca volvulus, Wuchereria bancrofti, and Brugia malayi, affecting more than 500 million people worldwide. Currently used drugs for mass drug administration (MDA) have been met with several challenges including the development of complications in individuals with filaria co-infections and parasitic drug resistance. The filarial endosymbiont, Wolbachia, has emerged as an attractive therapeutic target for filariasis elimination, due to the dependence of the filaria on this endosymbiont for survival. Here, we target an important enzyme in the Wolbachia heme biosynthetic pathway (ferrochelatase), using high-throughput virtual screening and molecular dynamics with MM-PBSA calculations. We identified four drug candidates; Nilotinib, Ledipasvir, 3-benzhydryloxy-8-methyl-8-azabicyclo[3.2.1]octane, and 2-(4-Amino-piperidin-1-yl)-ethanol as potential small molecules inhibitors as they could compete with the enzyme's natural substrate (Protoporphyrin IX) for active pocket binding. This prevents the worm from receiving the heme molecule from Wolbachia for their growth and survival, resulting in their death. This study which involved targeting enzymes in biosynthetic pathways of the parasitic worms' endosymbiont (Wolbachia), has proven to be an alternative therapeutic option leading to the discovery of new drugs, which will help facilitate the elimination of parasitic infections.

The dosing and efficacy of chemotherapeutic drugs can be limited by toxicity caused by off-pathway reactions. One hypothesis for how such toxicity arises is via metal-catalyzed oxidative damage of cardiac myosin binding protein C (cMyBP-C) found in cardiac tissue. Previous research indicates that metal ion mediated reactive oxygen species induce high levels of protein carbonylation, changing the structure and function of this protein. In this work, we use long timescale all-atom molecular dynamics simulations to investigate the ion environment surrounding the C0 and C1 subunits of cMyBP-C responsible for actin binding. We show that divalent cations are co-localized with protein carbonylation-prone amino acid residues and that carbonylation of these residues can lead to site-specific interruption to the actin-cMyBP-C binding.

Experimental and theoretically calculated UV-vis properties of three Cu(β-diketonato)2 complexes are presented. The Cu(β-diketonato)2 contains β-diketones without (β-diketone = acetylacetone, (CH3)COCH2CO(CH3), complex (1)), with one (β-diketone = thenoyltrifluoroacetone, (CF3)COCH2CO(C4H3S), complex (2)) and with two thiophene (β-diketone = (CF3)COCH2CO(C4H2S) (C4H3S), complex (3)) groups. More thiophenes on the β-diketonato ligand of Cu(β-diketonato)2, lead to a red shift of the experimental absorbance maxima of the UV-vis of the complex, from 295 nm for complex (1), to 340 nm for complex (2) to 390 nm for complex (3). Theoretical time dependant density functional theory calculations indicate that both the two strongest absorbance peaks of the ultraviolet-visible spectrum of Cu(acetylacetonato)2 are mainly ligand-to-metal charge-transfer excitations. However, the absorbance maxima of the UV-vis of thiophene-containing Cu(β-diketonato)2 are mainly ligand-to-ligand charge-transfer excitations. Calculated properties such as light harvesting energy (LHE = 0.47, 0.94 and 0.99 for (1)-(3) respectively), driving force for electron injection (ΔGinject = 1.43, 0.76 and 0.63 for (1)-(3) respectively), and driving force of dye regeneration (ΔGregenerate = 1.85, 2.16 and 1.49 for (1)-(3) respectively), are favourable for (1)-(3) to be considered as dyes in DSSCs. However, some structural modifications are needed to prevent intramolecular charge recombination after excitation.

Histone deacetylase (HDAC) inhibitors are in the limelight of anticancer drug development and research. HDAC10 is one of the class-IIb HDACs, responsible for cancer progression. The search for potent and effective HDAC10 selective inhibitors is going on. However, the absence of human HDAC10 crystal/NMR structure hampers the structure-based drug design of HDAC10 inhibitors. Different ligand-based modeling techniques are the only hope to speed up the inhibitor design. In this study, we applied different ligand-based modeling techniques on a diverse set of HDAC10 inhibitors (n = 484). Machine learning (ML) models were developed that could be used to screen unknown compounds as HDAC10 inhibitors from a large chemical database. Moreover, Bayesian classification and Recursive partitioning models were used to identify the structural fingerprints regulating the HDAC10 inhibitory activity. Additionally, a molecular docking study was performed to understand the binding pattern of the identified structural fingerprints towards the active site of HDAC10. Overall, the modeling insight might offer helpful information for medicinal chemists to design and develop efficient HDAC10 inhibitors.

Exo-inulinases are applied in inulin hydrolysis and production of feed additives and need to be stable at temperatures of 60-95 °C. Aspergillus awamori exo-inulinase Inu1 is considerably thermostable, with a Tm of 73.2 °C. However, the thermostability of the enzyme should be improved. A single substitution G338A in α-helix in the active center of the enzyme provided a 3.5 °C improvement in Tm. The time of half-life at 70 °C and 80 °C was increased in 5.7- and 2.7-times, respectively, compared to wild-type. Molecular dynamics simulations demonstrated that the substitution G338A caused a decrease in RMSF not only for the α-helix 337-YAANI-341, but also for the catalytically active residues D41 and E241 and the amino acid residues forming the cleft of the active center. Calculations with Constraint Network Analysis for the variant G338A showed the increase in the stability of intramolecular clusters.

Thermophilic enzymes are highly desired in industrial applications due to their efficient catalytic activity at high temperature. However, most enzymes exhibit inferior thermostability and it remains challenging to identify the optimal sites for designing mutations to improve protein stability. To tackle this issue, we integrated topological analysis and all-atom molecular dynamics simulations to efficiently pinpoint the thermally-unstable regions in protein structures. Using a protease CN2S8A as the model, we analyzed the intramolecular hydrogen bonding interactions between adjacent secondary structure elements, and then identified the topological weak spots of CN2S8A where weak hydrogen bonding interactions were formed. To examine the role of these sites in protein structural stability, we designed three virtual mutations at different weak spots and characterized the effects of these mutations on the structural properties of CN2S8A. The results showed that all three mutations increased the protein structural stability. In conclusion, these findings provide a novel method to identify the topological weak spots of proteins, with implications in the rational design of biocatalysts with superior thermostability.

Density functional theory (DFT) calculations at the M06-2X/def2-TZVP level have been employed to investigate the atmospheric oxidation mechanism of anthracene (ANT) initiated by HO•. Direct hydrogen atom abstraction from the ANT using HO• takes place hardly at ambient conditions while addition of HO• to the C1, C2, and C4 sites are thermodynamically and kinetically more advantageous. The addition reactions are controlled by the aromaticity and the kinetic trends were justified by resonance stabilization energies. The rate constants were calculated by using the Rice-Ramsperger-Kassel-Marcus (RRKM) and canonical transition state theory (CTST) methods in conjugation with zero curvature tunneling (ZCT). The overall RRKM-bimolecular rate constant at ambient conditions is 6.72 × 10-12 cm3 molecule-1 s-1, is negatively dependent on the temperature and can be expressed as k250-3501bar=3.92×10-14exp(1534.9T). Contribution of the AD-C4 path in the overall reaction is about 70-80%, implying that the dependence of overall rate constant on pressure can be ignored. The kinetic data exhibit that the ANT is degraded during its long-range transport in the atmosphere and cannot be classified as persistent organic pollutants.

Recently, molecular representation and property exploration, with the combination of neural network, play a critical role in the field of drug design and discovery for assisting in drug related research. However, previous research in molecular representation relies heavily on artificial extraction of features based on biological experiments which may result in a manually introduced noise of molecular information with high cost in time and money. In this paper, a novel method named Substructural Hierarchical Attention Network (SuHAN) is proposed to discover inherent characteristics of molecules for representation learning. Specifically, SuHAN is composed of the cascaded layer: atom-level layer and substructure-level layer. Molecule in the SMILES format is divided into several substructural fragments by predefined partition rules, and then they are fed into atom-level layer and substructure-level layer successively to obtain feature representation from different perspective: atomic view and substructural view. In this way, the prominent structural features that may be omitted in global extraction are excavated from a fine-grained viewpoint and fused to reconstruct representative pattern in an overall view. Experiments on biophysics and physiology datasets demonstrate that our model is competitive with a significant improvement of both accuracy and stability in performance. We confirmed that the substructural segments and progressive hierarchical networks lead to an effective molecular representation for downstream tasks. These results provide a novel perspective about reconstructing overall pattern through local prominent structure.

The thermodynamic and biophysical implications of the introduction of a co-solvent during protein-ligand binding remain elusive. Using ternary complexes of 12-kDa FK506 binding protein (FKBP12), FKBP-rapamycin binding (FRB) domain of the mammalian/mechanistic target of rapamycin (mTOR) kinase, and rapamycin analogs (rapalogs) in glycerol-water mixtures, the influence of solvent composition on ligand binding dynamics was explored. The pharmaceutical potential of rapalogs and the utility of glycerol as a co-solvent in drug delivery applications were critical in deciding the system to be studied. Consolidation of existing studies on rapamycin modification was first performed to strategically design a new rapalog called T1. The results from 100-ns dual-boost Gaussian accelerated molecular dynamics simulations showed that protein stability was induced in the presence of glycerol. Reweighting of the trajectories revealed that the glycerol-rich solvent system lowers the energy barrier in the conformational space of the protein while also preserving native contacts between the ligand and the residues in the binding site. Calculated binding free energies using MM/GBSA also showed that electrostatic energy and polar contribution of solvation energy are heavily influenced by the changes in solvation. Glycerol molecules are preferentially excluded through electrostatic interactions from the solvation shell which induce complex stability as seen in existing experiments. Hence, using glycerol as a co-solvent in rapamycin delivery has a significant role in maintaining stability. In addition, compound T1 is a potential mTORC1-selective inhibitor with strong affinity for the FKBP12-FRB complex. This study aims to provide insights on the design of new rapalogs, and the applicability of glycerol as co-solvent for FKBP12-rapalog-FRB complexes.

PURPOSE OR OBJECTIVE: Melanoma is one of the most dangerous forms of skin cancer and the discovery of novel drugs is an ongoing effort. Quantitative Structure Activity Relationship (QSAR) is a computational method that allows the estimation of the properties of a molecule, including its biological activity. QSAR models have been widely employed in the search for potential drug candidates, but also for agrochemicals and other molecules with applications in different branches of the industry. Here we present Bambu, a simple command line tool to generate QSAR models from high-throughput screening bioassays datasets. METHODS: The tool was developed using the Python programming language and relies mainly on RDKit for molecule data manipulation, FLAML for automated machine learning and the PubChem REST API for data retrieval. As a proof-of-concept we have employed the tool to generate QSAR models for melanoma cell growth inhibition based on HTS data and used them to screen libraries of FDA-approved drugs and natural compounds. Additionally, Bambu was compared to QSAR-Co, another automated tool for QSAR model generation. RESULTS: based on the developed tool we were able to produce QSAR models and identify a wide variety of molecules with potential melanoma cell growth inhibitors, many of which with anti-tumoral activity already described. The QSAR models are available through the URL http://caramel.ufpel.edu.br, and all data and code used to generate its models are available at Zenodo (https://doi.org/10.5281/zenodo.7495214). Bambu source code is available at GitHub (https://github.com/omixlab/bambu-v2). In the benchmark, Bambu was able to produce models with higher accuracy, recall, F1 and ROC AUC when compared to QSAR-Co for the selected datasets. CONCLUSIONS: Bambu is an free and open source tool which facilitates the creation of QSAR models and can be futurely applied in a wide variety of drug discovery projects.

Cucurbiturils are useful excipients in eye drop formulations: they can increase the water solubility of the drug, enhance drug absorption into the eye, improve aqueous stability and reduce local irritation. Effective and safe drug delivery is, however, a challenge and the information on the host (CBs)/guest (tropicamide and atropine) interactions can help improving the existing treatments and develop novel therapies not limited only to eye diseases/conditions. Since this carrier system can easily modify the properties of the drug and ensure its delivery at the targeted ocular tissue, further insight into the intimate mechanism of the host-guest recognition is crucial. The present DFT/SMD study focuses on the role of numerous factors governing this process, namely the specific position of the guest molecule in the cavity of the cucurbituril, the ionization form (non/protonated) of the antimuscarinic drug, the dielectric constant of the medium, and the size of the cavitant pore. The obtained results are in line with experimental observations and shed light on the mechanism, at atomic resolution, of recognition between the CBs and the two parasympatholytic drugs.

Antibiotics enter the environment through waste streams, where they can exert selective pressure for antimicrobial resistance in bacteria. However, many antibiotics are excreted as partly metabolized forms, or can be subject to partial breakdown in wastewater treatment, soil, or through natural processes in the environment. If a metabolite is bioactive, even at sub-lethal levels, and also stable in the environment, then it could provide selection pressure for resistance. (5S)-penicilloic acid of piperacillin has previously been found complexed to the binding pocket of penicillin binding protein 3 (PBP3) of Pseudomonas aeruginosa. Here, we predicted the affinities of all potentially relevant antibiotic metabolites of ten different penicillins to that target protein, using molecular docking and molecular dynamics simulations. Docking predicts that, in addition to penicilloic acid, pseudopenicillin derivatives of these penicillins, as well as 6-aminopenicillanic acid (6APA), could also bind to this target. MD simulations further confirmed that (5R)-pseudopenicillin and 6APA bind the target protein, in addition to (5S)-penicilloic acid. Thus, it is possible that these metabolites are bioactive, and, if stable in the environment, could be contaminants selective for antibiotic resistance. This could have considerable significance for environmental surveillance for antibiotics as a means to reduce antimicrobial resistance, because targeted mass spectrometry could be required for relevant metabolites as well as the native antibiotics.

Phosphodiesterase-4, the primary enzyme responsible for cAMP degradation in the majority of immune and inflammatory cells, plays a critical role in the regulation of intracellular cAMP levels. Consequently, small molecular entities capable of inhibiting PDE4 have been employed in the treatment of inflammation-associated disorders, such as chronic obstructive pulmonary disease (COPD), psoriasis, atopic dermatitis (AD), inflammatory bowel diseases (IBD), rheumatic arthritis (RA). In the present investigation, a multi-faceted approach was employed to identify novel PDE4 inhibitors, utilizing the co-crystallization structure of PDE4B available in the Protein Data Bank (PDB) database, drug-like screening, false positive filtration, similarity and ADMET screen, as well as molecular docking via multiple software platforms, in conjunction with bioactivity assays. A thiazol-3-propanamides derivative, designated MR9, was discovered to inhibit PDE4B activity with IC50 values of 2.12 μM and suppress cellular inflammatory factor TNF-α release with an EC50 value of 3.587 μM. These findings suggest that the innovative active scaffold of MR9 offers a promising foundation for further structural refinement aimed at developing more potent PDE4 inhibitors.

The exploration of chemical systems occurs on complex energy landscapes. Comprehensively sampling rugged energy landscapes with many local minima is a common problem for molecular dynamics simulations. These multiple local minima trap the dynamic system, preventing efficient sampling. This is a particular challenge for large biochemical systems with many degrees of freedom. Replica exchange molecular dynamics (REMD) is an approach that accelerates the exploration of the conformational space of a system, and thus can be used to enhance the sampling of complex biomolecular processes. In parallel, the empirical valence bond (EVB) approach is a powerful approach for modeling chemical reactivity in biomolecular systems. Here, we present an open-source Python-based tool that interfaces with the Q simulation package, and increases the sampling efficiency of the EVB free energy perturbation/umbrella sampling approach by means of REMD. This approach, Q-RepEx, both decreases the computational cost of the associated REMD-EVB simulations, and opens the door to more efficient studies of biochemical reactivity in systems with significant conformational fluctuations along the chemical reaction coordinate.

In this work, we performed coarse-grained molecular dynamics (CGMD) simulations of G3, G4, and G5 polyamidoamine (PAMAM) dendrimers grafting with fatty acid (FTA) chains. The FTA chains of varying length and grafting densities (50% and 100% of surface terminals) correspond to pH 7 and 5, respectively. Our findings suggested that the structural properties of dendrimers were determined by dendrimer generation, polymerization degrees, and pH. With one exception, the size of the FTA grafting dendrimer shrank after fatty acid attachment. Because of the protonation of the dendrimer's interior amines at low pH, the FTA chains are distributed at the dendrimer's surface group. At pH 7, the FTA chains that have aggregated in the interior of the dendrimer cause chain crowding. Our research provided references on drug encapsulation and the lower toxicity of these hydrophobically modified nanoparticles.

We have explored the consequence of lithium and phosphorous functionalization on the graphitic carbon nitride (g-C3N4) monolayer for hydrogen storage using density functional theory. Both pristine and Li and P decorated g-C3N4 show a semiconductor nature. The substantial overlap between the s orbital of Li and the p orbital of nitrogen near the Fermi level shows the binding between Li and the g-C3N4. The repositioning of HOMO and LUMO is noticed in the Li and P decorated g-C3N4. The Bader charge analysis indicates the charge allocation from the Li and P atom to the g-C3N4, which results in the adsorption of H2 by electrostatic interaction. The hydrogen storage capacity of 5.78 wt% is obtained after functionalizing Li and P into the g-C3N4. The obtained adsorption energies for the H2 adsorption and the H2 desorption temperature confirm that Li and P functionalized g-C3N4 is a fascinating candidate for the reversible loading of H2 at ambient conditions.

This work deals with the growth investigation of the methylammonium lead triiodide (MAPbI3) thin films prepared by the spin coating technique. Firstly, MAPbI3 films were studied by X-ray diffraction (XRD) and scanning electron microscopy (SEM) and UV-Visible spectroscopy as well as photoluminescence techniques are used to calculate the band gap energy. Indeed, the high-quality MAPbI3 perovskite films were obtained by using Chlorobenzene as an antisolvent with good crystallinity, large grain sizes, and higher absorption compared to MAPbI3 treated by toluene. Secondly, the performance of FTO/TiO2/MAPbI3/Spiro OMeTAD/Au perovskite solar cell was evaluated using a numerical simulation of the Solar Cell by SCAPS simulator. The effect of the structural and physical parameters of MAPbI3 absorber layer and HTL with the different antisolvents, including thickness, defect density, total charge density, donor density and electron affinity. Obtained results are: Jsc of 25.96 mA/cm2, PCE of 30.70%, Voc of 1.259 V, FF of 88.93% of MAPbI3-based solar cells when MAPbI3 is treated by toluene. However, for MAPbI3- Chlorobenzene, the I-V characteristics are rather: Jsc of 28.18 mA/cm2, PCE of 31.81%, FF of 88.19% and Voc of 1.200 V. It is pointed out that the use of chlorobenzene may be of interest to improve the perovskites solar cells performances.

