Zn2+ is one of the most versatile biologically available metal ions, but accurate modeling of Zn2+ -containing metalloproteins at the biomolecular force field level can be challenging. Since most Zn2+ models are parameterized in bulk solvent, in-depth knowledge about their performance in a protein environment is limited. Thus, we systematically investigate here the behavior of non-polarizable Zn2+ models for their ability to reproduce experimentally determined metal coordination and ligand binding in metalloproteins. The benchmarking is performed in challenging environments, including mono- (carbonic anhydrase II) and bimetallic (metallo-β-lactamase VIM-2) ligand binding sites. We identify key differences in the performance between the Zn2+ models with regard to the preferred ligating atoms (charged/non-charged), attraction of water molecules, and the preferred coordination geometry. Based on these results, we suggest suitable simulation conditions for varying Zn2+ site geometries that could guide the further development of biomolecular Zn2+ models.

We have performed full atomistic molecular dynamics (MD) simulations to investigate structure and stability of bilayer membrane systems consisting of monomeric or polymeric 10,12-pentacosadiynoic acid (PCDA) units connected with lysine groups by amide bonds. The PCDA monomer molecules show a twisted three-rod-domain structure with two kinks but upon polymerization, they possess more elongated conformation. The resulting polydiacetylene (PDA) membrane systems have stable membrane structures at room temperature, which is similar to biological lipid bilayer membranes and maintain their gel-like membrane integrity even up to as high as 370 K. Structural properties such as area per monomer, membrane thickness, density profile, 2D pair distribution function, and orientational correlation function are also calculated to understand the membrane structure and check its stability upon thermal fluctuation with atomistic resolution. This study is expected to provide the understanding about PDA membrane systems in atomistic details as well as significant insights into designing new novel PDA sensors.

Ewald summation is famous for its successful applications in molecular simulations for systems under 2 dimensional periodic boundary condition (2D PBC, e.g., planar interfaces) and systems under 3D PBC (e.g., bulk). However, the extension to systems under 1D PBC (like porous structures and tubes) is largely hindered by the special functions in the formula. In this work, a simple approximation of Ewald 1D sum is introduced with its error rigorously controlled. To investigate the impacts on the efficiency and accuracy by different parts, a pairwise potential is calculated for a series of screening parameters ( α ) and radial distances ( ρ ) between two point charges. A mapping between the sum of trigonometric functions in Ewald 1D method and the sum of specific vectors further reveals the different converging speeds of different Fourier parts. When choosing α = 0.2 Å-1 , it is appropriate to ignore the insignificant parts in the sum to accelerate the method.

The COVID-19 pandemic has been a public health emergency, with deadly forms constantly emerging around the world, highlighting the dire need for highly effective antiviral therapeutics. Peptide therapeutics show significant potential for this viral disease due to their efficiency, safety, and specificity. Here, two thousand seven hundred eight antibacterial peptides were screened computationally targeting the Main protease (Mpro) of SARS CoV-2. Six top-ranked peptides according to their binding scores, binding pose were investigated by molecular dynamics to explore the interaction and binding behavior of peptide-Mpro complexes. The structural and energetic characteristics of Mpro-DRAMP01760 and Mpro-DRAMP01808 complexes fluctuated less during a 250 ns MD simulation. In addition, three peptides (DRAMP01760, DRAMP01808, and DRAMP01342) bind strongly to Mpro protein, according to the free energy landscape and principal component analysis. Peptide helicity and secondary structure analysis are in agreement with our findings. Interaction analysis of protein-peptide complexes demonstrated that Mpro's residue CYS145, HIS41, PRO168, GLU166, GLN189, ASN142, MET49, and THR26 play significant contributions in peptide-protein attachment. Binding free energy analysis (MM-PBSA) demonstrated the energy profile of interacting residues of Mpro in peptide-Mpro complexes. To summarize, the peptides DRAMP01808 and DRAMP01760 may be highly Mpro specific, resulting disruption in a viral replication and transcription. The results of this research are expected to assist future research toward the development of antiviral peptide-based therapeutics for Covid-19 treatment.

