We present CHAMPION (Chalmers hierarchical atomic, molecular, polymeric, and ionic analysis toolkit): a software developed to automatically detect time-dependent bonds between atoms based on their dynamics, classify the local graph topology around them, and analyze the physicochemical properties of these topologies by statistical physics. In stark contrast to methodologies where bonds are detected based on static conditions such as cut-off distances, CHAMPION considers pairs of atoms to be bound only if they move together and act as a bound pair over time. Furthermore, the time-dependent global bond graph is possible to split into dynamically shifting connected components or subgraphs around a certain chemical motif and thereby allow the physicochemical properties of each such topology to be analyzed by statistical physics. Applicable to condensed matter and liquids in general, and electrolytes in particular, this allows both quantitative and qualitative descriptions of local structure, as well as dynamical processes such as speciation and diffusion. We present here a detailed overview of CHAMPION, including its underlying methodology, implementation, and capabilities.

Coarse-grained normal mode analyses of protein dynamics rely on the idea that the geometry of a protein structure contains enough information for computing its fluctuations around its equilibrium conformation. This geometry is captured in the form of an elastic network (EN), namely a network of edges between its residues. The normal modes of a protein are then identified with the normal modes of its EN. Different approaches have been proposed to construct ENs, focusing on the choice of the edges that they are comprised of, and on their parameterizations by the force constants associated with those edges. Here we propose new tools to guide choices on these two facets of EN. We study first different geometric models for ENs. We compare cutoff-based ENs, whose edges have lengths that are smaller than a cutoff distance, with Delaunay-based ENs and find that the latter provide better representations of the geometry of protein structures. We then derive an analytical method for the parameterization of the EN such that its dynamics leads to atomic fluctuations that agree with experimental B-factors. To limit overfitting, we attach a parameter referred to as flexibility constant to each atom instead of to each edge in the EN. The parameterization is expressed as a non-linear optimization problem whose parameters describe both rigid-body and internal motions. We show that this parameterization leads to improved ENs, whose dynamics mimic MD simulations better than ENs with uniform force constants, and reduces the number of normal modes needed to reproduce functional conformational changes.

The resonance theory is still very useful in understanding the valence electron structure. However, such a viewpoint is not usually obtained by general-purpose quantum chemical calculations, instead requires rather special treatment such as valence bond methods. In this study, we propose a method based on second quantization to analyze the results obtained by general-purpose quantum chemical calculations from the local point of view of electronic structure and analyze diazadiboretidine and the tautomerization of formamide. This method requires only the "PS"-matrix, consisting of the density matrix (P-matrix) and overlap matrix, and can be computed with a comparable load to that of Mulliken population analysis. A key feature of the method is that, unlike other methods proposed so far, it makes direct use of the results of general-purpose quantum chemical calculations.

This paper presents a brief summary of the difficulty that resides in the definition of the elusive concept of local chemical hardness. We argue that a definition of local hardness should be useful to a reactivity principle and not just as a mere definition. We then continue with a formal discussion about the benefits and difficulties of using the Fukui potential, which is interpreted as an alchemical derivative (alchemical hardness), as descriptor of local hardness of molecules. Computational evidence shows that the alchemical hardness is at least as good a descriptor as the combination of other two well-stabilized descriptors of local hardness, such as the Fukui function and grand canonical local hardness. Although our results are auspicious for the alchemical hardness as descriptor of local hardness, we finish by calling the attention of the community on the importance of discussing the raison d'être of a local hardness function and its main characteristics. We suggest that an axiomatic construction of local hardness could be they way of constructing a local hardness which is both useful and free of arbitrariness.