Protein-protein interactions are vital for various biological processes such as immune reaction, signal transduction, and viral infection. Molecular Dynamics (MD) simulation is a powerful tool for analyzing non-covalent interactions between two protein molecules. In general, MD simulation studies on the protein-protein interface have focused on the analysis of major and frequent molecular interactions. In this study, we demonstrate that minor interactions with low-frequency need to be incorporated to analyze the molecular interactions in the protein-protein interface more efficiently using the complex of SARS-CoV2-RBD and ACE2 receptor as a model system. It was observed that the dominance of interactions in the MD-simulated structures didn't directly correlate with the interactions in the experimentally determined structure. The interactions from the experimentally determined structure could be reproduced better in the ensemble of MD simulated structures by including the less frequent interactions compared to the norm of choosing only highly frequent interactions. Residue Interaction Networks (RINs) analysis also showed that the critical residues in the protein-protein interface could be more efficiently identified by incorporating low-frequency interactions in MD simulation. It is expected that the approach proposed in this study can be a new way of studying protein-protein interaction through MD simulation.

In this study, six small carbazole-based molecules are investigated for usage as hole transport materials (HTMs) in perovskite solar cells. Among these compounds, two molecules based on 9-(4-(thiophen-2-yl)phenyl)-9H-carbazole thiophene-phenyle and carbazole (M1 and M2) were already synthesized, and four new molecules are designed by substituting carbazole, in positions 3,6 and 2,7, with methoxyphenyl (P1 and P2) and dimethoxyphenylamine (E1 and E2). Theoretical methods used in the calculations included density functional theory and time-dependent density functional theory. FMOs of all under-probe molecules are well positioned to ensure accurate alignment and prevent charge recombination at the perovskite material interface. The molecules' absorbance in the area below 404 nm shows that HTMs cannot compete with perovskite materials in an inverted configuration of a device. Reorganization energies indicate that M1, P1,2 and E1,2 are more favourable to be HTM, while M2 shows a favourable electron transfer; it can be used as an electron transfer material (ETM). The results demonstrate that hole-electron couples can easily separate for any under-exanimated molecules, simplifying hole transport and enhancing the short-circuit (JSC). Additionally, DMPA-based molecules (E1,2) may display chemical instability because of their poor hardness and the local distribution of charge in electrostatic potential maps.

The single-point mutation D26E in human β-tubulin is associated with drug resistance seen with two anti-mitotic taxanes (paclitaxel and docetaxel) when used to treat cancers. The molecular mechanism of this resistance remains elusive. However, docetaxel and a third-generation taxane, cabazitaxel, are thought to overcome this resistance. Here, structural models of both the wildtype (WT) and D26E mutant (MT) human β-tubulin were constructed based on the crystal structure of pig β-tubulin in complex with docetaxel (PDB ID: 1TUB). The three taxanes were docked into the WT and MT β-tubulin, and the resulting complexes were submitted to three independent runs of 200 ns molecular dynamic simulations, which were then averaged. MM/GBSA calculations revealed the binding energy of paclitaxel with WT and MT β-Tubulin to be -101.5 ± 8.4 and -90.4 ± 8.9 kcal/mol, respectively. The binding energy of docetaxel was estimated to be -104.7 ± 7.0 kcal/mol with the WT and -103.8 ± 5.5 kcal/mol with the MT β-tubulin. Interestingly, cabazitaxel was found to have a binding energy of -122.8 ± 10.8 kcal/mol against the WT and -106.2 ± 7.0 kcal/mol against the MT β-tubulin. These results show that paclitaxel and docetaxel bound to the MT less strongly than the WT, suggesting possible drug resistance. Similarly, cabazitaxel displayed a greater binding propensity against WT and MT β-tubulin than the other two taxanes. Furthermore, the dynamic cross-correlation matrices (DCCM) analysis suggests that the single-point mutation D26E induces a subtle dynamical difference in the ligand-binding domain. Overall, the present study revealed how the single-point mutation D26E may reduce the binding affinity of the taxanes, however, the effect of the mutation does not significantly affect the binding of cabazitaxel.

The butadiyne-linked six-metalloporphyrin nanoring (Mg6-P6) and it's complex with a hexapyridyl template, Mg6-P6·T6 have a great potential for employment in future nanoelectronic applications such as a nanosensor for small gas molecules. The goal of this study is to scrutinize and improvement of the CO, N2, and O2 gas sensing capacity of Mg6-P6 and Mg6-P6·T6 using DFT calculations at CAM-B3LYP/6-31G (d,p) level of theory. The geometrical structures, binding energies, band gaps, the density of states (DOS), adsorption energies, HOMO and LUMO energies, Fermi level energies (EFL), NBO, FMO and TD-DFT spectrum were calculated to predict gas adsorption properties of Mg6-P6 and Mg6-P6·T6 systems. Based on the calculated adsorption energies and remarkable decrease in the Eg, it is expected that the Mg6-P6 and Mg6-P6·T6 are sensitive to O2 molecule. Surprisingly, the Mg6-P6-O2 and specially the Mg6-P6.T6-O2 record promising values of recovery times for different attempt frequencies. Therefore, the results open a way for the development of a new and selective O2 nanosensor in the presence of CO and N2 gas molecules.

In the present work, we deployed a novel orthorhombic germanane nanosheet (ortho-GeNS) as a sensing material to detect camphene and eucalyptol molecules, the indoor air pollutants in the ambient environment. In the beginning, the structural and dynamical permanency of ortho-GeNS is confirmed with cohesive energy (-4.164eV/atom) and phonon-band maps. Successively, the electronic features of ortho-GeNS are conferred using band structure along with the projected density of states maps. The energy gap of ortho-GeNS at the hybrid GGA/B3LYP level of theory is computed to be 3.948 eV. Mainly, the adsorption properties of terpinene molecules, namely camphene and eucalyptol on ortho-GeNS are investigated via ascertaining adsorption energy, Mulliken population analysis, and relative band gap variations. Besides, the scope of adsorption energy values (-0.405eVto-0.669eV) exemplifies that the target molecules are physisorbed on ortho-GeNS. Overall results suggested that the ortho-GeNS can be deployed as a worthy chemiresistive sensor to sense indoor air pollutants for monitoring indoor air quality.

Leishmaniasis is a complex neglected tropical disease caused by various leishmanial parasites that primarily affect the world's poorest people. A limited number of standard medications are available for this disease that has been used for several decades, which have drawbacks such as resistance, higher cost, and patient compliance, making it difficult to reach the poor. The search for novel chemical entities to treat leishmaniasis has led to target-based scaffold research. Thiochromone moieties in conjugation with aromatic amino acids have been considered for the study, along with possible substitutions of the electron-withdrawing and electron-donating groups. N-myristoyl transferase (NMT) has been selected as the molecular target for the study responsible for protein-protein interaction and ribosylation of proteins necessary for the growth inside the human body of the parasite. The designed novel thiochromone analogs were docked against the selected leishmanial NMT using thein-silico methods, physicochemical and toxicity properties were predicted, and Structure-Activity Relationship was also established in-silico. Finally, a molecular dynamics simulation study for 100 ns gave an idea about the stability of the protein-ligand complex. A time frame analysis of each 10 ns confirmation was also studied to understand better the putative binding pattern designed analogs.

Tuberculosis (TB) is a highly infectious disease caused by the pathogen Mycobacterium tuberculosis (Mtb). EPSP Synthase (MtEPSPS), the enzyme responsible for the sixth step of the shikimate pathway, is a potential target for the development of new drugs for the treatment of TB, as it is essential in mycobacteria but absent in humans. In this work, we performed virtual screening using sets of molecules from two databases and three crystallographic structures of MtEPSPS. The initial hits obtained from molecular docking were filtered based on predicted binding affinity and interactions with binding site residues. Subsequently, molecular dynamics simulations were carried out to analyze the stability of protein-ligand complexes. We have found that MtEPSPS forms stable interactions with several candidates, including already approved pharmaceutical drugs such as Conivaptan and Ribavirin monophosphate. In particular, Conivaptan had the highest estimated binding affinity with the open conformation of the enzyme. The complex formed between MtEPSPS and Ribavirin monophosphate was also energetically stable as shown by RMSD, Rg and FEL analyses, and the ligand was stabilized by hydrogen bonds with important residues of the binding site. The findings reported in this work could serve as the basis of promising scaffolds for the discovery, design, and development of new anti-TB drugs.

The benefits of large reserves, wide distribution, and high combustion energy density of natural gas hydrates are of great practical importance to alleviate the energy tension, enhance the existing energy system in China and reduce the greenhouse effect. The CO2 replacement method is a critical way to develop natural gas hydrate, while traditional experimental methods are difficult to reveal the microscopic mechanism of the replacement system. An MD (molecular dynamics) technique was utilized in this work to simulate the process of carbon dioxide replacement of gas hydrates. This simulation investigates the effects of temperature, pressure, and CO2 purity during the CO2 replacement process. CO2, different concentrations of CO2/H2O, and CO2/NH3 are used as the injected fluid. The simulation results show that the influence of temperature on the CO2 replacement of natural gas hydrate is more significant than that of pressure. Within the temperature and pressure range specified in the simulation, H2O inhibits the replacement of CO2, owing to the inhibitory effect increasing as the concentration of H2O increases; NH3 promotes the process of CO2 replacement under the temperature conditions of 250 K and 260 K, and the promotion effect becomes more significant as the concentration of NH3 increases. However, adding NH3 inhibits the CO2 replacement process with hydrate when the temperature lifts to 270 K. These findings provide new ideas to improve the efficiency of the CO2 replacement method and provide theoretical insight for the engineering exploitation of hydrates.

Pharmacophores are three-dimensional arrangements of molecular features required for biological activity that are often used in virtual screening efforts to prioritize ligands for experimental testing. G protein-coupled receptors (GPCR) are integral membrane proteins of considerable interest as targets for ligand discovery and drug development. Ligand-based pharmacophore models can be constructed to identify structural commonalities between known bioactive ligands for targets including GPCR. However, structure-based pharmacophores (which only require an experimentally determined or modeled structure for a protein target) have gained more attention to aid in virtual screening efforts as the number of publicly available experimentally determined GPCR structures have increased (140 unique GPCR represented as of October 24, 2022). Thus, the goal of this study was to develop a method of structure-based pharmacophore model generation applicable to ligand discovery for GPCR that have few known ligands. Pharmacophore models were generated within the active sites of 8 class A GPCR crystal structures via automated annotation of 5 randomly selected functional group fragments to sample diverse combinations of pharmacophore features. Each of the 5000 generated pharmacophores was then used to search a database containing active and decoy/inactive compounds for 30 class A GPCR and scored using enrichment factor and goodness-of-hit metrics to assess performance. Application of this method to the set of 8 class A GPCR produced pharmacophore models possessing the theoretical maximum enrichment factor value in both resolved structures (8 of 8 cases) and homology models (7 of 8 cases), indicating that generated pharmacophore models can prove useful in the context of virtual screening.

In this research, five distinct small donor molecules (designated as ACR-TPA-X1, ACR-TPA-X2, ACR-TPA-X3, ACR-TPA-X4, ACR-TPA-X5) are constructed by replacing the methoxy groups on both sides of the model molecule (ACR-TPA-R) with thiophene bridged acceptor moieties. We have used the B3LYP/6-31G (d,p) model for our computational studies. Our model molecule's morphological alteration has resulted in a lowered Eg of 1.77-2.51 eV as compared to model (ACR-TPA-R=3.84 eV). ACR-TPA-X2 investigated the λmax at 776 nm. ACR-TPA-X4 was found to be most miscible with dichloromethane (DCM). The greatest VOC(1.21 eV) was observed in ACR-TPA-X1. Among all of the variants, ACR-TPA-X1 had the highest PCE (23.42%). It was found that ACR-TPA-X4 had the highest electron mobility (0.00370 eV) and ACR-TPA-X5 had the highest hole mobility (0.00324 eV) of all the materials examined. The findings prove the worth of the methods used, paving the way for the development of effective small donors for OSCs and HTMs for PSCs.

This paper is focused on the theoretical investigation of O-C Bond Dissociation Enthalpy (BDE) of methoxy OCH3 group in 15 meta- and 15 para-substituted anisoles in gas phase, non-polar environment, and water. Density Functional Theory (DFT) calculations were carried out using M06-2X functional and 6-311++G(d,p) basis set. Obtained BDEs were correlated with Brown and Okamoto σp+ and Hammett σm constants representing commonly used descriptors of electron-donating or electron-withdrawing substituent effect. Obtained linear dependences allow the prediction of substituent effect on BDE using σp+ and σm constants. Calculated reaction enthalpies were also compared with available experimental and theoretical ab initio G4 values. Found results suggest that employed method may provide reliable thermochemistry data for demethylation of naturally occurring (poly)phenolic compounds, as well. In all studied environments, substituent induced changes in O-C BDE can be considered equal to those observed for the dissociation of phenolic O-H bond of substituted phenols.

To understand the effects of pressure on microstructural evolution, a molecular dynamics simulation study has been performed under pressures of 0-20 GPa for liquid Fe-S-Bi alloy during the solidification process. The variations in the radial distribution function, average atomic energy, and H-A bond index of the cooling system are analyzed. The rapid solidification process of liquid Fe-S-Bi alloy into crystalline and amorphous alloys is investigated from different perspective. The results show that the glass transition temperature Tg, the sizes of the MnS atomic groups, and major bond-types increase almost linearly with increasing pressure. In addition, the recovery rate of Bi increased first and then decreased with increasing pressure, reaching a peak of 68.97% under 5 GPa. The manganese sulfide compound is embedded in the alloy with a spindle-shape under 20 GPa, which is a better clusters structure.

Schistosoma glutathione transferases (GSTs) have been identified as attractive drug targets for the design of novel antischistosomals. Here, we used in silico methods to validate the discriminative inhibitory properties of bromosulfophthalein (BSP) against the 26-kDa GST from S. japonicum (Sj26GST), and the 28-kDa GST from S. haematobium (Sh28GST), versus human GST (hGST) isoforms alpha (hGSTA), mu (hGSTM) and pi (hGSTP). The use of BSP as an archetypal selective inhibitor was harnessed to produce molecular dynamics-derived pharmacophores of the two targets. Pharmacophore-based screening using a large dataset of experimental and approved drug compounds was performed to produce a shortlist of candidates. The top candidate for each target was prioritised via molecular docking, yielding guanosine-3'-monophosphate-5'-diphosphate (G3D) for Sj26GST, and quercetin-3'-O-phosphate (Q3P) for Sh28GST. Comparative molecular dynamics studies of both candidates compared to BSP showed similar characteristics of binding stability and strength, suggesting their potential to emulate the inhibitory effects of BSP.

Organic solar cells (OSCs) are capturing huge interest because of their numerous benefits, which include transparency, flexibility, and solution processability. In current project, five new donor molecules (J1-J5) were designed by employing the strategy of end capped alteration of the acceptor moieties on the two sides of the reference molecule. The Methoxy Triphenylamine hexaazatrinaphthylene (MeO-TPA-HATNA) have been used as a reference molecule in this study. DFT and TD-DFT methods employing B3LYP/6-31G (d, p) functional has been applied to perform different analysis. Geometrical, and opto-electronic features of all tailored chromophores were investigated, and comparison was made with the reference J. Among all tailored molecules, J5 shows highest λmax (862 nm) with the least band gap of 1.28 eV. TDM and DOS analysis revealed the high rate of charge transfer. Further, reorganization energy calculations are also executed to examine the charge transfer features of the designed molecules. The results shows that J5 among all these molecules has the highest rate of charge carrier (electron and hole) mobility with least RE values and this molecule can be used as a promising donor material for OSCs with remarkable charge transferring properties. Furthermore, the designed materials showed a suitable HOMO along with higher LUMO energy levels with respect to PC61BM molecule and coupling the PC61BM acceptor with investigated donor molecules gives highly increased Voc (0.66-0.76 V) than reference molecule (0.49 V) and also the power conversion efficiency (PCE) is elevated to 15.09%. The outcomes of current theoretical research have demonstrated that the end capped alteration of different acceptor groups is an excellent strategy to get OSCs with desirable photovoltaic performance. As, all the newly created molecules (J1-J5) have exhibited outstanding electronic and optical properties therefore, these can be expectedly prove excellent material for creating high efficiency future organic photovoltaic devices.

In the present work, the structure and electronic properties of Ti-, Cr-, Fe-, Ni-, Zn-, and Cu-inserted in porphyrin-reduced C70 fullerenes (TM-PIC70Fs) and their interactions with the ethenone were studied using DFT, NBO, and TD-DFT at CAM-B3LYP/6-31G(d) level of theory. 2.89-3.83 and 4.02-4.56 eV were obtained for the HOMO-LUMO gap energies and work functions of TM-PIC70Fs, respectively, compared with 3.76 and 4.54 eV for PIC70F. Among considered TM-PIC70Fs, the adsorption of the ethenone on Ti-PIC70F appreciably changed the HOMO-LUMO energy gap and work function. Consequently, Ti-PIC70F may be used as the ethenone's electronic conductivity and work function types sensor. According to calculated UV-visible spectra, the ethenone adsorption may change the color of Fe- and Ti-PIC70Fs. Therefore, they can be used as color-changing sensors of ethenone. In addition, Ti-, Cr-, Fe-, and Zn-PIC70Fs can be employed as suitable adsorbents of ethenone. Among proper sensors and adsorbents of ethenone, Cr-, Fe-, and Zn-PIC70Fs may be recovered and reused.

Acinetobacter baumannii is one of the most serious opportunistic pathogens according to WHO. The difference between bacterial and mammalian fatty acid biosynthesis pathways makes FASII enzymes attractive targets in drug discovery. 3-oxoacyl-[acyl-carrier-protein] synthase I (FabB) from the FAS II pathway catalyze the condensation of malonyl ACP with acyl-ACP, and elongates the fatty acid chain by two carbons. To investigate potential inhibitors of the A. baumannii FabB, we used computational approaches including homology modeling, high-throughput virtual screening, molecular docking, molecular dynamics simulations, and MM-GBSA free energy calculations. After the high-throughput virtual screening, the resulting ligands were further screened using the QM-polarized ligand docking (QPLD) and induced fit docking (IFD) approaches. Molecular dynamics simulations were performed for 100 ns. And according to binding free energy calculations, we have identified nine compounds with the best binding affinities. Three of these compounds were selected for an additional 1 μs MD simulation to assess ligand stability. Two of them named L6 and L7 showed promised stability and affinity to the target. Here, we present novel compounds against A. baumannii FabB via structure-based computational approaches. These compounds might pave the way for the design of new lead structures and inhibitors for multidrug-resistant A. baumannii.