The ESCASA algorithm for analytical estimation of proton positions from coarse-grained geometry developed in our recent work has been implemented in modeling protein structures with the highly coarse-grained UNRES model of polypeptide chains (two sites per residue) and nuclear magnetic resonance (NMR) data. A penalty function with the shape of intersecting gorges was applied to treat ambiguous distance restraints, which automatically selects consistent restraints. Hamiltonian replica exchange molecular dynamics was used to carry out the conformational search. The method was tested with both unambiguous and ambiguous restraints producing good-quality models with GDT_TS from 7.4 units higher to 14.4 units lower than those obtained with the CYANA or MELD software for protein-structure determination from NMR data at the all-atom resolution. The method can thus be applied in modeling the structures of flexible proteins, for which extensive conformational search enabled by coarse-graining is more important than high modeling accuracy.

Polyethyleneimine (PEI), one of the non-viral vectors of great interest for gene delivery, was investigated at all-atom level, with particular emphasis on its branched form. We report the extension of our previously published CHARMM force field (FF) for linear PEI, with parameters optimized specifically for branched configurations. A new residue type for the branch connector is introduced and the charges and bonded parameters are derived from ab initio calculations based on a model polymer. The new FF is validated by extensive molecular dynamics simulations of solvated branched PEIs of various protonation fractions and branch lengths. The gyration radii, end-to-end distances, and diffusion coefficients are compared with results for linear PEIs of similar molecular weights and protonation patterns. Solvated complexes of DNA with (linear/branched) PEI were also investigated to determine favorable attachment conformations. The parametrized atomistic force field is suitable for simulations of PEI with arbitrary branching pattern, protonation, and size, and is expected to provide relevant insights regarding optimal conditions for DNA-PEI complex formation.

The hydration thermodynamics of a globular protein (AcP), three intrinsically disordered protein regions (1CD3, 1MVF, 1F0R) and a fully disordered protein (α-synuclein) is studied by an approach that combines an all-atom explicit water molecular dynamics simulations and three-dimensional reference interaction site model (3D-RISM) theory. The variation in hydration free energy with percentage disorder of the selected proteins is investigated through its nonelectrostatic and electrostatic components. A decrease in hydration free energy is observed with an increase in percentage disorder, indicating favorable interactions of the disordered proteins with the solvent. This confirms the role of percentage disorder in determining the aggregation propensity of proteins which is measured in terms of the hydration free energy in addition to their respective mean net charge and mean hydrophobicity. The hydration free energy is decoupled into energetic and entropic terms. A residue-wise decomposition analysis of the hydration free energy for the selected proteins is evaluated. The decomposition shows that the disordered regions contribute more than the ordered ones for the intrinsically disordered protein regions. The dominant role of electrostatic interactions is confirmed from the residue-wise decomposition of the hydration free energy. The results depict that the negatively charged residues contribute more to the total hydration free energy for the proteins with negative mean net charge, while the positively charged residues contribute more for proteins with positive mean net charge.

Machine learning is becoming increasingly more important in the field of force field development. Never has it been more vital to have chemically accurate machine learning potentials because force fields become more sophisticated and their applications expand. In this study a method for developing chemically accurate Gaussian process regression models is demonstrated for an increasingly complex set of molecules. This work is an extension to previous work showing the progression of the active learning technique in producing more accurate models in much less CPU time than ever before. The per-atom active learning approach has unlocked the potential to generate chemically accurate models for molecules such as peptide-capped glycine.

The molecular geometry of new titanium(IV) and oxidozirconium(IV) phenylacetohydroxamate complexes [TiCl2 (L1)2 ] (I) and [ZrO(L1)2 ] (II) (where L1 = Potassium phenylacetohydroxamate = C6 H5 CH2 CONHOK) computed by B3LYP/6-311++G(d,p) method has shown these to be distorted octahedral and square pyramidal, respectively. A comparison of computed characteristic bond lengths (CO, CN, and NO) of complexes with that of free ligand has shown chelation through carbonyl and hydroxamic oxygen atoms (O, O coordination). The TiO/ZrO bond lengths in complexes are suggestive of weak coordination through (carbonyl CO) and strong covalent (hydroxamic NO) bonding of the ligand. The magnitude of ClTiCl bond angle involving two chloride atoms is suggestive of cis-conformation at titanium metal in (I). The thermodynamic parameters Gibbs free energy, enthalpy, entropy, nuclear internal energy, constant volume heat capacity, and internal energy of ligand and complexes have been computed. From the energies of highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO), the global reactivity descriptors such as ionization potential (IP), electron affinity (EA), chemical potential (μ), hardness (η), softness (S), electronegativity (χ), electrophilicity index (ω), and dipole moment have been calculated. The computed vibrational frequencies, 1 H and 13 C NMR spectra have substantiated the molecular structure of complexes. The thermal behavior of complexes has been studied by thermogravimetric techniques (TGA, DTG, and DTA) in N2 atmosphere has shown complexes are thermally stable.