The development of polymer electrolytes (PEs) is crucial for advancing safe, high-energy density batteries, such as lithium-metal and other beyond lithium-ion chemistries. However, reaching the optimum balance between mechanical stiffness and ionic conductivity is not a straightforward task. Zwitterionic (ZI) gel electrolytes comprising lithium salt and ionic liquid (IL) solutions within a fully ZI polymer network can, in this context, provide useful properties. Although such materials have shown compatibility with lithium metal in batteries, several fundamental structure-dynamic relationships regarding ionic transport and the Li+ coordination environment remain unclear. To better resolve such issues, molecular dynamics simulations were carried out for two IL-based electrolyte systems, N-butyl-N-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide ([BMP][TFSI]) with 1 M LiTFSI salt and a ZI gel electrolyte containing the IL and a ZI copolymer: poly(2-methacryloyloxyethyl phosphorylcholine-co-sulfobetaine vinylimidazole), poly(MPC-co-SBVI). The addition of ZI polymer decreases the [TFSI]- -[Li]+ interactions and increases the IL ion diffusivities, and consequently, the overall ZI gel ionic conductivity. The structural analyses showed a large preference for lithium-ion interactions with the polymer phosphonate groups, while the [TFSI]- anions interact directly with the sulfonate group and the [BMP]+ cations only display secondary interactions with the polymer. In contrast to previous experimental data on the same system, the simulated transference numbers showed smaller [Li]+ contributions to the overall ionic conductivities, mainly due to negatively charged lithium aggregates and the strong lithium-ion interactions in the systems.

Transactivation response element RNA/DNA-binding protein 43 (TDP-43) is involved in the regulation of alternative splicing of human neurodegenerative disease-related genes through binding to long UG-rich RNA sequences. Mutations in TDP-43, most in the homeodomain, cause neurological disorders such as amyotrophic lateral sclerosis and fronto temporal lobar degeneration. Several mutants destabilize the structure and disrupt RNA-binding activity. The biological functions of these mutants have been characterized, but the structural basis behind the loss of RNA-binding activity is unclear. Focused on the specific TDP-43-ssRNA complex (PDB code 4BS2), we applied molecular dynamics simulations and the molecular mechanics Poisson-Boltzmann surface area free energy calculation to characterize and explore the structural and dynamic effects between ssRNA and TDP-43. The energetic analysis indicated that the intermolecular van der Waals interaction and nonpolar solvation energy play an important role in the binding process of TDP-43 and ssRNA. Compared with the wild-type TDP-43, the reduction of the polar or non-polar interaction between all the mutants F149A, D105A/S254A, R171A/D174A, F147L/F149L/F229L/F231L and ssRNA is the main reason for the reduction of its binding free energy. Decomposing energies suggested that the extensive interactions between TDP-43 and the nitrogenous bases of ssRNA are responsible for the specific ssRNA recognition by TDP-43. These results elucidated the TDP-43-ssRNA interaction comprehensively and further extended our understanding of the previous experimental data. The uncovering of TDP-43-ssRNA recognition mechanism will provide us useful insights and new chances for the development of anti-neurodegenerative drugs.

Sugar alcohol dehydration in hot water is an important reaction that allows for environmentally friendly biomass conversion without the use of organic solvents. Here, we report a free-energy analysis by metadynamics (MTD) simulations based on ab initio density functional theory and semiempirical density-functional tight-binding method to understand the mechanism of dehydration reactions of d-sorbitol (SBT) in hot acidic water. Comparing the results of ab initio and semiempirical MTD, it was found that the latter gives a reliable free energy surface of SBT dehydration reaction, although the results vary upon the inclusion of dispersion correction. It was found that the reaction proceeds consistently via an SN 2 mechanism, whereby the free energy of protonation of the hydroxyl group created as an intermediate is affected by the acidic species. This mechanism was further verified by real-time trajectories started from the transition state using ab initio molecular dynamics simulations. The free energy barriers of the reaction pathways leading to five-membered ether products are lower than those leading to six-membered ether products, in agreement with experiment. This outcome can be ascribed, in part, to our finding that the reaction barrier of the pathway is correlated to the stability of the SBT confined conformation at the initial stage of the reaction.