Advancement in solar cells has gained the attention of researchers due to increasing demand and renewable energy sources. Modeling of electron absorbers and donors has been performed extensively for the development of efficient solar cells. In this regard, efforts are being made for designing effective units for the active layer of solar cells. In this study, CXC22 was utilized as a reference in which acetylenic anthracene acted as a π bridge and infrastructure was D-π-A. We theoretically designed four novel dye-sensitized solar cells JU1-JU4 by utilizing reference molecules to improve the photovoltaic and optoelectronic properties. All designed molecules differ from R by donor moiety modifications. Different approaches were done to R and all molecules to explore different analyses like binding energies, excitation energies, dipole moment, TDM (transition density matrix), PDOS (partial density of states), absorption maxima, and charge transfer analysis. For the evaluation of results, we used the DFT technique and the findings demonstrated that the JU3 molecule showed a better redshift absorption value (761 nm) as compared to all other molecules due to the presence of anthracene in the donor moiety which lengthens the conjugation. JU3 was proven to be the best candidate among all due to improved excitation energy (1.69), low energy band gap (1.93), higher λmax value, and improved electron and hole energy values leading toward higher power conversion efficiency. All the other theoretically formed molecules exhibited comparable outcomes as compared to a reference. As a result, this work revealed the potential of organic dyes with anthracene bridges for indoor optoelectronic applications. These unique systems are effective contributors to the development of high-performance solar cells. Thus, we provided efficient systems to the experimentalists for the future development of solar cells.

Alzheimer's disease is associated with accumulating different amyloid peptides on the nerve cell membranes. The non-thermal effects of the GHz electric fields in this topic have yet to be well recognized. Hence, in this study, the impacts of 1 and 5 GHz electric fields on the amyloid peptide proteins accumulation on the cell membrane have been investigated, utilizing molecular dynamics (MD) simulation. The obtained results indicated that this range of electric fields did not significantly affect the peptide structure. Moreover, it was found that the peptide penetration into the membrane was increased as the field frequency was increased when the system was exposed to a 20 mv/nm oscillating electric field. In addition, it was observed that the protein-membrane interaction is reduced significantly in the presence of the 70 mv/nm electric field. The molecular level results reported in this study could be helpful in better understanding Alzheimer's disease.

Multiple Sclerosis (MS) is a demyelinating disease of the central nervous system that disturbs the flow of brain signals to other parts of the body. The actual cause of the disease is still not apparent. The intrinsically disordered proteins (IDP) play a crucial role in neurodegenerative diseases like Alzheimer's, Lewy bodies, Parkinson's, Amyotrophic Lateral Sclerosis, Multiple Sclerosis, etc. In MS, it was known that the immune system attacks the proteins like Myelin Basic Protein (MBP), Myelin-associated Oligodendrocyte Basic protein (MOBP), Myelin-Associated Protein (MAG), and Myelin Proteolipid Protein (PLP) and this leads to demyelination causing MS. Here the proteins MBP and MOBP are both moonlighting intrinsically disordered proteins and exist between the myelin sheath, unlike MAG which is a transmembrane protein. The main focus of the article was to examine the significant role of proteins intrinsically disordered regions (IDR) in maintaining their function. Molecular dynamics simulation studies were performed to study the conformational dynamics of these protein IDRs both in water and near the myelin sheath. The results suggest that the IDR dominates the structural dynamics of these proteins and IDR in both proteins was responsible for their interaction with the myelin sheath. Interestingly, it was noted that the known epitopes MBP83-96 and MOBP65-87 in the IDR have no interaction with the myelin sheath. Thus when the protein remains intrinsically disordered it maintains the proper function and myelin integrity and if it adopts folds the region was identified as an epitope by the immune system leading to demyelination causing MS.

With the development of alternate electrical power system and the improvement of voltage level, the operation conditions faced by epoxy resin (ER) insulation materials are becoming more and more complex. The traditional ER materials have been difficult to meet the increasingly stringent requirements. In this paper, the thermal and mechanical properties of DGEBA/TDE-85/MTHPA blend system were studied by molecular dynamics (MD) simulation and experiment. The results show that the addition of TDE-85 can significantly improve the thermal and mechanical properties, and the comprehensive improvement effect is the best when the molar ratio of DGEBA and TDE-85 is about 8:2. The experimental results are consistent with the simulation results. Further analysis of the micro-parameters of the monomer and the cross-linking network found that the torsional energy barrier of TDE-85 is higher than DGEBA. And the compatibility of the two ER is better when the ratio is 8:2. In addition, TDE-85 can introduce high-stability Y-nodes into the system, making the cross-linked network more stable, which has a significant effect on improving the thermal and mechanical properties. The research provide a reference for the blending modification of high-performance ER for high-voltage insulation.

Amyloid-beta (Aβ) protofibrils are closely related to Alzheimer's disease. Their behaviors with or without the presence of Aβ fibrillization inhibitors have been intensively studied by molecular dynamics simulations. In this work, the molecular mechanisms of licochalcone A and licochalcone B on destabilizing Aβ(1-42) protofibrils are explored. It is found that both two licochalcones can disorder the configuration of the Aβ(1-42) protofibril. The stable interactions between the Aβ(1-42) protofibril and licochalcone A or licochalcone B are able to be formed. A reduction of the β-sheet structure contents and an increment of the random coil structures of Aβ(1-42) protofibril are observed in the presence of either licochalcone A or licochalcone B. The hydrogen bonds inside the Aβ(1-42) protofibril could be partially collapsed to varying degrees by two licochalcones. Furthermore, the van der Waals interactions between Aβ(1-42) protofibril and licochalcone A make an important contribution to the binding free energy, while the contribution of the electrostatic interactions between Aβ(1-42) protofibril and licochalcone B is more prominent in the binding affinity. Our work may help in the development of new drug candidates for disrupting the Aβ protofibril.

In this paper, we design new forms of organic conjugated compounds-based quinoxaline derivatives. Specifically, we exploit density functional theory and time-dependent-density functional theory in order to study the structure, the optic, the electronic, the reorganization energy and the photovoltaic features of such new molecules. Particularly, all engineered compounds have a narrow band gap in the range of 0.696-0.721 eV, high oscillator frequency and good optical properties. Moreover, the PCBM is employed as an electron acceptor. Employing global reactivity descriptors, we demonstrate that the molecules can efficiently emit electrons into the PCBM and the electrons are attracted to PCBM from molecules. In addition, the results show an appropriate open circuit voltage in the range of 0.338-0.362 V. The proposed compounds exhibit excellent electron transport and charge conduction from the donor to the acceptor. These new molecules show potential properties to develop bulk heterojunction organic photovoltaic cells.

Simplified Molecular-Input Line-Entry System (SMILES) is one of a widely used molecular representation methods for molecular property prediction. We conjecture that all the characters in the SMILES string of a molecule are essential for making up the molecules, but most of them make little contribution to determining a particular property of the molecule. Therefore, we verified the conjecture in the pre-experiment. Motivated by the result, we propose to inject proper noisy information into the SMILES to augment the training data by increasing the diversity of the labeled molecules. To this end, we explore injecting perturbing noise into the original labeled SMILES strings to construct augmented data for alleviating the limitation of the labeled compound data and enhancing the model to extract more useful molecular representation for molecular property prediction. Specifically, we directly adopt mask, swap, deletion, and fusion operations on SMILES strings to randomly mask, swap, and delete atoms in SMILES strings. Then, the augmented data is used by two strategies: each epoch alternately feeds the original and perturbing noisy molecules, or each batch alternately feeds the original and perturbing noisy molecules. We conduct experiments on both Transformer and BiGRU models to validate the effectiveness by adopting widely used datasets from MoleculeNet and ZINC. Experimental results demonstrate that the proposed method outperforms strong baselines on all the datasets. NoiseMol obtains the best performance on BBBP and FDA when compared with state-of-the-art methods. Besides, NoiseMol achieves the best accuracy on LogP. Therefore, injecting perturbing noise into the labeled SMILES strings is an effective and efficient method, which improves the prediction performance, generalization, and robustness of the deep learning models.

Autophagy is an important cellular process that triggers a coordinated action involving multiple individual proteins and protein complexes while SARS-CoV-2 (SARS2) was found to both hinder autophagy to evade host defense and utilize autophagy for viral replication. Interestingly, the possible significant stages of the autophagy biochemical network in relation to the corresponding autophagy-targeted SARS2 proteins from the different variants of concern (VOC) were never established. In this study, we performed the following: autophagy biochemical network design and centrality analyses; generated autophagy-targeted SARS2 protein models; and superimposed protein models for structural comparison. We identified 2 significant biochemical pathways (one starts from the ULK complex and the other starts from the PI3P complex) within the autophagy biochemical network. Similarly, we determined that the autophagy-targeted SARS2 proteins (Nsp15, M, ORF7a, ORF3a, and E) are structurally conserved throughout the different SARS2 VOC suggesting that the function of each protein is preserved during SARS2 evolution. Interestingly, among the autophagy-targeted SARS2 proteins, the M protein coincides with the 2 significant biochemical pathways we identified within the autophagy biochemical network. In this regard, we propose that the SARS2 M protein is the main determinant that would influence autophagy outcome in regard to SARS2 infection.

The quest in finding an everlasting panacea to the pernicious impact of sickle cell disease (SCD) in the society hit a turn of success since the recent discovery of a small molecule reversible covalent inhibitor, Voxelotor. A drug that primarily promotes the stability of oxygenated hemoglobin and inhibit the polymerization of HbS by enhancing hemoglobin's affinity for oxygen has opened a new frontier in drug discovery and development. Despite eminent efforts made to reproduce small molecules with better therapeutic targets, none has been successful. To this end, we employed the use of structure-based computational techniques with emphasis on the electrophilic warhead group of Voxelotor to harness novel covalent binders that could elicit better therapeutic response against HbS. The PubChem database and DataWarrior software were used to design random molecules using Voxelotor's electrophilic functionality. Following the compilation of these chemical entities, a high-throughput covalent docking-based virtual screening campaign was conducted which revealed three (Compound_166, Compound_2301, and Compound_2335) putative druglike candidates with higher baseline energy value compared to the standard drug. Subsequently, in silico ADMET profiling was carried out to evaluate their pharmacokinetics and pharmacodynamics properties, and their stability was evaluated for 1 μs (1 μs) using molecular dynamics simulation. Finally, to prioritize these compounds for further development in drug discovery, MM/PBSA calculations was employed to evaluate their molecular interactions and solvation energy within the HbS protein. Despite the admirable druglike and stability properties of these compounds, further experimental validations are required to establish their preclinical relevance for drug development.

Innovations in drug-target interactions (DTIs) prediction accelerate the progression of drug development. The introduction of deep learning models has a dramatic impact on DTIs prediction, with a distinct influence on saving time and money in drug discovery. This study develops an end-to-end deep collaborative learning model for DTIs prediction, called EDC-DTI, to identify new targets for existing drugs based on multiple drug-target-related information including homogeneous information and heterogeneous information by the way of deep learning. Our end-to-end model is composed of a feature builder and a classifier. Feature builder consists of two collaborative feature construction algorithms that extract the molecular properties and the topology property of networks, and the classifier consists of a feature encoder and a feature decoder which are designed for feature integration and DTIs prediction, respectively. The feature encoder, mainly based on the improved graph attention network, incorporates heterogeneous information into drug features and target features separately. The feature decoder is composed of multiple neural networks for predictions. Compared with six popular baseline models, EDC-DTI achieves highest predictive performance in the case of low computational costs. Robustness tests demonstrate that EDC-DTI is able to maintain strong predictive performance on sparse datasets. As well, we use the model to predict the most likely targets to interact with Simvastatin (DB00641), Nifedipine (DB01115) and Afatinib (DB08916) as examples. Results show that most of the predictions can be confirmed by literature with clear evidence.

The activated carbon in the vehicle's carbon canister needs to adsorb a variety of VOCs (Volatile Organic Compounds) emitted by gasoline evaporation, while the difference in gas adsorption capacity can lead to adsorption competition phenomena. In this study, three typical VOCs (toluene, cyclohexane, and ethanol) were selected to study the adsorption competition characteristics between multi-component gases at different pressures by molecular simulation method. In addition, the effect of temperature on adsorption competition was also investigated. The results show that the selectivity of activated carbon to toluene is negatively correlated with the adsorption pressure, but the opposite is true for ethanol, and the change of cyclohexane is not significant. The competitive order of the three VOCs is toluene > cyclohexane > ethanol at low pressure, which becomes ethanol > toluene > cyclohexane at high pressure. With increasing pressure, the interaction energy decreases from 12.87 kcal/mol to 11.87 kcal/mol, where the electrostatic interaction energy increases from 1.97 kcal/mol to 2.54 kcal/mol. In microporous activated carbon, the competition is mainly manifested in that ethanol preempts the low-energy adsorption sites of toluene in the pore size of 10 Å to 18 Å, while gas molecules near the surface of activated carbon or in smaller pore sizes are stably adsorbed without competition. Despite the fact that high temperature decreases the total adsorption capacity, activated carbon selectivity for toluene increases instead, while the competitiveness of polar ethanol decreases significantly.

Kirsten rat sarcoma virus G12C (KRASG12C) is the major protein mutation associated with non-small cell lung cancer (NSCLC) severity. Inhibiting KRASG12C is therefore one of the key therapeutic strategies for NSCLC patients. In this paper, a cost-effective data driven drug design employing machine learning-based quantitative structure-activity relationship (QSAR) analysis was built for predicting ligand affinities against KRASG12C protein. A curated and non-redundant dataset of 1033 compounds with KRASG12C inhibitory activity (pIC50) was used to build and test the models. The PubChem fingerprint, Substructure fingerprint, Substructure fingerprint count, and the conjoint fingerprint-a combination of PubChem fingerprint and Substructure fingerprint count-were used to train the models. Using comprehensive validation methods and various machine learning algorithms, the results clearly showed that the XGBoost regression (XGBoost) achieved the highest performance in term of goodness of fit, predictivity, generalizability and model robustness (R2 = 0.81, Q2CV = 0.60, Q2Ext = 0.62, R2 - Q2Ext = 0.19, R2Y-Random = 0.31 ± 0.03, Q2Y-Random = -0.09 ± 0.04). The top 13 molecular fingerprints that correlated with the predicted pIC50 values were SubFPC274 (aromatic atoms), SubFPC307 (number of chiral-centers), PubChemFP37 (≥1 Chlorine), SubFPC18 (Number of alkylarylethers), SubFPC1 (number of primary carbons), SubFPC300 (number of 1,3-tautomerizables), PubChemFP621 (N-C:C:C:N structure), PubChemFP23 (≥1 Fluorine), SubFPC2 (number of secondary carbons), SubFPC295 (number of C-ONS bonds), PubChemFP199 (≥4 6-membered rings), PubChemFP180 (≥1 nitrogen-containing 6-membered ring), and SubFPC180 (number of tertiary amine). These molecular fingerprints were virtualized and validated using molecular docking experiments. In conclusion, this conjoint fingerprint and XGBoost-QSAR model demonstrated to be useful as a high-throughput screening tool for KRASG12C inhibitor identification and drug design.

Herein, we investigated the stability of lead halide perovskites under ambient conditions after mixing the two cations Formamidinium (FA) and Cesium (Cs). The CsxFA1-xPbI3 perovskites solutions were prepared with different contents of x (0.0, 0.3, 0.5, 0.7 and 1.0) and deposited on substrates by spin-coating technique. The CsxFA1-xPbI3 films were, afterwards, characterized using the X-ray diffraction (XRD), UV-visible spectroscopy, photoluminescence (PL) spectra and scanning electron microscopy (SEM) to figure out their crystallinity, morphology, and optical properties. We noticed a stable perovskite structure for the mixed compounds unalike the pure FA and Cs films. The XRD analysis revealed, even after two weeks, the growth and good stability after two weeks of the desired black cubic α-phase perovskite structure in opposite to FAPbI3 and CsPbI3 which, respectively, showed faster degradation and transition into non-perovskite δ-phase and ɣ-phase no perovskite phases. The mixed perovskites Cs-FA also displayed a high absorbance especially for the ones with 30% of Cs and 70% of FA or 50% of each, with an excellent band gap energy ranging between 1.52 and 1.7 eV where FAPbI3 and CsPbI3 were showing a bandgap between 1.5 and 1.9 eV respectively. Moreover, the performance of the CsxFA1-xPbI3 based solar cells were simulated with SCAPS by using the band gaps obtained from the experimental study and after by varying the band gap, the thickness of the absorber layers and then different types of Electron Transport Layer (ETL). The simulation results revealed that the Cs0.3FA0.7PbI3 based solar cells had the highest higher efficiency around 22.36%.

There is scarce information on the vibrational and thermal properties of small Ni clusters. Here, the outcomes of ab initio spin-polarized density functional theory calculations on the size and geometry effects upon the vibrational and thermal properties of Nin (n = 13 and 55) clusters, are discussed. For theses clusters a comparison is presented between the closed shell symmetric octahedral (Oh) and the icosahedral (Ih) geometries. The results indicate that the Ih isomers are lower in energy. Besides, ab initio molecular dynamics runs at T = 300K show that Ni13 and Ni55 clusters transform from their initial Oh geometries towards the corresponding Ih ones. For Ni13, we also consider the lowest energy less symmetric layered 1-3-6-3 structure, and the cuboid, recently observed experimentally for Pt13, which is competitive in energy but is unstable, as phonon analysis reveals. We calculate their vibrational density of states (νDOS) and heat capacity, and compare with the Ni FCC bulk counterpart. The characteristic features of the νDOS curves of these clusters are interpreted in terms of the clusters' sizes, the interatomic distance contractions, the bond order values as well as the internal pressure and strains of the clusters. We find that the softest possible frequency of the clusters is size and structure-dependent, being the smallest for the Oh ones. We identify mostly shear, tangential type displacements involving mainly surface atoms for the lowest frequency of the spectra of both Ih and Oh isomers. For the maximum frequencies of these clusters the central atom shows anti-phase movements against groups of nearest neighbor atoms. An excess of heat capacity at low temperatures with respect to the bulk is found, while at high temperatures a constant limiting value, close but lower to the Dulong and Petit value, is determined.