Polymorph discrimination for a molecular crystal has long been a challenging task, which, nonetheless, is a major concern in the pharmaceutical industry. In this work, we have investigated polymorph discrimination on three different molecular crystals, tetrolic acid, oxalic acid, and oxalyl dihydrazide, covering both packing polymorphism and conformational polymorphism. To gain more understanding, we have performed energy decomposition analysis based on many-body expansion, and have compared the results from the XO-PBC method, that is, the eXtended ONIOM method (XO) with the periodic boundary condition (PBC), with those from some commonly used dispersion corrected density functional theory (DFT-D) methods. It is shown here that, with the XYG3 doubly hybrid functional chosen as the target high level to capture the intra- and short-range intermolecular interactions, and the periodic PBE as the basic low level to take long range interactions into account, the XO-PBC(XYG3:PBE) method not only obtains the correct experimental stability orderings, but also predicts reasonable polymorph energy ranges for all three cases. Our results have demonstrated the usefulness of the present theoretical methods, in particular XO-PBC, while highlighted the importance of a better treatment of different kinds of interactions to be beneficial to polymorph control.

AzoChignolin is a photoswitchable variant of the mini-protein Chignolin with an azobenzene (AMPP) replacing the central loop. AzoChignolin is unfolded with AMPP in the trans-isomer. Transition to the cis-isomer causes β-hairpin folding similar to Chignolin. The AzoChignolin system is excellently suited for comprehensive analysis of folding nucleation kinetics. Utilizing multiple long-time MD simulations of AzoChignolin and Chignolin in MeOH and water, we estimated Markov models to examine folding kinetics of both peptides. We show that while AzoChignolin mimics Chignolin's structure well, the folding kinetics are quite different. Not only folding times but also intermediate states differ, particularly Chignolin is able to fold in MeOH into an α-helical intermediate which is impossible to form in AzoChignolin. The Markov models demonstrate that AzoChignolin's kinetics are generally faster, specifically when comparing the two main microfolding processes of hydrophobic collapse and turn formation. Photoswitchable loops are used frequently to understand the kinetics of elementary protein folding nucleation. However, our results indicate that intermediates and folding kinetics may differ between natural loops and photoswitchable variants.

Gold and silver subnanoclusters with few atoms are prominent candidates for catalysis-related applications, primarily because of the large fraction of lower-coordinated atoms exposed and ready to interact with external chemical species. However, an in-depth energetic analysis is necessary to characterize the relevant terms within the molecular adsorption process that can frame the interactions within the Sabatier principle. Herein, we investigate the interaction between Agn and Aun subnanoclusters (clu, n = 2-7) and N2 , NO, CO, and O2 molecules, using scalar-relativistic density functional theory calculations within van der Waals D3 corrections. The onefold top site is preferred for all chemisorption cases, with a predominance of linear (≈180°) and bent (≈120°) molecular geometries. A larger magnitude of adsorption energy is correlated with smaller distances between molecules and clusters and with the weakening of the adsorbates bond strength represented by the increase of the equilibrium distances and decrease of molecular stretching frequencies. From the energetic decomposition, the interaction energy term was established as an excellent descriptor to classify subnanoclusters in the adsorption/desorption process concomitant with the Sabatier principle. The limiting cases: (i) weak molecular adsorption on the subnanoclusters, which may compromise the reaction activation, where an interaction energy magnitude close to 0 eV is observed (e.g., physisorption in N2 /Ag6 ); and (ii) strong molecular interactions with the subnanoclusters, given the interaction energy magnitude is larger than at least one of the individual fragment binding energies (e.g., strong chemisorption in CO/Au4 and NO/Au4 ), conferring a decrease in the desorption rate and an increase in the possible poisoning rate. However, the intermediate cases are promising by involving interaction energy magnitudes between zero and fragment binding energies. Following the molecular closed-shell (open-shell) electronic configuration, we find a predominant electrostatic (covalent) nature of the physical interactions for N2 ⋯clu and CO ⋯clu (O2 ⋯clu and NO⋯clu), except in the physisorption case (N2 /Ag6 ) where dispersive interaction is dominant. Our results clarify questions about the molecular adsorption on subnanoclusters as a relevant mechanistic step present in nanocatalytic reactions.