The excitation energies, singlet-triplet energy gap and spin-orbit coupling constants for Zn-, GaCl-, Pd-, and Pt- tetrasulfonyl phthalocyanines complexes (ZnPc, GaClPc, PdPc, and PtPc) have been computed by using the density functional theory and employing the M06 exchange-correlation functional. Results show that these systems possess interesting photophysical properties, which make them possible photosensitizers to be proposed in photodynamic therapy (PDT). Absorption energies of all the complexes examined have been found falling inside the so-called therapeutic window (550-800 nm). Singlet-triplet energy gap values are higher than those required for the production of cytotoxic molecular oxygen and the spin-orbit coupling constants are such as to ensure an efficient spin orbit intersystem crossing. The obtained data are consistent with the experimental oxygen singlet quantum yields. The platinum complex appears to be the most effective candidate to propose for PDT.

The pH-Low Insertion Peptide (pHLIP) is a membrane-active peptide that spontaneously folds into a transmembrane α-helix upon acidification. This activity enables pHLIP to potentially act as a vector for drugs related to diseases characterized by acidosis such as cancer or heart ischemia. Presently, due to aggregation-based effects, formulations of pHLIP are only viable at near-μM concentrations. In addition, since most of pHLIP's measurable qualities involve a membrane, probing the details of pHLIP in the interstitial region is difficult. In attempts to shed light on these issues, we performed constant pH molecular dynamics simulations on pHLIP as well as P20G, a variant with increased helicity, in solution at 0 and 150 mM NaCl over a broad range of pHs. In general, the addition of ions reduced the effective pKa of the acidic residues in pHLIP. P20G exhibits a higher helicity than pHLIP in general and is more compact than pHLIP at pH values under 4. In terms of charge effects, sodium cations localized predominantly to the C-terminus of the peptide with a high density of acidic residues. Additionally, the salt bridge between R11 and D14 is by far the most favored and particularly so with pHLIP at 150 mM NaCl. We expect that this approach will be a valuable tool to screen variants of pHLIP for favorable properties in solution, an aspect of pHLIP design that to this point has largely been neglected.

Energetic effects of solvation of SbF5 , SbCl5 , and 21 group 13 Lewis acids (LA) and their molecular complexes with acetonitrile and pyridine are evaluated using SMD approach. Compared to the gas phase, solvation increases the stability of boron- and aluminum-containing complexes but decreases the stability of gallium and indium-containing homologs due to larger solation energies of free LA. New Lewis acidity scales, based on the Gibbs energy of dissociation of the molecular complexes LA·pyridine and LA·acetonitrile in the gas phase, in benzene and acetonitrile solutions, are proposed.

To explore the characteristics of group 14 elements in sp3 and sp2 hybrid environments systematically, the concept of fragment structure energy (FSE) was proposed through ab initio molecular orbital method. A fragment in this study means a building block of molecular structure and the energy of each kind of fragments (FSE) is obtained from the total electronic energy of different size of model compounds by just a simple algebraic method. The model compounds are the hydrogen-terminated diamond and graphene analogs as the typical compounds in the ideal sp3 - and sp2 -environment, respectively. As a result, the sp3 environment was found to be more stable than the sp2 for all the group 14 elements (C-Pb) in the ideal hybrid environment. Furthermore, a mixing effect of carbon and heavier group 14 elements (E = Si, Ge, Sn, and Pb) was investigated by comparing the E/C-alternately mixed- and the pure FSEs.