We designed a series of single transition metal-anchored arsenene coordinated with nitrogen atoms (TMNx@As) as electrocatalysts for chlorine evolution reaction (CER). Density functional theory (DFT) and machine learning were employed to investigate the catalytic activity of TMNx@As. It is found that the performance of TMNx@As is the best when the transition metal is Pd and the nitrogen coordination content is 66.67%. The catalytic activity of TMNx@As for chlorine evolution reaction is mainly determined by the covalent radius (Rc) and atomic non-bonded radius (Ra) of the transition metal and the fraction of N atoms in metal's coordinating atoms (fN).

The hierarchical silicoaluminophosphate (SAPO-34) catalyst was synthesized using the mixtures of diethylamine (D) and butylamine (B) as a structure-directing agent (SDA), and carbon nanotube (CNT) as a secondary template in the hydrothermal method. The catalysts were characterized by Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDX), N2 physisorption, and temperature-programmed desorption of ammonia (NH3-TPD) techniques and evaluated for the catalytic activity in the Methanol to Olefins (MTO) process. The results showed that the use of CNT as the secondary template improved the hierarchical structure of SAPO-34 due to increasing the external surface area and mesoporosity and decreasing the particle size and as a result, made better the performance of the prepared SAPO-34 zeolite in the MTO process. Among all the prepared samples, the CNT-B-D catalyst synthesized by mixing three templates displayed the highest ethylene and propylene selectivity of 49% and 34%, respectively. Also, using CNT in the synthesis of samples increased the catalytic stability. In addition, pure, binary, and ternary adsorption isotherms and diffusivities of the main products and reactants over the SAPO-34 were investigated by theoretical measurements, because sorption and diffusion affect the catalyst stability and C2-C3 selectivity in the MTO reaction. The higher diffusion rate of ethylene leads to following the aromatic-based cycle in the MTO process.

Exploring allosteric inhibition and the discovery of new inhibitor binding sites are important studies in protein regulation mechanisms and drug discovery. Structural and network-based analyses of trajectories resulting from molecular dynamics (MD) simulations have been developed to discover protein dynamics, landscape, functions, and allosteric regions. Here, an experimentally suggested non-competitive inhibitor, xanthene-11v, was considered to explore its allosteric inhibition mechanism in α-glucosidase MAL12. Comparative structural and network analyses were applied to eight 250 ns independent MD simulations, four of which were performed in the free state and four of which were performed in ligand-bound forms. Projected two-dimensional free energy landscapes (FEL) were constructed from the probabilistic distribution of conformations along the first two principal components. The post-simulation analyses of the coordinates, side-chain torsion angles, non-covalent interaction networks, network communities, and their centralities were performed on α-glucosidase conformations and the intermediate sub-states. Important communities of residues have been found that connect the allosteric site to the active site. Some of these residues like Thr307, Arg312, TYR344, ILE345, Phe357, Asp406, Val407, Asp408, and Leu436 are the key messengers in the transition pathway between allosteric and active sites. Evaluating the probability distribution of distances between gate residues including Val407 in one community and Phe158, and Pro65 in another community depicted the closure of this gate due to the inhibitor binding. Six macro states of protein were deduced from the topology of FEL and analysis of conformational preference of free and ligand-bound systems to these macro states shows a combination of lock-and-key, conformational selection, and induced fit mechanisms are effective in ligand binding. All these results reveal structural states, allosteric mechanisms, and key players in the inhibition pathway of α-glucosidase by xanthene-11v.

Retinoids play crucial roles in various biological processes by interacting with their carrier proteins such as cellular retinol-binding protein (CRBP). Understanding the molecular interactions between retinoids and CRBP enables their pharmacological and biomedical applications. Experimentally, CRBP(I) does not bind to retinoic acid, but when arginine is introduced into 108th residue instead of glutamine (Q108R), it binds to retinoic acid. Here, molecular dynamics simulations were performed to understand the differences in the microscopic and dynamic behaviors of the non-binding wild-type CRBP(I)-retinoic acid and binding Q108R variant-retinoic acid complexes. The ligand RMSD and RMSF, the binding poses of binding motif amino acids, and the number of hydrogen bonds and salt-bridges revealed the relative instability of the non-binding complex. In particular, the ligand's terminal group showed very different dynamics and interactions. So far, most studies have focused on the binding characteristics of retinoids, but the features of their non-binding modes have not been studied well. This study provides some structural insights into the non-binding modes of a retinoid in CRBP, which may be applicable in retinoid-based drug discovery and protein engineering through computational modeling.

The scarcity of efficient force fields to describe metal complexes may be a problem for new advances in medicinal chemistry. Thus, the development of force fields for these compounds can be valuable for the scientific community, especially when it comes to molecules that show interesting outputs regarding potential treating of diseases. Vanadium complexes, for instance, have shown promising results towards therapeutics of Alzheimer's Disease, most notably the bis(maltolato)oxovanadium (IV). Therefore, the mainly goal of this work is to develop and validate a new set of parameters for this vanadium complex from a minimum energy structure, obtained by DFT calculations, where great results of the new force field are found when confronted with experimental and quantum reference values. Moreover, the new force field showed to be quite effective to describe the molecule of under study whilst GAFF could not describe it effectively. In addition, a case study points out hydrogen bonds in the vanadium complex-PTP1B system.

The mechanism and dynamics of CHF2CF2OCHF2 initiated by OH radical evaluated through the density functional theory and variflex code. The solvation pattern of PCM was utilized to analyze the influence of water on the CHF2CF2OCHF2 + OH reaction. The most feasible reaction channel is resulting in the product CF2CF2OCHF2 with H2O by hydrogen abstraction. The computed rate coefficient is consistent with the experimental data. The results turned out that aqueous water act as a disincentive to the title reaction. In the atmosphere, the computation results testified that OH, H2O, NH3 and HCOOH could not accelerate the degradation of the CHF2CF2OCHF2 through OH-initiated in view of the Gibbs free barriers. The research of the follow-up oxidation procedure of the products CHF2CF2OCF2 and CF2CF2OCHF2 with O2/NO reactions indicated that CF2O and CHF2 were the most feasible products. The atmospheric lifetimes of CHF2CF2OCHF2 were in the scope of 71.10-4.74 years in altitude of 0-12 km and at 200-300 K. This research supplies discernment into the conversion of CHF2CF2OCHF2 in a complex environment.

Type 2 diabetes can cause a variety of complications, significantly affecting people's health. Given their ability to suppress carbohydrate digestion, alpha-glucosidase inhibitors are effective treatments for diabetes. However, the current approved glucosidase inhibitors' side effects of abdominal discomfort limit their use. We used the compound Pg3R from the natural fruit berry as a reference, screening against a large database of 22 million compounds to identify potential health-friendly alpha-glucosidase inhibitors. Ligand-based screening enables us to identify 3968 ligands that exhibit structural similarity compared to the natural compound. These lead hits were used for LeDock, and their binding free energies were evaluated by MM/GBSA. Among the top-scoring candidates, ZINC263584304 exhibited the strongest binding affinity to alpha-glucosidase, with a "low-fat" structural characteristic. Its recognition mechanism was further investigated by microsecond MD simulations and free energy landscapes, exhibiting novel conformational changes during the binding process. Our study provided a novel alpha-glucosidase inhibitor with the potential to treat type 2 diabetes.

The sulfur adsorption on gold surface is a hot topic in catalysis, electrochemistry and chemical sensors. However, the multiple structures of adsorbed sulfur and sulfur-induced reconstruction in gold substrate topography are still open problems until now. Here we performed an extensively study on sulfur adsorption on Au(111) surface based on First-Principles calculation. Our results show that the sulfur adsorption with additional Au atoms is not favorable. Thus, the well-known lifting of the herringbone reconstruction of Au(111) after sulfur adsorption can't be attributed to the lifting gold atoms. More importantly, we proposed an extremely stable configuration of S-Au(111) surface characterized by (√3 × √3)R30° at 0.33 coverage, in which each S atom is chemisorbed in 3-fold coordinated sites and all the surface-Au atoms are terminated. Finally, the good agreement between our simulated STM and LEED images and experimental observations illuminates the truth that our proposed configuration is also favorable in experiment. This super stable S-adsorbed surface can be used as a starting point for the growth of two dimensional transition metal sulfides.

In this study, oxygenated triarylmethyl (oxTAM) is investigated by DFT calculations as a drug carrier framework for Nitrosourea (NU) and Fluorouracil (FU) drugs. Based on the adsorption analysis i.e., energies and distances between interacting atoms, it is found that oxTAM exhibits excellent carrier abilities for the delivery of FU (-1.53 eV & 2.00 Å) and NU (-1.33 eV & 2.12 Å) drugs. NCI and QTAIM results indicate the presence of hydrogen bonding in drug-carrier complexes. The values of dipole moment and global chemical descriptors show the significant reactivity of oxTAM for NU and FU drugs. Based on electronic property analysis, FU@oxTAM has a higher adsorption trend for complexation with oxTAM as compared to NU@oxTAM. Moreover, FU can easily release from the carrier due to the decreasing adsorption stability after protonation under an acidic environment as well as a short recovery time observed for the oxTAM carrier surface. Keeping in view all the above parameters, we inferred that oxTAM can serve as a potential drug delivery system for anticancer drugs including, Nitrosourea and Fluorouracil drugs.

The current work aimed to predict three critical properties: critical temperature (Tc), critical volume (Vc), and critical pressure (Pc) of pure hydrocarbons. A multi-layer perceptron artificial neural network (MLP-ANN) has been adopted as a nonlinear modeling technique and computational approach based on a few relevant molecular descriptors. A set of diverse data points was used to build three QSPR-ANN models, including 223 points for Tc, Vc, and 221 for Pc. The entire database was randomly split into two subsets: 80% for the training set and 20% for the testing set. A large number of 1666 molecular descriptors were calculated and then reduced by a statistical methodology based on several phases to retain them into a reasonable number of relevant descriptors, wherein about 99% of initial descriptors were excluded. Thus, the Quasi-Newton backpropagation (BFGS) algorithm was applied to train the ANN structure. The results of three QSPR-ANN models showed good precision, confirmed by the high values of determination coefficient (R2) ranging from 0.9990 to 0.9945, and the low values of calculated errors, such as the Mean Absolute Percentage Error (MAPE) that ranged from 2.2497 to 0.7424% for the best three models of Tc, Vc, and Pc. The weight sensitivity analysis method was applied to know the contribution of each input descriptor individually or by class on each appropriate QSPR-ANN model. Moreover, the applicability domain (AD) method was also used with a strict limit of standardized residual values (di = ±2). However, the results were promising, with nearly 88% of the data points validated within the AD range. Finally, the results of the proposed QSPR-ANN models were compared with other well-known QSPR or ANN models for each property. Consequently, our three models provided satisfactory results, outperforming most of the models mentioned in this comparison. This computational approach can be applied in petroleum engineering and other related fields to accurately determine the critical properties of pure hydrocarbons: Tc, Vc, and Pc.

Pristine and halogen doped β12 borophene, as anode of lithium-ion batteries (LIBs) and sodium-ion batteries (SIBs), was considered by first-principles study based on density functional theory. Li and Na were adsorbed on β12 borophene with adsorption energies of -3.18 eV and -2.33 eV, respectively. The effect of halogen addition, X = F, Cl, Br, and I, to borophene sheet on adsorption and also diffusion pathways of Li and Na was studied. The adsorption energy calculations show that the halogen atoms improve Li/Na adsorption on borophene sheet. Also, the results indicate that Li/Na adsorption energies on Brominated borophene sheet are higher compared to other halogen types. Diffusion calculations show that Br addition induces an electron deficiency on BoBr surface which lowers the energy barrier of migration of Li and Na ions compared to the pristine borophene. According to density of states analysis, electron charge is transferred from Li and Na atoms toward halogenated borophene sheet. Also, it can be concluded that electron transfer from Li/Na to borophene host in BoX is higher compared to pristine borophene which is in agreement with adsorption energies. The fully lithiated/sodiated complexes of BoBr are Li0.71BoBr and Na0.50BoBr which is equivalent to theoretical specific capacities of 1401 and 981 mAh/g which are about 3.5 and 2.6 times higher than graphite for Li and Na adsorption, respectively. Higher specific capacity of Li compared to Na is mainly attributed to steric hindrance of Na regarding its greater size. Open circuit voltage values of 1.6 V and 1.4 V were obtained for Li and Na intercalation processes, respectively, into halogen added β12 borophene indicating that this structure can be applied as anode for both LIB and SIB systems.

Deep eutectic solvents (DESs) have emerged as the promising replacement to the ionic liquids in solvent engineering for bio-compatibility. We aim to understand the effect of aqueous deep eutectic solvents on the conformation of intrinsically disordered proteins (IDPs). In this context, we have studied the effect on amyloid beta (Aβ42) monomer in the hydrated DES composed of tetrabutylammonium chloride and ethylene glycol in a 3:1 ratio using all-atom molecular dynamics simulations. DES is found to effectively screen the interaction of four zones of the amyloid beta monomer with water. Water molecules and the DES constituents modulate the local protein-solvent interactions, in the solvation shell of the protein. In addition, the aqueous DES medium conserves the secondary structure of the Aβ42 monomer by increasing the intramolecular hydrogen bonding and D23-K28 salt-bridge interactions when compared to the pure water medium. The current study provides insights into the impact of DES in stabilizing an IDP, at molecular level. We envisage the hindered aggregation of the amyloid beta structures in DES medium over the pure water medium due to the screening of hydrophobic intramolecular interactions.

Pharmacophore models are three-dimensional arrangements of molecular features required for biological activity that are used in ligand identification efforts for many biological targets, including G protein-coupled receptors (GPCR). Though GPCR are integral membrane proteins of considerable interest as targets for drug development, many of these receptors lack known ligands or experimentally determined structures necessary for ligand- or structure-based pharmacophore model generation, respectively. Thus, we here present a structure-based pharmacophore modeling approach that uses fragments placed with Multiple Copy Simultaneous Search (MCSS) to generate high-performing pharmacophore models in the context of experimentally determined, as well as modeled GPCR structures. Moreover, we have addressed the oft-neglected topic of pharmacophore model selection via development of a cluster-then-predict machine learning workflow. Herein score-based pharmacophore models were generated in experimentally determined and modeled structures of 13 class A GPCR and resulted in pharmacophore models exhibiting high enrichment factors when used to search a database containing 569 class A GPCR ligands. In addition, classification of pharmacophore models with the best performing cluster-then-predict logistic regression classifier resulted in positive predictive values (PPV) of 0.88 and 0.76 for selecting high enrichment pharmacophore models from among those generated in experimentally determined and modeled structures, respectively.

The main protease of SARS-CoV-2 (called Mpro or 3CLpro) is essential for processing polyproteins encoded by viral RNA. Several Mpro mutations were found in SARS-CoV-2 variants, which are related to higher transmissibility, pathogenicity, and resistance to neutralization antibodies. Macromolecules adopt several favored conformations in solution depending on their structure and shape, determining their dynamics and function. In this study, we used a hybrid simulation method to generate intermediate structures along the six lowest frequency normal modes and sample the conformational space and characterize the structural dynamics and global motions of WT SARS-CoV-2 Mpro and 48 mutations, including mutations found in P.1, B.1.1.7, B.1.351, B.1.525 and B.1.429+B.1.427 variants. We tried to contribute to the elucidation of the effects of mutation in the structural dynamics of SARS-CoV-2 Mpro. A machine learning analysis was performed following the investigation regarding the influence of the K90R, P99L, P108S, and N151D mutations on the dimeric interface assembling of the SARS-CoV-2 Mpro. The parameters allowed the selection of potential structurally stable dimers, which demonstrated that some single surface aa substitutions not located at the dimeric interface (K90R, P99L, P108S, and N151D) are able to induce significant quaternary changes. Furthermore, our results demonstrated, by a Quantum Mechanics method, the influence of SARS-CoV-2 Mpro mutations on the catalytic mechanism, confirming that only one of the chains of the WT and mutant SARS-CoV-2 Mpros are prone to cleave substrates. Finally, it was also possible to identify the aa residue F140 as an important factor related to the increasing enzymatic reactivity of a significant number of SARS-CoV-2 Mpro conformations generated by the normal modes-based simulations.

In the present work, the drug-loading efficacy of graphyne (GYN) for doxorubicin (DOX) drug is investigated for the first time by using density functional theory (DFT). Doxorubicin drug is effective in the cure of numerous types of cancer including bone cancer, gastric, thyroid, bladder, ovarian, breast, and soft tissue cancer. Doxorubicin drug prevents the cell division process by intercalating in the double-helix of DNA and stopping its replication. The optimized, geometrical, energetic, and excited-state characteristics of graphyne (GYN), doxorubicin drug (DOX), and doxorubicin-graphyne complex (DOX@GYN complex) are calculated to see how effective it is as a carrier. The DOX drug interacted with GYN with an adsorption-energy of -1.57 eV (gas-phase). The interaction of GYN with DOX drug is investigated using NCI (non-covalent interaction) analysis. The findings of this analysis showed that the DOX@GYN complex has weak forces of interaction. Charge transfer from doxorubicin drug to GYN during DOX@GYN complex formation is described by charge-decomposition analysis and HOMO-LUMO analysis. The increased dipole-moment (8.41 D) of the DOX@GYN in contrast with therapeutic agent DOX and GYN indicated that the drug will move easily in the biochemical system. Furthermore, the photo-induced electron-transfer process is explored for excited states, and it reveals that upon interaction, fluorescence-quenching will occur in the complex DOX@GYN. In addition, the influence of the positive and negative charge states on the GYN and DOX@GYN is also considered. Overall, the findings indicated that the GYN could be exploited as an effective drug-transporter for the delivery of doxorubicin drug. Investigators will be inspired to look at another 2D nanomaterials for drug transport applications as a result of this theoretical work.

Protein oxidative modifications with reactive carbonyl species (RCS) is directly linked to metabolic processes in premature aging, cancer, neurodegenerative and infectious diseases. RCS as 4-Hydroxy-2-nonal (HNE), 4-Hydroxy-2-hexenal (HHE), 4-Oxo-2-nonenal (ONE) and Malondialdehyde (MDA) attack nucleophilic amino acids residues forming irreversible adducts with proteins as Thioredoxins (Trx). This is a class of small thiol oxide-reductases playing a key role in redox signaling and oxidative stress responses in mammals. Although proteomic studies have identified to Cys-32 residue as a target of HNE attack that inhibit its enzymatic activity, how this carbonylation affects its structure and dynamic behavior at the atomic level is unknown. Even more, the molecular bases for the atomistic behavior of these modified proteins have not been completely understood. We present molecular dynamics simulations of Trx-modified with four different RCS to analyze its global and local structural effects. For this, parameters supported in the AMBER force fields were built and validated for three non-natural cysteine residues modified with HHE, ONE and MDA. Results obtained showed a slight change in the global conformational stability of Trx modified with HNE and MDA, establishing that all modified proteins presented local regions of high mobility in the modified catalytic site and some regions far from the modification area. In addition, essential domain movement modes evidences that proteins modified with the RCS assayed induce changes in conformational flexibility. Finally, these data showed that the given conformational changes did not caused global changes in proteins but rather localized changes in particular regions.

The molecular clock is vital for regulating circadian rhythms in various physiological processes, and its dysregulation is associated with multiple diseases. As such, the use of small molecule modulators to regulate the molecular clock presents a promising therapeutic approach. In this study, we generated a homology model of the human circadian locomotor output cycles kaput (CLOCK) protein to evaluate its ligand binding sites. Using molecular docking, we obtained further insights into the binding mode of the control compound CLK8 and explored a selection of dietary compounds. Our investigation of dietary compounds was guided by their potential interactions with the retinoic acid-related orphan receptors RORα/γ, which are involved in circadian regulation. Through the molecular similarity and docking analyses, we identified oleanolic acid demethyl, 3-epi-lupeol, and taraxasterol as potential ROR-interacting compounds. These compounds may exert therapeutic effects through their modulation of RORα/γ activity and subsequently influence the molecular clock. Overall, our study highlights the potential of small molecule modulators in regulating the molecular clock and the importance of exploring dietary compounds as a source of such modulators. Our findings also provide insights into the binding mechanisms of CLK8 and shed light on potential compounds that can interact with RORs to regulate the molecular clock. Future investigations could focus on validating the efficacy of these compounds in modulating the molecular clock and their potential use as therapeutic agents.

Understanding the effective factors in the performance of some Oligo (p-phenylenes) (OPPs) and Polycyclic Aromatic Hydrocarbons (PAHs), as efficient organocatalysts in photocatalytic CO2 transformations are the main goals of this investigation. The studies are based on density functional theory (DFT) calculations on the mechanistic aspects of C-C bond formation through a coupling reaction between CO2•- and amine radical. The reaction is performed through two successive single electron transfer steps. After careful kinetic investigations by Marcus' theory rules, powerful descriptors are used to describe the behavior of observed barrier energies of electron transfer steps. The studied PAHs and OPPs consist of different numbers of rings. Thus, it can be considered different charge densities, afforded from π electrons, of PAHs and OPPs that cause distinguished efficiency in kinetic aspects of electron transfer steps. Electrostatic Surface Potential (ESP) analyses reveal a good relationship between the charge density of the studied organocatalysts in single electron transfer (SET) steps and the kinetic parameters of the steps. Moreover, the contribution of rings in the framework of PAHs and OPPs would be another effective factor in the barrier energies of SET steps. Aromatic properties of the rings, studied by the Anisotropy of the Current-Induced Density (ACID), Nucleus-Independent Chemical Shift (NICS), the multi-center bond order (MCBO), and AV1245 Indexes, are the other impressive factors in the role of rings in SET steps. The results show that the aromatic properties of the rings are not similar to each other. Higher aromaticity affords remarkable reluctance of the corresponding ring to participate in SET steps.

Noradrenaline (NA), one of the important excitatory catecholamine neurotransmitters, is used as a medication for Parkinson's Disease (PD). The β-cyclodextrin (β-CD) is one of the most effective drug carrier & also used in chiral separation. So, in this theoretical investigation, the R/S-Noradrenaline (R/S-NA) forms binding & chiral recognition mechanisms and energies with β-CD were explored. Using the AutoDock, R/S forms were first docked into the cavity of β-CD giving host-guest complexes with the free energy of binding for S-NA (-4.81 kcal/mol) larger than R-NA (-4.53 kcal/mol). The host-guest inclusion 1:1 complexes between R/S-NA and β-CD have been also modeled and optimized with ONIOM2 (B3LYP/6-31g++DP: PM6) method by using the Gaussian software. Further, frequency calculations were carried out to obtain the free energies. In comparison to the R-NA (-54.59 kcal/mol), it was observed that the S-NA (-56.48 kcal/mol) with β-CD is more stable. Furthermore, the H-bond results from molecular dynamics simulation revealed that S-NA/β-CD was more stable than R-NA/β-CD. In addition, the thermodynamic properties, vibrational analysis (IR), HOMO-LUMO band gap energy, inter molecular hydrogen bond interactions, and conformational analysis were investigated for both the R/S forms to support & compare the stability of the inclusion complex. These inclusion & high stability of S-NA/β-CD and in turn its theoretical chiral recognition behavior observed agreeing well with the reported NMR experimental data have implications in drug delivery and chiral separation research.

The peculiar properties of 2-D nano-materials have always inspired the research community for the further discovery of novel materials. Although III-V nitrides have been extensively explored for various remarkable phenomena, phosphides of the same group are yet to be explored. Taking a step in this direction, here we report the structural and electronic properties of zigzag BP nanoribbons (ZBPNR) with coved edge defects. The effect of sp2 and sp3 edge passivation has also been compared to reveal interesting findings. The position of coved defect is considered in a number of different possibilities. It is observed that all the structures are energetically stable and maintain planar geometries. The H-passivated ribbons exhibit a semiconductor behavior with their band gap reciprocal to the ribbon width. However, for coved edge nanoribbons, a semiconductor as well as pure metallic nature has been predicted depending upon the site of the coved defect. Furthermore, the nature of the band gap is direct in H-passivated nanoribbons whereas for coved edges a direct to indirect alternation has been observed. The obtained wide range of electronic band gap (0.15 eV to 1.34 eV) indicates that ZBPNR could be useful for designing beyond silicon semiconductor devices.

The condensation process of water with different nuclei under electromagnetic wave irradiation was studied by molecular dynamics simulation. It was found that there is a different electric-field effect when the condensation nucleus was a small (NH4)2SO4 cluster than a CaCO3 nucleus. Through the analysis of the hydrogen-bond number, energy change, and dynamic behavior, we found that the effect of external electric field on the condensation process mainly comes from the change of potential energy caused by the dielectric response and there is a competition effect between the dielectric response and the dissolution in the system with (NH4)2SO4.

The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has raised concerns worldwide due to its enhanced transmissibility and immune escapability. The first dominant Omicron BA.1 subvariant harbors more than 30 mutations in the spike protein from the prototype virus, of which 15 mutations are located at the receptor binding domain (RBD). These mutations in the RBD region attracted significant attention, which potentially enhance the binding of the receptor human angiotensin-converting enzyme 2 (hACE2) and decrease the potency of neutralizing antibodies/nanobodies. This study applied the molecular dynamics simulations combined with the molecular mechanics-generalized Born surface area (MMGBSA) method, to investigate the molecular mechanism behind the impact of the mutations acquired by Omicron on the binding affinity between RBD and hACE2. Our results indicate that five key mutations, i.e., N440K, T478K, E484A, Q493R, and G496S, contributed significantly to the enhancement of the binding affinity by increasing the electrostatic interactions of the RBD-hACE2 complex. Moreover, fourteen neutralizing antibodies/nanobodies complexed with RBD were used to explore the effects of the mutations in Omicron RBD on their binding affinities. The calculation results indicate that the key mutations E484A and Y505H reduce the binding affinities to RBD for most of the studied neutralizing antibodies/nanobodies, mainly attributed to the elimination of the original favorable gas-phase electrostatic and hydrophobic interactions between them, respectively. Our results provide valuable information for developing effective vaccines and antibody/nanobody drugs.

In this study, theoretically designed D-π-A derivatives containing different π-subunits as linkers were investigated to enlighten their potential applicability in photovoltaic applications. For this aim, we first focused on clarifying the effect of tailored π-linker scaffolds on the frontier orbital energies of the investigated photosensitizers. In the concomitant step, global descriptors, TiO2 adsorption, maximum absorbance wavelength, light-harvesting efficiency (LHE), energy conversion efficiency (η), short circuit current density (JSC), open circuit photovoltage (VOC), fill factor (FF), and reorganization energy (λe, λh, λT) values, electron density differentiation maps (EDDM), transition density matrices (TDM), fragmental contributions on electron-hole overlap were investigated in detail. Based on the trend of the calculated properties, 2,3-dimethylthieno [3,4-b]pyrazine (D-Ɛ3-δn-A; n = 1-3) and 5-isobutyl-10,11-dimethyl-10,11-dihydro-5H-pyrrolo [3,4-e]thieno [2',3':4,5]pyrrolo [3,2-g]thieno [3,2-b]indole (D-Ɛ6-δn-A; n = 1-3) bearing molecules were identified as the best-suited and improved dye candidates for DSSC applications. Following the prediction of photovoltaic properties for the pristine dye molecules, our consecutive efforts have contributed to a similar calculation protocol comprising DFT and subsequent TD-DFT computations for the D-Ɛn-δn-A@Ti5O10 clusters to elucidate the interaction of the investigated photosensitizers with the semiconductor layer (TiO2).

In this work, the adsorption of the O2 molecule on the transition metals (TM(II) = Sc2+, Ti2+, V2+, Cr2+, Mn2+, Fe2+, Co2+, Ni2+, Cu2+ and Zn2+) porphyrins induced carbon nanocone (TM(II)-PCNC) were investigated using density functional theory (DFT) in terms of stabilities, energetic, structural, and electronic properties. It has been found that the O2 molecule is adsorbed on the TM(II)-PCNC with adsorption energies in the range of 0.29 to -98.32 kcal/mol. The interaction between the O2 gas and the Sc-PCNC molecule from the outer site is the strongest. The interaction of the O2 gas over the Ni-PCNC molecule from both outer and inner sites is the weakest. It can be concluded that the suitable interaction energy (Eg) for sensing ability attributed to the Zn-PCNC because an effective and physical interaction between Zn-PCNC and the O2 gas leads to short recovery time. DFT calculations also clarified that the high %ΔEg of Zn-PCNC and hence the high sensitivity to the O2 gas confirm that the Zn-PCNC molecule is a promising candidate for having a good sensing ability to the O2 gas.

The methane activation reaction is of fundamental importance for its transformation into high-value chemicals. Despite the fact that both homolysis and heterolysis are competitive mechanisms of C-H scission, experimental and DFT studies have revealed heterolytic scission of the C-H bond over metal-exchange zeolites. To rationalize the new catalysts, work must be done on the homolytic versus heterolytic scission of the C-H bond mechanism on these catalysts. We have performed the quantum mechanical calculations for the C-H bond homolysis versus heterolysis over Au-MFI and Cu-MFI catalysts. Calculations results showed that homolysis of the C-H bond is favorable both thermodynamically as well as kinetically over Au-MFI catalysts. However, over Cu-MFI, heterolytic scission is favorable. Both Cu(I) and Au(I) activate the CH4 via electronic density back donation from filled nd10 orbitals, according to NBO calculations. Cu(I) cation has a higher electronic density back donation than Au(I) cation. This is also supported by the charge on the C-atom of Methane. Additionally, a greater negative charge on the O-atom in the active site in case of Cu(I), where proton transfer occurs, promotes heterolytic scission. Because of the larger size of the Au-atom and the smaller negative charge of the O-atom in the active site, where proton transfer occurs, C-H bond homolytic fission is preferable over Au-MFI.

In this work, various atomic charge schemes including natural bond orbital (NBO), electrostatic potential based (CHELPG), and σ-hole model charges were applied in the OPLS-AA force field to investigate their effects on the thermophysical and structural properties of iodobenzene and its derivatives. Molecular dynamics simulations presented in this work show that the studied structural and thermophysical properties are in good agreement with experiments when the CHELPG charge was coupled with the OPLS-AA force field. Also, the arrangement of iodobenzene derivatives in the liquid phase was investigated via combined radial/angular distribution functions (CDFs) analyses and halogen-bonding theory. The most probable orientation of iodobenzene derivatives at the liquid/vacuum interface was assigned by atom density profile and bivariate orientational distribution maps. For all studied iodobenzene derivatives, benzene rings are oriented such that the iodine atoms tend toward the vacuum phase.

Ibuprofen is a commonly used drug for treating headaches, pain, and fever. The lipid bilayer is the primary and most important interface for drugs to interact with biological systems. However, the molecular interactions between ibuprofen and the cell membrane are not well understood. Our findings suggest that the interactions between ibuprofen and the bilayer involve multiple steps and depend on the concentration of the drug. At low concentrations of ibuprofen, it can bind to the surface of the lipid bilayer. The electrostatic and vdW energies of IBU-lipid at 0 ns of the simulation were -22.5 ± 3.2 and -5.9 ± 1.2 kj.mol-1 Fig. 2. In the following, the vdW energy of the IBU-lipid was increased by around -134.6 ± 3.7 kj.mol-1 whereas the electrostatic energy of the IBU-lipid was significantly decreased. This binding is facilitated by electrostatic and vdW interactions between ibuprofen and the head group of lipids. In the second step, ibuprofen is inserted into the lipid bilayer and positioned at the interface between the bilayer and the aqueous phase. In high concentrations of ibuprofen, it moved to the central region of the lipid bilayer. At this concentration, the physical and structural properties of the cell membrane change significantly. Results from the radial distribution function analysis indicate that at low concentrations, ibuprofen molecules are situated close to the head groups of phosphate groups. However, at high concentrations of ibuprofen, these molecules move to the inner side of the lipid bilayer. In addition, our findings indicate that at low concentrations of ibuprofen, these molecules did not significantly alter the physical properties of the cell membrane. In contrast, at high concentrations of ibuprofen, the physical parameters of the hydrocarbon tails, such as thickness, fluidity, and order, changed dramatically. APL parameter for POPC membrane increased slightly to 0.60 and 0.63 nm2 in the presence of low and high concentrations of ibuprofen molecules. The three-step interaction between ibuprofen and the lipid bilayer involves several events, such as the movement of ibuprofen molecules towards the central region of the lipid bilayer and the deformation and alteration of the structural and stability properties of the cell membrane. These effects are observed only at high concentrations of ibuprofen. It appears that the side effects of ibuprofen overdose are related to changes in the properties of the cell membrane and, subsequently, the function of membrane-anchored target proteins.

Norvaline is a straight-chain, hydrophobic, non-proteinogenic amino acid, isomeric with valine. Both amino acids can be misincorporated into proteins at isoleucine positions by isoleucyl-tRNA synthetase when the mechanisms of translation fidelity are impaired. Our previous study showed that the proteome-wide substitution of isoleucine with norvaline resulted in higher toxicity in comparison to the proteome-wide substitution of isoleucine with valine. Although mistranslated proteins/peptides are considered to have non-native structures responsible for their toxicity, the observed difference in protein stability between norvaline and valine misincorporation has not yet been fully understood. To examine the observed effect, we chose the model peptide with three isoleucines in the native structure, introduced selected amino acids at isoleucine positions and applied molecular dynamics simulations at different temperatures. The obtained results showed that norvaline has the highest destructive effect on the β-sheet structure and suggested that the higher toxicity of norvaline over valine is predominantly due to the misincorporation within the β-sheet secondary elements.

In this work, we studied the hydrogen adsorption capabilities of functionalized graphene sheets containing a variety of defects (D-G) via molecular dynamics (MD) simulations that govern the mechanisms involved in hydrogen adsorption. Specifically, the graphene sheets containing monovacancy (MV), Stone-Wales (SW), and multiple double vacancy (DV) defects were functionalized with Ti and N atoms to enhance their hydrogen adsorption capacity. We measured the adsorption capacities of the N-/D-G sheets with varying concentrations of Ti adatoms at 300 K and 77 K temperatures and various pressures. Our study revealed that the increasing concentration of Ti adatoms on the D-G sheets led to a significant improvement in the hydrogen adsorption capacity of the graphene sheets. The DV(III)-G sheets showed the maximum adsorption capacity at 300 K because the DV(III)-G sheets had a small number of large-sized pores that bind hydrogen with high binding energy. Thus, hydrogen remained adsorbed even at higher temperatures (300 K). The N doping on the D-G sheets initially reduced their hydrogen adsorption capabilities; however, the N-D-G sheets enhanced their hydrogen adsorption capacity with the increasing concentrations of Ti adatoms. Compared to all other defect types, the Ti-N-DV(III)-G sheet with a Ti concentration of 10.5% showed a hydrogen uptake of 5.5 wt% at 300 K and 100 bar pressure. Thus, the N doping and Ti implantations improved the hydrogen storage capabilities of the graphene sheets, and these findings helped design solid-state hydrogen storage systems operating at ambient conditions and moderate pressure ranges.

In the current study, the drug loading ability of graphyne (GY) for the amiodarone (AMD) drug is investigated for the first time. The efficacy of GY as a carrier for amiodarone (a cardiovascular drug) is evaluated by calculating its electronic, energetic, optimized, and excited state properties with help of the density functional theory (DFT). The AMD drug interacted with the GY molecule with an adsorption energy of about -0.19 eV (gas-phase) and -1.92 eV (aqueous phase), suggesting that the AMD@GY complex is stable in water-phase. The HOMO (highest-occupied molecular-orbital) of the AMD@GY complex is concentrated on the AMD drug while the LUMO (lowest-unoccupied molecular-orbital) is centralized on GY with absolute charge separation, indicating charge transfer will occur between AMD and GY. The charge-transfer process is further studied with the aid of charge-decomposition analysis (CDA). The non-covalent interaction analysis (NCI) exposed that non-covalent forces exist between the GY carrier and AMD drug. These non-covalent forces between AMD drug and GY carrier play a significant role in drug unloading at the targeted or diseased site. Likewise, the calculations at excited-state, charge-state (+1 and -1) influence on GY and AMD@GY complex structures, and photo-induced electron transfer analysis (PET) are also studied for the graphyne-based drug-delivery system. According to PET and electron-hole analysis, fluorescence-quenching will occur upon interaction. Overall, it is concluded that graphyne can be exploited as a drug carrier for amiodarone drug delivery. Researchers will be fascinated to look at alternative 2D nanomaterials for drug delivery applications as a result of this theoretical work.