The diagonal components and the trace of tensors which account for chiroptical response of the hydrazine molecule N2 H4 , that is, static anapole magnetizability and frequency-dependent electric dipole-magnetic dipole polarisability, are a function of the ϕ ≡  ∠  H─N─N─H dihedral angle. They vanish for symmetry reasons at ϕ = 0° and ϕ = 180°, corresponding respectively to C2v and C2h point group symmetries, that is, cis and trans conformers characterized by the presence of molecular symmetry planes. Nonetheless, vanishing diagonal components have been observed also in the proximity of  ∠  H─N─N─H = 90°, in which the point group symmetry is C2 and hydrazine is unquestionably chiral. In the boranylborane molecule B2 H4 , assuming the B─B bond in the y direction, the ayy component of the anapole magnetizability tensor approximately vanishes for dihedral angles  ∠  H─B─B─H corresponding to chiral rotamers which belong to D2 symmetry. Such anomalous effects have been ascribed to physical achirality of these conformers, that is, to their inability to sustain electronic current densities inducing either anapole moments, or electric and magnetic dipole moments, about the chiral axis connecting heavier atoms, as well as perpendicular directions. In other terms, the structure of certain geometrically chiral rotamers may be such that neither toroidal nor helical flow, which determine chiroptical phenomenology, can take place in the presence of perturbing fields parallel or orthogonal to the chiral axis.

Theoretical/computational description of excited state molecular dynamics is nowadays a crucial tool for understanding light-matter interactions in many materials. Here we present an open-source Python-based nonadiabatic molecular dynamics program package, namely PyUNIxMD, to deal with mixed quantum-classical dynamics for correlated electron-nuclear propagation. The PyUNIxMD provides many interfaces for quantum chemical calculation methods with commercial and noncommercial ab initio and semiempirical quantum chemistry programs. In addition, the PyUNIxMD offers many nonadiabatic molecular dynamics algorithms such as fewest-switch surface hopping and its derivatives as well as decoherence-induced surface hopping based on the exact factorization (DISH-XF) and coupled-trajectory mixed quantum-classical dynamics (CTMQC) for general purposes. Detailed structures and flows of PyUNIxMD are explained for the further implementations by developers. We perform a nonadiabatic molecular dynamics simulation for a molecular motor system as a simple demonstration.

We describe a bundle for UCSF ChimeraX called SEQCROW that provides advanced structure editing capabilities and quantum chemistry utilities designed for complex organic and organometallic compounds. SEQCROW includes graphical presets and bond editing tools that facilitate the generation of publication-quality molecular structure figures while also allowing users to build molecular structures quickly and efficiently by mapping new ligands onto existing organometallic complexes as well as adding rings and substituents. Other capabilities include the ability to visualize vibrational modes and simulated IR spectra, to compute and visualize molecular descriptors including percent buried volume, ligand cone angles, and Sterimol parameters, to process thermochemical corrections from quantum mechanical computations, to generate input files for ORCA, Psi4, and Gaussian, and to run and manage computational jobs.

Despite their mass production and large applications, polyolefins' stability and durability toward the air, moisture, and weather resistance is a challenge for the ecosystem. After long-term exposure to ultraviolet (UV) radiation or high-temperature or erosion, polyolefins undergo degradation generating microplastics (MPs). The MPs generated after the degradation of these polyolefins are hazardous for the ecosystem. In the present work, we have carried out density functional theory (DFT) studies to investigate the photodegradation of six different polyolefins ranging from polyethylene to polydecene, differing in side-chain. Herein, we have investigated photooxidized derivatives of different polyolefins and analyzed their relative stability, conformations, UV-visible spectral behavior, and carbonyl index. The photooxidized derivatives of various polyolefins formed during degradation are examined. The time-dependent density functional theory analysis confirms that the carbonyl groups of photooxidized products show absorption peak in Infrared (IR) and visible region, acting as light-absorbing species. The relative stabilities of hydroperoxide formed during photo/thermal oxidation of different polyolefins have been evaluated to explain the degradation behavior. The oligomerization and stabilization energies of their corresponding hydroperoxide's were computed and analyzed to explain the degradation behavior of the polyolefins. The computed results suggest that polyolefins in their pristine state are stable toward photooxidation, but chemical impurities like carbonyl, unsaturated carbonyl, carboxylic acid, and hydroperoxide derivatives make them prone to undergo degradation, a fundamental process leading to generation of MPs. The comparative results confirmed that the side-chain length affects the stability and degradation of different polyolefins toward photooxidation.