The [4 + 2] cycloaddition reactions of 2-styrylchromones have been predominantly described as one of the efficient methods for the synthesis of xanthones-a prominent class of tricyclic molecules that occur widely in nature. These xanthones are well known for their pharmacological activities especially their role as anti-cancer agents in the medicinal world. In this study, the mechanistic insight into the unusual (peri- and stereo-) selectivities of the reaction of 2-(2-dimethylaminovinyl)-1-benzopyran-4-one (A1) with N-phenylmaleimide (NPM) and dimethylacetylenedicarboxylate (DMAD) has been studied using density functional theory (DFT) at the M06-2X/6-311G (d, p) level of theory. The reaction of A1 and NPM in dimethylformamide (DMF) is periselective towards the initial formation of a [4 + 2] cycloadduct and stereoselectively in an exo fashion with an activation energy of 6.8kcalmol-1 and a rate constant of 6.43×107s-1 which occurs about 878 million times faster than the closest competing pathway for the initial [2 + 2] cycloaddition fashion with an activation energy of 19.0kcalmol-1 and a rate constant of 7.32×10-2s-1. For the substituent effect on the reaction, the reaction selectivity is still maintained where the exo intermediate remains the most kinetically favored cycloadduct. However, the magnitude of the barriers increases slightly with a margin of about 0.1-4.8kcalmol for the electron-donating groups (EDGs) in the order; strong EDGs (OH < NH2 < OCH3) < weak EDGs (<Ph) and 5.3-6.4kcalmol for electron-withdrawing groups in the order; strong EWGs (CF3) < weak EWGs (Cl < Br). On the other hand, DMAD periselectively adds across the amino substituted olefinic bond of A1 via an initial [2 + 2] stepwise cycloaddition fashion followed by an intramolecular rearrangement to form the xanthone product. The rate constant of the rate-determining step in the pathway for the formation of the kinetically favored [4 + 2] cycloadduct with an activation barrier of 17.3kcalmol-1 is 1.29s-1 which occurs about 373,000 times slower than the most preferred pathway affording a [2 + 2] cycloadduct with an activation barrier of 9.7kcalmol-1 and a rate constant of 4.81×105s-1. Both reactions are normal electron-demand cycloaddition reactions and are kinetically controlled.

The properties of drugs may undergo changes when multiple drugs are co-administered to treat co-existing or complex diseases, potentially leading to unforeseen drug-drug interactions (DDIs). Therefore, predicting potential drug-drug interactions has been an important task in pharmaceutical research. However, the following challenges remain: (1) existing methods do not work very well in cold-start scenarios, and (2) the interpretability of existing methods is not satisfactory. To address these challenges, we proposed a multi-channel feature fusion method based on local substructure features of drugs and their complements (LSFC). The local substructure features are extracted from each drug, interacted with those of another drug, and then integrated with the global features of two drugs for DDI prediction. We evaluated LSFC on two real-world DDI datasets in worm-start and cold-start scenarios. Comprehensive experiments demonstrate that LSFC consistently improved DDI prediction performance compared with the start-of-the-art methods. Moreover, visual inspection results showed that LSFC can detect crucial substructures of drugs for DDIs, providing interpretable DDI prediction. The source codes and data are available at https://github.com/Zhang-Yang-ops/LSFC.

In this study, nine new electron rich compounds are presented, and their electronic, geometrical, and nonlinear optical (NLO) characteristics have been investigated by using the Density functional theory. The basic design principle of these compounds is placing alkaline earth metal (AEM) inside and alkali metal (AM) outside the hexaammine complexant. The properties of nine newly designed compounds are contrasted with the reference molecule (Hexaammine). The effect of this doping on Hexaamine complexant is explored by different analyses such as electron density distribution map (EDDM), frontier molecular orbitals (FMOs), density of states (DOS) absorption maximum (λmax), hyperpolarizabilities, dipole moment, transition density matrix (TDM). Non-covalent interaction (NCI) study assisted with isosurfaces has been accomplished to explore the vibrational frequencies and types of synergy. The doping of hexaammine complexant with AM and AEM significantly improved its characteristics by reducing values of HOMO-LUMO energy gaps from 10.7eV to 3.15eV compared to 10.7 eV of hexaammine. The polarizability and hyperpolarizability (αo and βo) values inquisitively increase from 72 to 919 au and 4.31 × 10-31 to 2.00 × 10-27esu respectively. The higher values of hyperpolarizability in comparison to hexaammine (taken as a reference molecule) are credited to the presence of additional electrons. The absorption profile of the newly designed molecules clearly illustrates that they are highly accompanied by higher λmax showing maximum absorbance in red and far-red regions ranging from 654.07 nm to 783.94 nm. These newly designed compounds have superior outcomes having effectiveness for using them as proficient NLO materials and have a gateway for advanced investigation of more stable and highly progressive NLO materials.

In this study, a series of eight non-fused rings-based semiconducting acceptors (AR1-AR8) were computationally developed by making modifications to the parent molecule (PTICO). In this study, a DFT analysis was conducted at an accurately chosen level of theory to gather a comprehensive inventory of the optoelectronic characteristics of AR1-AR8 and PTICO. The findings indicate that all recently developed molecules exhibit a bathochromic shift in their maximum UV-visible absorbance (λmax) with a smaller band gap (Eg). AR1 has demonstrated the most significant red shift in UV-visible absorbance and possesses the smallest Eg when compared to other recently developed acceptors. AR2 acceptor has shown the best results both as electron and hole-transporting materials owing to its smallest value of reorganization energy for electrons and holes. J61 donor was engaged to calculate the open-circuit voltage (VOC) and the highest VOC with maximum FF % value was observed in AR4. The investigation of charge transfer was also conducted utilizing J61 in conjunction with the AR4 acceptor. Natural transition orbitals (NTO) have also been inspected to recognize the percentage electron transport contribution (% ETC) from the ground state to the first excites state (S0 to S1). The findings of this research suggest that the modified acceptors exhibit potential for practical implementation in the development of organic solar cells that possess improved photovoltaic performance.

A series of new organic dyes (T1-T6) with nonfullerene acceptors have been theoretically designed around the chemical structure of tyrian purple (T) natural dye. For their ground state energy parameters, all the molecular geometries of those dyes were optimized by density functional theory (DFT) at its Becke, 3-parameter, Lee-Yang-Parr (B3LYP) level of theory with 6-31G+(d,p) basis sets. When benchmarking against several long range and range separated levels of theory, the Coulomb attenuated B3LYP (CAM-B3LYP) produced most accurate absorption maxima (λmax) value to that of T so it was further employed for further Time dependent DFT (TD-DFT) calculations. Frontier molecular orbitals (FMOs) with natural bond orbital (NBO) studies were used to study their intra molecular charge transfer (ICT). All of the dyes had their energy gaps (Eg) values between their FMOs to range around 0.96-3.39 eV, whereas the starting reference dye had an Eg of 1.30 eV. Their ionization potential (IP) values were ranged to be 3.07-7.25 eV which indicated their nature to loss electrons. The λ max in chloroform was marginally red-shifted with a value 600-625 from T (580 nm). The dye T6 showed its highest linear polarizability (<α>), and first and second order hyperpolarizabilities (β and γ). The synthetic experts can find the present research to design finest NLO materials for current and future uses.

The competence of organic solar cells (OSCs) could be enhanced by improving the light absorption capabilities as well as the open-circuit voltage (Voc) of utilized molecules. To upgrade overall functionality of OSCs, seven new molecules were designed in this work using an end-cap alteration technique on Quinoxaline fused core-based non-fullerene acceptor (Qx-2) molecule. This technique is known to be quite advantageous in terms of improvement of the effectiveness and optoelectrical behavior of various OSCs. Critical parameters like the absorption maximum, frontier molecular orbitals, excitation energy, exciton binding energy, Voc, and fill factor of molecules were considered for the molecules thus designed. All newly designed molecules showed outstanding improvement in optoelectronic as well as performance-related properties. Out of all scrutinized molecules, Q1 exhibited highest wavelength of absorption peak (λmax = 779 nm) with the reduced band gap (1.90 eV), least excitation energy (Ex = 1.59 eV), along with the highest dipole moment (17.982950 D). Additionally, the newly designed compounds Q4, Q5, and Q6 exhibited significantly improved Vocs that were 1.55, 1.47, and 1.50 eV accordingly, as compared to the 1.37 eV of Qx-2 molecule. These molecules also showed remarkable improvement in fill factor attributed to direct correspondence of Voc with it. Inclusively, these results support the superiority of these newly developed molecules as prospective constituents of upgraded OSCs.

Cancer is one of the leading causes of mortality in the world. Despite the existence of diverse antineoplastic treatments, these do not possess the expected efficacy in many cases. Knowledge of the molecular mechanisms involved in tumor processes allows the identification of a greater number of therapeutic targets employed in the study of new anticancer drugs. In the last decades, peptide-based therapy design using computational chemistry has gained importance in the field of oncology therapeutics. This work aims to evaluate the electronic structure, physicochemical properties, stability, and inhibition of ETFS amino acids and peptides derived from the p53-MDM2 binding domain with action in cancer cells; by means of chemical descriptors at the DFT-BHandHLYP level in an aqueous solution, and its intermolecular interactions through molecular docking studies. The results show that The ETFS fragment plays a critical role in the intermolecular interactions. Thus, the amino acids E17, T18 and S20 increase intermolecular interactions through hydrogen bonds and enhance structural stability. F19, W23 and V25 enhance the formation of the alpha-helix. The hydrogen bonds formed by the backbone atoms for PNC-27, PNC-27-B and PNC-28 stabilize the α-helices more than hydrogen bonds formed by the side chains atoms. Also, molecular docking indicated that the PNC27B-MDM2, PNC28B-MDM2, PNC27-MDM2 and PNC28A-MDM2 complexes show the best binding energy. Therefore, DFT and molecular docking studies showed that the proposed peptides: PNC-28B, PNC-27B and PNC-28A could inhibit the binding of MDM2 to the p53 protein, decreasing the translocation and degradation of p53 native protein.

The present study investigates the competition between hydrogen, halogen, and tetrel bonds from the interaction of COCl2 with HOX using quantum chemistry simulations at the MP2/aug-cc-pVTZ computational level, in which five configurations were optimized, including adducts I -V. Two hydrogen bonds, two halogen bonds, and two tetrel bonds were obtained for five forms of adducts. The compounds were investigated using spectroscopic, geometry, and energy properties. Adduct I complexes are more stable than others, and adduct V halogen bonded complexes are more stable than adduct II complexes. These results are in agreement with their NBO and AIM results. The stabilization energy of the XB complexes depends on the nature of both the Lewis acid and base. The stretching frequency of the O-H bond in adducts I, II, III, and IV displayed a redshift, and a blue shift was observed in adduct V. The results for the O-X bond showed a blue shift in adducts I and III and a red shift in adducts II, IV, and V. The nature and characteristics of three types of interactions are investigated via NBO analysis and atoms in molecules (AIM).

In this research work, we employed a tricycle graphane nanosheet as a chemical sensor to monitor the toxic hydrocarbon molecules, namely propylene, and 1,3-butadiene, which are emitted from automobile industries. At first, the structural stability and dynamical permanency of tricycle graphane is ascertained based on cohesive energy and phonon-band-spectrum. Sequentially, the electronic properties of tricycle graphane are conferred with the results of the projected density of states spectrum and band structure. The computed band gap of tricycle graphane is 5.53 eV. Chiefly, the adsorption behaviour of target propylene and 1, 3-butadiene on tricycle graphane is explored by determining adsorption energy, relative band gap variation, and Mulliken population analysis. Furthermore, the range of adsorption energy magnitudes (-0.16 eV to -1.03 eV) demonstrates that the target hydrocarbon molecules are physically adsorbed on tricycle graphane material. The overall outcome endorses that the tricycle graphane can be utilised as a prominent sensor to sense the hydrocarbon molecules released from automobiles and monitor air pollutants.

This study aimed to explore the potential of Host-Guest coupling with Nanocarrier graphyne (GPH) to enhance the bioavailability of the drug 1-(2-chloroethyl)-3-cyclohexyl-1-nitrosourea (LUM) for brain tumor therapy. The electronic, geometric, and excited-state properties of GPH, LUM, and the graphyne@1-(2-chloroethyl)-3-cyclohexyl-1-nitrosourea-complex (GPH@LUM-complex) were studied using DFT B3LYP/6-31G** level of theory. The results showed that the GPH@LUM-complex was stable with negative adsorption energy (-0.20 eV), and there was good interaction between GPH and LUM in the solvent phase. The weak interaction forces between the two indicated an easy release of the drug at the target site. The Frontier Molecular Orbitals (FMO), Charge Density Analysis (CDA), and Natural Bond Orbital (NBO) analysis supported LUM to GPH charge transfer during complex formation, and the Reduced Density Gradient (RDG) isosurfaces identified steric effects and non-bonded interactions. UV-visible examination showed the potential of the GPH@LUM-complex as a drug carrier with a blue shift of 23 nm wavelength in the electronic spectra. The PET process analysis revealed a fluorescence-quenching process, facilitating systematic drug delivery. The study concluded that GPH had potential as a carrier for delivering LUM, and different 2D nanomaterials could be explored for drug delivery applications. The theoretical study's findings may motivate researchers to investigate the practical applications of GPH@LUM-complex in oncology.

1,4-Diazepine as an active drug component underlies the potency of most psychotic, anticancer, anticonvulsant, and antibacterial drugs in the market and is, therefore crucial in chemotherapeutic treatment in biomedicine. Proper functionalization of this moiety can afford even more potent drugs. As a result of their therapeutic significance, this study aims at precisely giving a comprehensive computational insight into the unexpected initial reactivity of 1,4-diazepine derivatives and mesitonitrile oxide. The initial reaction between mesitonitrile oxide and 1,4-diazepine derivatives proceeds via a (3 + 2) cycloaddition reaction which leads to the formation of a cycloadduct where the mesitonitrile oxide unexpectedly adds across the imine functionality at the expense of the potential olefinic carbon-carbon double bond. Calculations at the density functional theory (DFT) M06/6-311G (d, p) level of theory indicate that the initial (3 + 2) cycloaddition reaction of mesitonitrile oxide (1,3-dipole) and 1,4-diazepine derivatives (dipolarophile) in all cases proceeds to form the cycloadduct where the 1,3-dipole adds preferentially to the imine functionality at the expense of the potential olefinic carbon-carbon double bond. In light of the parent reaction, the most kinetically favored cycloadductP3A had a rate constant of 5.1 × 106 M-1s-1, which is about 12 manifolds faster than the next competing stereoisomer P1A with a rate constant of 4.1 × 105 M-1s-1 and about 1024 faster than the most favored cycloadduct P3B with a rate constant of 7.2 × 10-19 M-1s-1 in the unfavored pathway (Path B). Irrespective of the electronic and steric nature of the electron-donating (EDG) and electron-withdrawing (EWG) substituents placed on the dipolarophile, the selectivities of the reaction were maintained. Rationalization of the potential energy surface depicts that the 1,3-dipole adds across the dipolarophile via an asynchronous concerted mechanism. Rationalization of the HOMO-LUMO energies of the mesitonitrile oxide (1,3-dipole) and the 1,4-diazepine derivatives (dipolarophile) depict that the EDG-substituted dipolarophile react as nucleophiles, whereas the dipole reacts as an electrophile. Conversely, the HOMO-LUMO interaction between the EWG-substituted dipolarophile indicates that the EWG-substituted dipolarophile react as electrophiles, whereas the dipole reacts as a nucleophile. The electrophilic parr function at various reactive sites of the dipolarophile shows that the 1,3-dipole preferentially adds across the local centers with the largest electrophilic NBO or Mulliken spin densities which is consistent with the energetic trend observed. The reactivity of the 1,4-diazepine derivatives and the mesitonitrile oxide showed poor stereoselectivity.

Polygalacturonase (PG) is an important hydrolytic enzyme involved in pectin disassembly and the subsequent textural changes during fruit ripening. Although the interaction of fungal PGs with other proteins has been documented, the interaction of plant PGs with other plant proteins has not yet been studied. In this study, the molecular mechanisms involved in raspberry fruit ripening, particularly the polygalacturonase (RiPG) interaction with polygalacturonase inhibiting protein (RiPGIP) and substrate, were investigated with a structural approach. The 3D model of RiPG2 and RiPGIP3 was built using a comparative modeling strategy and validated using molecular dynamics (MD) simulations. The RiPG2 model structure comprises 11 complete coils of right-handed parallel β-helix architecture, with an average of 27 amino acid residues per turn. The structural model of the RiPGIP3 displays a typical structure of LRR protein, with the right-handed superhelical fold with an extended parallel β-sheet. The conformational interaction between the RiPG2 protein and RiPGIP3 showed that RiPGIP3 could bind to the enzyme and thereby leave the active site cleft accessible to the substrate. All this evidence indicates that RiPG2 enzyme could interact with RiPGIP3 protein. It can be a helpful model for evaluating protein-protein interaction as a potential regulator mechanism of hydrolase activity during pectin disassembly in fruit ripening.

Despite the substantial advancements in organic solar cells (OSCs), the best devices still have quite low efficiencies due to less focus on donor molecules. With the intention to present efficient donor materials, seven small donor molecules (T1-T7) were devised from DRTB-T molecule by using end-capped modeling. Newly designed molecules exhibited remarkable improved optoelectronic properties such as less band gap (from 2.00 to 2.23 eV) than DRTB-T having band gap of 2.57 eV. Similarly, a significant improvement in λmax values was noticed in designed molecules in gaseous medium (666 nm-738 nm) and solvent medium (691 nm-776 nm) than DRTB-T having λmax values at 568 nm and 588 nm in gas and solvent phase respectively. Among all molecules, T1 and T3 exhibited significant improvement in optoelectronic properties such as narrow band gap, lower excitation energy, higher λmax values and lower electron reorganization energy as compared to pre-existed DRTB-T molecule. The better functional ability of T1-T7 is also suggested by an improvement in open circuit voltage (Voc) of designed structures (1.62 eV-1.77 eV) as compared to R (1.49 eV) when PC61BM is used as an acceptor. So, all our newly derived donors can be employed in the active layer of organic solar cells to manufacture efficient OSCs.