The current study dwells upon the efforts to computationally probe a phosphine-free pincer-nickel complex that would demonstrate an efficiency better than the reported phosphine-based pincer-nickel complex (iPr2 POCNEt2 )Ni(CH2 CN) for cyanomethylation reaction. For this purpose, the mechanism of cyanomethylation of benzaldehyde was studied quantum mechanically for a series of 11 pincer-nickel complexes. The energetics of various intermediates and transition states involved in the catalytic cycle for each catalyst was compared with the corresponding energetics of the Miller's catalyst (iPr2 POCNEt2 )Ni(CH2 CN) that is reported to accomplish the cyanomethylation at room temperature. While pincer complexes (iPr4 NNN)Ni(CH2 CN) and (iPr4 NCN)Ni(CH2 CN) containing strong σ-donating amines were found to fare poorly, pincer-nickel complexes (iPr2 NCN)Ni(CH2 CN) and (dm PheboxNCN)Ni(CH2 CN) based on weaker σ-donating imines had energetics more favorable than the reported efficient catalyst (iPr2 POCNEt2 )Ni(CH2 CN). While strong trans-influencing C as the pincer central atom was found to be pivotal for lowering the cyanomethylation kinetics, presence of a poor trans-influencing N proved to be detrimental on the overall energetics.

Drug resistance in tuberculosis is major threat to human population. In the present investigation, we aimed to identify novel and potent benzimidazole molecules to overcome the resistance management. A series of 20 benzimidazole derivatives were examined for its activity as selective antitubercular agents. Initially, AutodockVina algorithm was performed to assess the efficacy of the molecules. The results are further enriched by redocking by means of Glide algorithm. The binding free energies of the compounds were then calculated by MM-generalized-born surface area method. Molecular docking studies elucidated that benzimidazole derivatives has revealed formation of hydrogen bond and strong binding affinity in the active site of Mycobacterium tuberculosis protein. Note that ARG308, GLY189, VAL312, LEU403, and LEU190 amino acid residues of Mycobacterium tuberculosis protein PrpR are involved in binding with ligands of benzimidazoles. Interestingly, the ligands exhibited same binding potential to the active site of protein complex PrpR in both the docking programs. In essence, the result portrays that benzimidazole derivatives such as 1p, 1q, and 1 t could be potent and selective antitubercular agents than the standard drug isoniazid. These compounds were then subjected to molecular dynamics simulation to validate the dynamics activity of the compounds against PrpR. Finally, the inhibitory behavior of compounds was predicted using a machine learning algorithm trained on a data collection of 15,000 compounds utilizing graph-based signatures. Overall, the study concludes that designed benzimidazoles can be employed as antitubercular agents. Indeed, the results are helpful for the experimental biologists to develop safe and non-toxic drugs against tuberculosis.

The diversity of ice polymorphs is of interest in condensed-matter physics, engineering, astronomy, and biosphere and climate studies. In particular, their triple points are critical to elucidate the formation of each phase and transitions among phases. However, an approach to distinguish their molecular structures is lacking. When precise molecular geometries are given, order parameters are often computed to quantify the degree of structural ordering and to classify the structures. Many order parameters have been developed for specific or multiple purposes, but their capabilities have not been exhaustively investigated for distinguishing ice polymorphs. Here, 493 order parameters and their combinations are considered for two triple points involving the ice polymorphs ice III-V-liquid and ice V-VI-liquid. Supervised machine learning helps automatic and systematic searching of the parameters. For each triple point, the best set of two order parameters was found that distinguishes three structures with high accuracy. A set of three order parameters is also suggested for better accuracy.