Alzheimer's disease (AD) is a multifactorial neurodegenerative disease mainly characterized by extracellular accumulation of amyloid-β (Aβ) peptide. Previous studies reported pentapeptide RIIGL as an effective inhibitor of Aβ aggregation and neurotoxicity induced by Aβ aggregates. In this work, a library of 912 pentapeptides based on RIIGL has been designed and assessed for their efficacy to inhibit Aβ42 aggregation using computational techniques. The top hit pentapeptides revealed by molecular docking were further assessed for their binding affinity with Aβ42 monomer using MM-PBSA (molecular mechanics Poisson-Boltzmann surface area) method. The MM-PBSA analysis identified RLAPV, RVVPI, and RIAPA, which bind to Aβ42 monomer with a higher binding affinity -55.80, -46.32, and -44.26 kcal/mol, respectively, as compared to RIIGL (ΔGbinding = -41.29 kcal/mol). The residue-wise binding free energy predicted hydrophobic contacts between Aβ42 monomer and pentapeptides. The secondary structure analysis of the conformational ensembles generated by molecular dynamics (MD) depicted remarkably enhanced sampling of helical and no β-sheet conformations in Aβ42 monomer on the incorporation of RVVPI and RIAPA. Notably, RVVPI and RIAPA destabilized the D23-K28 salt bridge in Aβ42 monomer, which plays a crucial role in Aβ42 oligomer stability and fibril formation. The MD simulations highlighted that the incorporation of proline and arginine in pentapeptides contributed to their strong binding with Aβ42 monomer. Furthermore, RVVPI and RIAPA prevented conformational conversion of Aβ42 monomer to aggregation-prone structures, which, in turn, resulted in a lower aggregation tendency of Aβ42 monomer.

Density functional theory calculations were employed to identify the ability of some diphenylamine-based hole-transporting materials (HTMs) for use in top-performance perovskite solar cells. The effects of donor/acceptor electron groups and the new π-bridge section in the three-part of structures were investigated thoroughly. The results indicated that adding electron-withdrawing functional groups such as CN in the phenylazo-indol moiety and substituting electron donor groups such as CH3 in the NH2 hydrogen atoms of the diphenylamine section can cause higher power conversion light-harvesting efficiency in new HTMs. Also, the replacement of thieno [3,2-b] benzothiophene as a part of the π bridge with the phenyl group according to the optical and electronic structure properties improves the efficiency of the new phenylazoindole derivatives.

Herein, we investigate different oxides layers: Zinc Oxide (ZnO), Nickel Oxide (NiO), Titanium Oxide (TiO2), and Copper Oxide (CuO), which are effective materials for Copper Zinc Tin Sulfide (CZTS) based solar cells due to their excellent electrical and optical properties. The different oxide films were prepared using spray pyrolysis as a low-cost technique. Then, the films were characterized by X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), and UV-Visible to examine different properties. The XRD pattern showed that the different oxides are polycrystalline. ZnO exhibits a hexagonal wurtzite structure, and NiO is cubic. For the TiO2, (101) and (004) peaks have been identified, corresponding to the tetragonal anatase phase. CuO showed diffraction peaks corresponding to the monoclinic structures. The SEM results revealed that the deposited films consist of crystals with low crystallinity for NiO and good crystallinity for the rest oxides. The band gap was calculated from the UV-visible measurement. We obtained 3.26 eV, 3.34 eV, 3.2 eV, and 1.7 eV for ZnO, NiO, TiO2, and CuO respectively. The performance of the CZTS-based solar cell was checked by using the simulator SCAPS. ZnO and TiO2 were used as window layers where CZTS efficiencies are 24.40% and 24.54%, respectively. These findings show that ZnO and TiO2 films can be produced by low-cost techniques such as spray pyrolysis to be used as windows and electron transport layers for CZTS-based solar cells.

Kaposi sarcoma (KS) is one of the most common AIDS-related malignant neoplasms, which can leave lesions on the skin among HIV patients. These lesions can be treated with 9-cis-retinoic acid (9-cis-RA), an endogenous ligand of retinoic acid receptors that has been FDA-approved for treatment of KS. However, topical application of 9-cis-RA can induce several unpleasant side effects, like headache, hyperlipidemia, and nausea. Hence, alternative therapeutics with less side effects are desirable. There are case reports associating over-the-counter antihistamine usage with regression of KS. Antihistamines competitively bind to H1 receptor and block the action of histamine, best known for being released in response to allergens. Furthermore, there are already dozens of antihistamines that are FDA-approved with less side effects than 9-cis-RA. This led our team to conduct a series of in-silico assays to determine whether antihistamines can activate retinoic acid receptors. First, we utilized high-throughput virtual screening and molecular dynamics simulations to model high-affinity interactions between antihistamines and retinoic acid receptor beta (RARβ). We then performed systems genetics analysis to identify a genetic association between H1 receptor itself and molecular pathways involved in KS. Together, these findings advocate for exploration of antihistamines against KS, starting with our two promising hit compounds, bepotastine and hydroxyzine, for experimental validation study in the future.

In this study, we have investigated the stability and electronic properties of the CunRu (n = 2-10) nanoclusters and their interaction with the CH3OH molecule without and with the presence of O2 molecule by using DFT calculations with TPSS/SDD/6-311g(d,p) level of theory. Based on the second energy difference (Δ2E), the results reveal that the CunRu (n = 4, 6 and 8) clusters are relatively more stable than their neighboring clusters. The values obtained for the Fukui function (f-) proves that the Ru atom in the CunRu clusters is an excellent adsorption site for the molecules. The interaction of the CunRu clusters with CH3OH molecule exhibits that the Ru atom is the preferred adsorption site for the CH3OH molecule, where the O atom of the CH3OH molecule is strongly chemisorbed onto the Ru site of the clusters, forming a strong bond between the Ru and O atoms. The copper sites of the clusters were found less preferred for the adsorption of CH3OH, and the complexes formed between both species are less stable than those obtained from the CH3OH chemisorption over the Ru site of the clusters. The interaction of CH3OH with the clusters was also evaluated in an oxidizing environment, and the results obtained reveal that the molecule is greatly chemisorbed over the ruthenium site with adsorption energies which vary from - 1.18 to - 2.05 eV. In the presence of the oxygen, the gap energy of the clusters was sharply changed after their interactions with the CH3OH molecule, suggesting that these clusters can easily detect the above molecule with great sensitivity. Therefore, the presence of the oxygen not only does not prevent the adsorption process, but it considerably promotes the CH3OH chemisorption onto the ruthenium site of the clusters and therefore significantly rises their sensitivity performance. In conclusion, the CunRu clusters could be employed as effective nanosensors for the CH3OH molecule detection.

Cytochrome P4501B1 (CYP1B1) is reported to be overexpressed in various malignancies including ovarian, lung, lymph, and breast cancers. The overexpression of this enzyme is accountable for the biotransformation-based inactivation of some anti-cancer drugs i.e. Docetaxel, Paclitaxel, and Cisplatin. To circumvent solutions to this issue, the current study reports some optimized derivatives of benzochalcone as selective CYP1B1 inhibitors. The optimized derivatives were screened using some structure-based drug-designing approaches including molecular docking and molecular dynamics. The implemented approaches revealed that all the designed molecules demonstrated not only essential interactions with key amino acid residues but also maintained stability within the active site of CYP1B1. Furthermore, to validate the in-silico results and develop a SAR, the designed molecules were subsequently synthesized and tested for their ability to selectively inhibit CYP1B1 over CYP1A1 using well established EROD assay. This assay results suggested that compounds 1(c), 1(d), and 1(e) are eightfold more selective CYP1B1 inhibitors over CYP1A1 with IC50 values ranging from 0.06 to 0.09 μM respectively. Among these, compound 1(d) manifested potent inhibitory activity i.e. IC50 of 0.06 μM with 24 folds selectivity over 1A1. To have a better insight into the binding pattern of 1(d) within CYP1B1 and precisely compute binding affinity for 1(d)-CYP1B1 complex, one of the advanced QM/MM approaches i.e. ONIOM has been implemented. Where 1(d)-CYP1B1 complex conferred comparable binding affinity in terms of ΔG (kcal/mol) with that of ANF-CYP1B1 complex. This research could provide a suitable starting point for the development of more potent multi-functional compounds with CYP1B1 inhibitory activity.

Metalloproteinase-9 (MMP-9) is a key protein in cancer advancement and metastasis owing to its ability to degrade some extracellular matrix components. Mangiferin, a natural polyphenolic compound, has demonstrated through experimental and theoretical studies to be a great anticancer agent for the selective inhibition of MMP-9. This work aimed to evaluate the utility of several fluorinated compounds obtained from MF as possible Positron Emission Tomography (PET) radiopharmaceuticals oriented to MMP-9. Density Functional Theory calculations of MF were made to obtain the most active sites toward electrophilic and nucleophilic reactions and propose a synthetic route to produce its fluorinated derivatives. The reactivity study allowed us to propose a late-stage synthetic route based on click chemistry to obtain three fluorinated MF-based derivatives. Molecular docking calculations suggested that the derivative F-propyl-MF could be suitable as PET radiopharmaceutical owing to the establishment of a five-coordinated complex with the catalytic Zn atom belonging to the active site of MMP-9, crucial factor in the inhibition of MMP-9.

An increase in the occurrence of fungal infections throughout the world, as well as the rise of novel fungal strains and antifungal resistance to commercially available drugs, suggests that new therapeutic choices for fungal infections are needed. The purpose of this research was to find new antifungal candidates or leads of secondary metabolites derived from natural sources that could effectively inhibit the enzymatic activity of Candida albicans lanosterol 14-alpha demethylase (CYP51) while also having good pharmacokinetics. In silico prediction of the drug-likeness, chemo-informatics and enzyme inhibition indicate that the 46 compounds derived from fungi, sponges, plants, bacteria and algae sources have a high novelty to meet all five requirements of Lipinski's rules and impede enzymatic function. Among the 15 candidate molecules with strong binding affinity to CYP51 investigated by molecular docking simulation, didymellamide A-E compounds demonstrated the strongest binding energy against the target protein at -11.14, -11.46, -11.98, -11.98, and -11.50 kcal/mol, respectively. Didymellamide molecules bind to comparable active pocket sites of antifungal ketoconazole and itraconazole medicines by hydrogen bonds forming to Tyr132, Ser378, Met508, His377 and Ser507, and hydrophobic interactions with HEM601 molecule. The stability of the CYP51-ligand complexes was further investigated using molecular dynamics simulations that took into account different geometric features and computed binding free energy. Using the pkCSM ADMET descriptors tool, several pharmacokinetic characteristics and the toxicity of candidate compounds were assessed. The findings of this study revealed that didymellamides could be a promising inhibitor against these CYP51 protein. However, there is still a need for further in vivo and in vitro studies to support these findings.

This study focused on modeling and density functional theory (DFT) analysis of reference (AI1) and designed structures (AI11-AI15), based on the thieno-imidazole core, in order to create profitable candidates for solar cells. All the optoelectronic properties of the molecular geometries were computed using DFT and time dependent-DFT approaches. The influence of terminal acceptors on the bandgaps, absorption, hole and electron mobilities, charge transfer capabilities, fill factor, dipole moment, etc. Of the recently designed structures (AI11-AI15), as well as reference (AI1), were evaluated. Optoelectronics and chemical parameters of newly architecture geometries were shown to be superior to the cited molecule. The FMOs and DOS graphs also demonstrated that the linked acceptors remarkably improved the dispersion of charge density in the geometries under study, particularly in AI11 and AI14. Calculated values of binding energy and chemical potential confirmed the thermal stability of the molecules. All the derived geometries surpassed the AI1 (Reference) molecule in terms of maximum absorbance ranging from 492 to 532 nm (in chlorobenzene solvent) and a narrower bandgap ranging from 1.76 to 1.99eV. AI15 had the lowest exciton dissociation energy of 0.22eV as well as lowest electrons and hole dissociation energies, while AI11 and AI14 showed highest VOC, fill factor, power conversion efficiency (PCE), IP and EA (owing to presence of strong electron pulling cyano (CN) moieties at their acceptor portions and extended conjugation) than all the examined molecules, implying that they could be used to build elite solar cells with enhanced photovoltaic attributes.

mercury emission control from flue gas is a crucial issue for environment protection. Alumina is an important alkali metal oxide for mercury adsorption in particulate, meanwhile is the potential adsorbent for mercury removal. The cognition on mercury heterogeneous reaction mechanism with alumina in presence of hydrogen chloride is inadequate. In this work, the DFT calculation was applied to detect mercury's chlorides adsorption on α-Al2O3 (001) surface, the Bader charge analysis was used to estimate electron transfer and the transition state theory was used to clarify reaction pathway and energy barrier, besides, the kinetic analysis based on Gibbs free energy was conducted to study the impact of temperature on chemical reaction. The results show that Hg can be captured by weak chemisorption on α-Al2O3 (001) surface with the adsorption energy of -56.37 kJ/mol, HgCl, HgCl2 are intensively bonded on surface with adsorption energies of -276.90 kJ/mol and -231.87 kJ/mol, the surface unsaturated Al and O atoms are the active sites. Charge transfer and PDOS analysis prove that the forming of covalent bonding is responsible for Hg species adsorption. Two possible reaction pathways of Hg oxidization to HgCl2 are discussed, in which a smaller energy barrier of 0.1 eV implies the dominant pathway 1 via Eley-Rideal mechanism: two adsorbed HCl molecules dissociate on surface and then react with one Hg atom. High temperature can promote the reaction rate constants of pathway 1 and 2, but is only favorable for reducing energy barrier of pathway 2.

In this paper, the Kubo-Greenwood formula based on the tight-binding model is used to investigate the effects of the bias voltage and magnetic field on the electrical conductivity and heat capacity of the trilayer BP and BN with energy-stable stacking structures. The results show that electronic and thermal properties of the selected structures can be significantly modified by external fields. The position and intensity of DOS peaks and the band gap of selected structures are affected by the external fields. When external fields increases above critical value, the band gap decreases to zero and semiconductor-metallic transition occurs. The results show that the thermal properties of the BP and BN structures are zero in TZ temperature region and increase by temperature above TZ. The increasing rate for thermal properties depends on the stacking configuration and changes with the bias voltage and magnetic field. In the presence of the stronger field, the TZ region decreases below 100 K. Compared to the BP structures, the BN types with larger band gap has smaller electrical conductivity which can be increased in order to 3L-BP by applying the stronger magnetic field or bias voltage. These results are interesting for the future development of nanoelectronic devices.

Seven new molecules (S1-S7) of D-π-D type have been designed for organic photovoltaic applications. The DFT and TD-DFT methods were used to investigate the effect of different central bridge groups on the geometric, optoelectronic, and charge transport properties of the constructed molecules. Among them, S4 and S6 have the lowest energy band gap and a red shift in the absorption spectra, revealing the perfect relationship between the central bridge and the strong electron withdrawal character through extended conjugation. Similarly, S6 explored the lowest reorganization energy (RE) value for electron and hole revealing its enhanced charge transition, also shows better ICT characteristics with its highest NLO properties. Compound S4 showed the smallest value of ΔEL-L and Eb, and the highest Voc due to its low HOMO, which improves the photocurrent density of the devices. Thus, the results suggest that bridge modification is a practical strategy to improve the efficiency of OSCs.

A photosensitizer plays a vital role in adjusting the optical and electrochemical properties that affect the performance of dye-sensitized solar cells (DSSCs). Therefore, it should meet critical requirements for efficient operation of DSSCs. This study proposes catechin, a natural compound, as a photosensitizer and modifies its properties through hybridization with graphene quantum dots (GQDs). Density functional theory (DFT) and time-dependent DFT methods were used to investigate the geometrical, optical, and electronic properties. Twelve nanocomposites of catechin attached to carboxylated/uncarboxylated GQD were designed. The GQD was further doped with central/terminal boron atom or decorated with boron groups (organo-borane, borinic, and boronic groups). The available experimental data of parent catechin was used to validate the elected functional and basis set. Through hybridization, the energy gap of catechin was significantly narrowed by 50.66-61.48%. Therefore, its absorption was shifted from the UV to the visible region which matches the solar spectrum. Also, increasing the absorption intensity led to high light-harvesting efficiency close to unity that can increase current generation. The energy levels of designed dye nanocomposites are appropriately aligned with the conduction band and redox potential, indicating the feasibility of electron injection and regeneration. The observed properties confirm that the reported materials exhibit characteristics of interest thus they could be promising candidates for applications in DSSCs.

Computational quantum chemistry has become a powerful tool with a wide range of possibilities to solve chemical-physical problems. As a result of this, the interest in the applications of computational quantum chemistry has expanded considerably, and has opened up novel research opportunities. In particular, those related to the characterization of heavy-atoms complexes, as most electronic structure calculations for such systems struggle with the problem posed by the large number of electrons present in them, and consequently, the introduction of relativistic effects. The present study performed an exhaustive assess to characterized the uncommon NgH+ (Ng = Kr, Xe, and Rn) hydride cations in order to provide accurate rovibrational data of their isotopes to assist in the laboratory characterization or even their astronomical detection. Scalar relativistic effects were included, and the ground and first electronically exited states potential curves were obtained from benchmark ab initio CCSD(T)/CBS and MRCI+Q electronic structure calculations. Next, such interaction potentials, correctly extended to long-range asymptotic regions, were employed in quantum bound state calculations and molecular spectroscopic constants were determined for the most abundance 84Kr, 132Xe, and 222Rn isotopes. Our results were discussed in comparison with available experimental and previous theoretical estimates, aiming to treat accuracy issues. The new sets provide reference data that could serve for spectroscopic characterization of such low abundance and high radioactive species.

A DFT (density functional theory) study was conducted with eight oxovanadium complexes (C1 - C8) of general formula [VO(L1-4)(R)] (R = bipyridine, phenanthroline; L1-4 = group of ligands derived from dithiocarbamate). The obtained geometries showed a good correlation with the experimental structures. Molecular orbital analysis revealed that the contribution of the L-ligand in the SOMO (single-occupied molecular orbital) of the complexes correlated with the experimental antioxidant activity (IC50), while the contribution of the R-ligand to the LUMO (lowest unoccupied molecular orbital) of the complexes correlated with the experimental complex-DNA interaction (Kb). It has been identified that the presence of an electron-donating substituent group (such as -NH2) in the C5 - C6 structures should enhance these complexes' antioxidant and DNA interaction activities.

The primary goal of the current research is to describe an effective and eco-friendly adsorbent for the removal of aquatic micropollutants. The design of the cellulose-modified zinc oxide (ZnO) nanocomposite was successfully carried out by density functional calculations. The proposed structures of the constituent and composite materials were confirmed using formation energy (Ef), frontier orbitals, band gaps (Egap), density of state (DOS) plots, natural bond orbitals (NBO), and UV-Vis spectral analysis. The cellulose/(ZnO)12 composite was further used for the adsorption of different heavy metal ions such as Hg(II), Pb(II), Cd(II), Ni(II), and As(III) through calculation of electronic and optical properties. The values of the adsorption energy (Eads) show that the As(III) interacted better with the composite in both phases, i.e., gas (-806.98 kcal/mol) and aqueous (-491.66 kcal/mol). The analysis of frontier molecular orbital data exhibited a decrease in the Egap of composite@metal ion complexes. The high negative value of the solvation energies (ΔEsol) indicates the suitability of composite@metal ions in an aqueous environment. The nature of interactions between metal ions and the composite unit is analyzed by noncovalent interactions (NCI) and the quantum theory of atoms in molecules (QTAIM). The theoretical results of the present study show the feasibility of the cellulose/(ZnO)12 composite for the removal of heavy metal ions and provide useful information to experimentalists to treat contaminated water.

In present work, the influence of internal acceptors and π-spacers on optoelectronic properties for dye-sensitized solar cells (DSSCs) is investigated. The dyes consist of various internal acceptors (A), a triphenylamine donor and π-spacers combined with cyanoacrylic acid acceptor. Density functional theory (DFT) was employed to inspect the dye geometries, charge transport characteristics and electronic excitations. The frontier molecular orbitals (FMOs), highest occupied molecular orbital, lowest unoccupied molecular orbital and HOMO-LUMO energy gap are assisted in the determination of suitable energy levels for electron transfer, electron injection and regeneration of dye. The required photovoltaic parameters like JSC, ΔGreg, ΔGinj, LHE and other associated parameters are presented. The results demonstrate that altering the π-bridge and adding an internal acceptor to the D-π-A scaffold changes the photovoltaic properties and absorption energies. Therefore, the key objective of the current effort is to launch a theoretical groundwork for suitable operational alterations and scheme in creating successful DSSCs.

Data-driven methods are receiving significant attention in recent years for chemical and materials researches; however, more works should be done to leverage the new paradigm to model and analyze the adsorption of the organic molecules on low-dimensional surfaces beyond using the traditional simulation methods. In this manuscript, we employ machine learning and symbolic regression method coupled with DFT calculations to investigate the adsorption of atmospheric organic molecules on a low-dimensional metal oxide mineral system. The starting dataset consisting of the atomic structures of the organic/metal oxide interfaces are obtained via the density functional theory (DFT) calculation and different machine learning algorithms are compared, with the random forest algorithm achieving high accuracies for the target output. The feature ranking step identifies that the polarizability and bond type of the organic adsorbates are the key descriptors for the adsorption energy output. In addition, the symbolic regression coupled with genetic programming automatically identifies a series of hybrid new descriptors displaying improved relevance with the target output, suggesting the viability of symbolic regression to complement the traditional machine learning techniques for the descriptor design and fast modeling purposes. This manuscript provides a framework for effectively modeling and analyzing the adsorption of the organic molecules on low-dimensional surfaces via comprehensive data-driven approaches.

Because of the increasing scarcity of fossil fuels and the growing need for energy, it has become necessary to research new renewable energy resources. In this study, five new high-performance materials (TP-FA1F-TP - TP-FA5F-TP) of the D-π-A-π-D configuration based on triphenylamine (TPA) were theoretically investigated by applying DFT and TD-DFT methods for future application as heterojunction organic solar cells (BHJ). The influence of the modification of the acceptor (A) of the parent molecule TP-FTzF-TP on the structural, electronic, photovoltaic and optical properties of the TP-FA1F-TP - TP-FA5F-TP organic molecules was investigated in detail. TP-FA1F-TP - TP-FA5F-TP showed Egap in the interval of 1.44-2.01 eV with λabs in the range of 536-774 nm, open-circuit voltage (Voc) values varied between 0.3 and 0.56 V and power conversion efficiencies (PCE) ranging from (3-6) %. Our results also show that the donor molecules suggested in this research exhibit an improved performance compared to the recently synthesized TP-FTzF-TP, such as a lowest HOMO energy, a smaller Egap, and a greater absorption spectrum, and can lead to higher performance. Indeed, this theoretical research could lead to the future synthesis of better compounds as active substances used in BHJ.

In view of the numerous environmental hazards and health challenges linked to sulfur (iv) oxide (SO2), an indirect greenhouse gas, and the resultant need to develop efficient gas nanosensor devices, this research had as its principal focus on the theoretical evaluation of the gas sensing potential of metals: Ag, Au and Cu functionalized silicon-doped quantum dots (Si@QD) for the detection and adsorption of SO2 gas investigated using the first-principles density functional theory (DFT) computation at the B3LYP-D3(BJ)/def2-SVP level of theory. Eight (8) possible adsorption modes: SO2_O_Si@QD, SO2_O_Ag_Si@QD, SO2_O_Au_Si@QD, SO2_O_Cu_Si@QD, SO2_S_Si@QD, SO2_S_Ag_Si@QD, SO2_S_Au_Si@QD, and SO2_S_Cu_Si@QD were considered based on SO2 interactions with the studied materials at the -S and -O sites of the SO2 molecule. The counterpoise correction (BSSE) showed that five of the eight interactions had favorable Ead + BSSE values ranging from -0.31 to -1.98 eV. All the eight interactions were observed to be thermodynamically favorable with ΔG and ΔH ranging from -129.01 to -200.24 kcal/mol and -158.26 to -229.73 kcal/mol respectively. Results from the topology analysis reveal that van der Waals forces occurred the greatest at the gas-sensor interphase while SO2_S_ Cu_Si@QD is predicted to have the highest sensing potency based on the conductivity and recovery time estimations. These results confirm the potential efficient feasibility of real-world device application of the metals (Ag, Au, Cu) functionalized Si-doped QDs.

Removal of commonly used dyes from water bodies has recently gained great interest from the scientific community. Presence of the methylene blue (MB) dye in drinking water poses harmful effects on the human health. The large-scale removal of MB is achievable through highly efficient, inexpensive, renewable, and biodegradable adsorbents. Our research group has recently synthesized a sodium alginate-based hydrogel and explored its application towards the removal of MB. Previous results have shown that the synthesized hydrogel exhibits a high adsorption capacity of 51.34 mg/g under basic conditions. Herein, we employed the density functional theory (DFT) calculations to explore the mechanism of MB removal by using sodium alginate hydrogel at various pH levels. Results of this study have shown that under acidic/neutral conditions the removal of MB is endergonic (ΔGint = 6.10 kcal/mol). Whereas under basic conditions it is highly exergonic (ΔGint = -97.58 kcal/mol). Moreover, the QTAIM and NCI analyses have shown that the MB dye is chemisorbed to the absorbent via strong covalent-like interactions between the polymer's carboxylate groups and the hydrogens in MB. Furthermore, preferability of basic conditions have been confirmed by the large charge transfer (0.104 |e|), as compared to no charge being transferred in the acidic/neutral conditions.

Dye-sensitized solar cells (DSSCs) have drawn a significant interest due to their low production cost, light weight, better flexibility in design, and better tunability. Herein, two metal free organic dyes based on donor-π-acceptor (D-π-A) type architecture having methoxy substituted triphenyl amine (TPA) and methyl substituted indoline(IND) as the donor units, cyanoacrylic acid (CA) as the acceptor unit, and 8H-thieno [2', 3':4,5]thieno[3,2-b]thieno[2,3-d]pyrrole (TTP) unit as π-bridge are successfully designed for fabrication of DSSCs. To tune the optical properties, structural engineering has been carried out at the TTP unit via substituting different +I groups, viz., -H, -CH3, -OCH3, -CH2CH2, -SH, and -OH and different -I groups viz. -CF3, -COCH3, -COOH and -CN. Various structural, electronic and optical parameters are calculated for the designed dyes. Our study reveals that dyes substituted with electron withdrawing groups possess lower ΔH-L values for both TPA-CA and IND-CA groups of dyes. Moreover, the ESOP and GSOP values of all the dyes confirm the spontaneity of the electron injection and dye regeneration processes with respect to the conduction band of the TiO2 surface and redox potential of the I-/I3- redox couple. The absorption properties also manifest the red shift behavior of the designed dyes. Further, from the study of the structural and electronic properties of the dye-Ti5O10 clusters it is evident that the performance of the dyes get increased upon binding to the TiO2 surface. Hence, our study provides a good recommendation for further designing of dyes to enhance the performance of DSSCs.

Density functional theory (DFT) and time-dependent density functional theory (TD-DFT) approaches were applied to explore the effect of central transition metals and the dye/TiO2 interface on dye-sensitized solar cell (DSSC) performance and supply a promising way to estimate and screen possible candidates for DSSC applications. The interaction properties, bonding characteristics, sensitized mechanisms, charge transfer, frontier molecular orbitals, energy gap, partial densities of states (PDOS), non-covalent interactions (NCI), and electronic absorption spectra were examined and analyzed to provide the photovoltaic characteristics of Sc, Cu, and Ti tetrasulfonic acid phthalocyanine sensitizer@TiO2 interface in both gas phase and polar solvent as acetonitrile. The interfacial of TiPc-(SO3H)4 with TiO2, which facilitates the driving force for the electron injection of photosensitizers (ΔGinj), increases the charge separation, open-circuit voltage (Voc), and high light-harvesting efficiency (LHE) values. However, minimize the charge recombination, lifetime of the excited state (τ), regeneration driving force (ΔGreg). Our results reveal that TiPc-(SO3H)4@TiO2 is superior to those of ScPc-(SO3H)4, CuPc-(SO3H)4, TiPc-(SO3H)4 and Pc-(SO3H)4/TiO2, indicating the novel TiPc-(SO3H)4@TiO2 interface could be promising candidates for DSSC photovoltaic devices performance. In addition, the static mean polarizability and first hyperpolarizability of all six dyes elucidated that the TiPc-(SO3H)4@TiO2 interface can be regarded as a potential performer in non-linear optical (NLO) properties. These theoretical identifications may provide novel perspectives and instructions for future experimental researchers to promote the synthesis and application of TiPc-(SO3H)4@TiO2 interfaces to improve the photo-to-current conversion efficiency.

An effort has been made to explore the adsorption potential of activated carbon (AC) structures for adsorption of hydrogen sulfide (H2S) and sulfur dioxide (SO2) employing density functional theory (DFT) at GGA level. 2-ring, 3-ring, 6-ring, and 9-ring carbon structures are used as adsorbent surfaces. The above mentioned rings are examined by creation of defect and inclusion of hydrogen as well to get the clear view close to experimental observations of adsorption properties of activated carbon. The adsorption properties depend upon many factors including whether adsorbate adsorbs in planer or non-planer mode, defect creation in the adsorbent substrate, atomic hydrogen insertion in the system and size of the adsorbent system. Our calculations show that side by side (planer) interaction binds the molecules much more strongly in comparison with molecules adsorbed upon the surface in non-planer mode. If vacancy is created at the central position of the surface, the molecules bind with substantial binding energy. However, overall Eads of the molecules varies randomly and no consistency could be achieved. Additionally, smaller sized structures are favorable relative to the bigger surfaces. The highest Eads for both the molecules is -2.97 eV, though not on the same substrate system. Finally, it can be argued that activated carbon is very useful material for adsorbing the noxious gases.

Transition metals doped semiconductors have been extensively used as a greener alternative to lead-based solar cell materials. In this work, we have investigated the structure, electronic, optical, and thermo-chemical properties of CuCrX2 (X = S, Se, Te) by using the Conceptual Density Functional Theory (CDFT) approach. Different suitable exchange correlations have been used for the process of geometry optimization of systems in the study. Applied exchange correlations namely B3LYP and WB97XD demonstrate that the energy gap shows a decline from the atom S to Se to Te. HOMO-LUMO obtained from level B3LYP/LANL2DZ is in accordance with the stated data. The attained band gap directs that studied materials could be beneficial for further utilization in optoelectronic and photovoltaic devices. A comparative study has been made based on the selected exchange correlations for the analysis of investigated materials, which has not been explored commonly. The study reveals that B3LYP/LANL2DZ could be a better choice for a combination set of level and basis set for studying these types of compounds. CDFT-based global reactivity descriptors are computed and analyzed. The obtained band gap range indicates the desirable nature of CuCrX2 for further exploration in the application of Intermediate Band Solar cells.

Metal nanoclusters deposited on oxides have been widely used in photocatalysis playing an important role in the design of model catalysts with applications in heterogeneous catalysis. In particular, we are interested in the potential activity of these cluster-supported systems for the removal of nitrogen oxides either by possible catalytic reduction and/or by their adsorption. In this work, using first-principles methods, we evaluate the main characteristics of Agn (n = 1-4) nanoclusters isolated and deposited on anatase TiO2(101) and rutile TiO2(110) surfaces. Our results indicate that they are preferably adsorbed on rutile surface. The different formation energy at each surface can be explained using a Bader charge analysis. Particularly for Ag4 the lowest formation energy is obtained for tetrahedral geometry while the isolated Ag4 geometry is planar. Small silver deposits placed superficially on titania surfaces modify its electronic structures and improve the conduction band edges positions for possible NO reduction. Band edges positions with respect to the vacuum potential have been studied. The comparison of the conduction band minimum with the reduction potentials of NO/N2O and N2O/N2 shows that they are higher, being Ag3 on rutile and Ag1, Ag2 and Ag4P on anatase better for NO reduction. To complete the analysis, the calculation of work function, energy gap, ionization energy and electron affinity are relevant since they allow the location of semiconductor band edges at point of zero charge. Finally, the adsorption of nitrogen oxides is studied where the NO2 adsorption is favored over NO.

A variety of organic solar cells has been discovered, but there is a need for efficient optoelectronic material to obtain high power conversion efficiency. In this study, we derived new molecules from Z-shaped heptazethrene. We measured its photovoltaic parameters, including frontier molecular orbitals (where the energy gap decreases to 16% as compared to the reference), molecular electrostatic potential maps (more nucleophilic core), the density of states (partial and total), absorbance in Vis-IR region (in the range of 650-1000 nm), transition density matrix, and hole-electron mobility in terms of reorganization energy that showed 11% higher electron mobility (λe) and 52% higher hole mobility (λh) as compared to the reference. A comparable power conversion efficiency (∼9%) is obtained from a single photon. Using the concept of singlet fission, we can increase the efficiency twice using a single photon (based on the diradical character of the molecule). The diradical character of the entitled molecules was also calculated. The designed molecules fulfil the criteria of singlet fission that generate two excited triplets from a single photon (ES1>2ET1). The designed molecules are more stable than the reference indicated by the singlet-triplet energy gap, which is 37% higher. Hence this work assists the researcher in enhancing the efficiency of the solar cell.

Recent advancements in two-dimensional (2D) allotropes of carbon materials and their usage as superior CO2 adsorbents can decrease the detrimental impact of CO2 on climate change. With the use of quantum chemical calculations, the effect of metal clusters (Agn = 1-4 and Pdn = 1-4) on the structural and electrical characteristics of 55-77 2D graphene sheet is examined in the current work with an aim towards enhancing CO2 capture capacity. The findings revealed that the binding energy (Eb) of the 55-77 sheet decoration with Pdn = 1-4 metal clusters are greater owing to chemisorption by 1.17 eV, 1.69 eV, 0.27 eV, and 1.58 eV than the decoration with Agn = 1-4 clusters. Moreover, CO2 molecules adsorb on the Pdn = 1-4 cluster decorated systems having -0.35 eV, 0.83 eV, 1.53 eV, and -0.98 eV greater adsorption energies than on the Agn = 1-4 decorated 55-77 sheet due to a stronger charge transfer. Further, the findings of an atoms in molecules (AIM) study show that the interaction between CO2 and Pdn = 1-4 decorated 55-77 sheet is partially covalent and non-covalent, confirming the greater charge transfer between the CO2 molecule and Pdn = 1-4 decorated 55-77 systems. Moreover, the CO2 adsorption on Pdn = 1-4 decorated 55-77 systems is clearly demonstrated by non-covalent interaction (NCI) analysis to be a strong electrostatic interaction at sign(λ2)ρ = -0.05 a.u, and this is further supported by an electron localization function (ELF) map. The highest CO2 adsorption capacity is obtained for 55-77/Pd1+CO2 with the value of 6.27 wt % which concludes 55-77 sheet with Pdn decoration is a more suitable structure for CO2 adsorption than the Agn decorated system.

In this research, the thermoelectric properties of the (6, 6) two sided-closed single-walled boron nitride nanotube ((6, 6) TSC-SWBNNT) was investigated in the state without impurity and carbon atom impurity instead of boron and nitrogen atoms in the center, left, and right the nanotube. The test conditions were the energy range of -5.5 to 5.5 eV and temperatures of 200, 300, 500, 700, 900, 1100, and 1300 K. Based on the obtained results, with an increase in temperature and the creation of impurities, the band gap is affected and becomes noticeably smaller. At the temperature of 1300 K, the band gap shows the greatest decrease and the peak height shows the least decrease. With increasing temperature, the number of peaks has decreased, suggesting an increase in the mobility of electrons and holes and a decrease in their localization. The Seebeck coefficient figures also changed by replacing carbon atoms with boron and nitrogen atoms in different parts of the nanotube. In addition, the height of the heat conduction peaks increased with increasing temperature. However, the heat conduction values are generally in the range of 9-10 nm, which are small values. With the increase in temperature, ZT values increased such that the highest values corresponded to the temperature of 1300 K. The ZT values higher than 1, especially at high temperatures, show that (6, 6) TSC-SWBNNT nanotubes are suitable candidates for thermoelectric materials.

Hydrogen fluoride (HF) is a highly dangerous and corrosive gas that can cause severe burns and respiratory damage. The density functional theory method (DFT) used to study the interaction between the HF gas and the surface of a carbon nanocone (CNC) doped with gallium atom as a chemical sensor. The results showed that CNC wasn't a good candidate to sense the HF gas and consequently its electrical properties are changed insignificant. To improve the properties of the CNC, several strategies were tried: functionalizing by pyridinol (Pyr) and pyridinol oxide (PyrO), decorated with metals (M = B, Al, and Ga), and doped with element of third group (M = B, Al, and Ga). The obtained data demonstrated that the promising results were obtained by doping the CNC with Ga atom. After full optimization, we achieved one stable configuration between the HF gas and CNC-Ga structure (S15 configuration) with Eads = -19.86 kcal/mol. The electronic properties of the CNC-Ga structure is sensible changed after the HF molecule is adsorbed. According to calculated the energy gap between HOMO and LUMO orbitals of S15 configuration are increased which could be applied a chemical signal. Eventually, one could propose that the CNC-Ga has the ability to act as a Φ-type sensor based on its physical adsorption energy and quick recovery time and doped with gallium atom is a promising strategy.