Modern Density Functional Theory models are now suitable for many molecular and condensed phase studies. The study of noncovalent interactions, a well-known drawback, is no longer an insurmountable obstacle through design and empirical corrections. However, using empirical corrections as in the DFT-D methods might not be an all-in-one solution. This work uses a simple system, X2 -H2 O with X = Cl or Br, with two different interactions, halogen-bonded (XB) and hydrogen-halogen (HX), to investigate the capability of current density functional approximations (DFA) in predicting interaction energies with eight different exchange-correlation functionals. SAPT(DFT) provides, for all the studied cases, better predictions than the widely used supermolecular approach. In addition, the components of the interaction energy suggest where some of the shortcomings originate in each DFA. The analysis of the functionals used confirms that PBE0 and ω-B97X-D have a physically correct behavior. Using SAPT(DFT) and PBE0, and ω-B97X-D, we obtained the interaction energy of Cl2 and Br2 inside different clathrate cages and satisfactorily compared with wavefunction results; hence, the lower and upper limits of this value are defined: Cl2 @512 , -5.3 ± 0.3 kcal/mol; Cl2 @512 62 , -5.5 ± 0.1 kcal/mol; Br2 @512 62 , -7.6 ± 1.0 kcal/mol; Br2 @512 63 , -10.6 ± 1.0 kcal/mol; Br2 @512 64 , -10.9 ± 0.8 kcal/mol.

The bonding in lithium high-spin clusters contradicts the usual chemical bonding concept since there are no electron pairs between the atoms, and they are bound with parallel spin electrons. Quantum theory of atoms in molecules and interacting quantum atom analysis (IQA) were used to investigate the nature of bonding in the high-spin Linn + 1 (n = 2 - 5) clusters. Our findings demonstrate that the non-nuclear attractors (NNAs) are an essential component of the high-spin lithium clusters and play a key role in keeping them stable. Based on IQA energy terms, an electrostatic destabilizing interaction between the lithium atoms works against the cluster formation. On the other hand, the interactions between lithium atoms and NNA basins are stabilizing and outweigh the lithium-lithium destabilizing effects. In fact, NNAs tend to draw lithium atoms together and stabilize the resulting cluster. The high-spin clusters of lithium can be regarded as electrostatically driven compounds since the electrostatic components are primarily responsible for the stabilizing interactions between NNAs and Li atoms. The only exception is 3 Li2 , which lacks NNA and has a non-repellent lithium-lithium interaction. Indeed, in the 3 Li2 , the interatomic electrostatic component is negligibly small, and the exchange-correlation term leads to a weak bonding interaction.

The question of whether amino acids critical to protein folding kinetics are evolutionarily conserved has been investigated intensively in the past, but no consensus has yet been reached. Recently, we have demonstrated that the transition state, dictating folding kinetics, is characterized as the state of maximum dynamic cooperativity, i.e., the state of maximum correlations between amino acid contact formations. Here, we investigate the evolutionary conservation of those amino acids contributing significantly to the dynamic cooperativity. We find a strong indication of a new kind of relationship-necessary but not sufficient causality-between the evolutionary conservation and the dynamic cooperativity: larger contributions to the dynamic cooperativity arise from more conserved residues, but not vice versa. This holds for all the protein systems for which long folding simulation trajectories are available. To our knowledge, this is the first systematic demonstration of any kind of evolutionary conservation of amino acids relevant to folding kinetics.

We present a new implementation of real-time time-dependent density functional theory (RT-TDDFT) for calculating excited-state dynamics of periodic systems in the open-source Python-based PySCF software package. Our implementation uses Gaussian basis functions in a velocity gauge formalism and can be applied to periodic surfaces, condensed-phase, and molecular systems. As representative benchmark applications, we present optical absorption calculations of various molecular and bulk systems and a real-time simulation of field-induced dynamics of a (ZnO)4 molecular cluster on a periodic graphene sheet. We present representative calculations on optical response of solids to infinitesimal external fields as well as real-time charge-transfer dynamics induced by strong pulsed laser fields. Due to the widespread use of the Python language, our RT-TDDFT implementation can be easily modified and provides a new capability in the PySCF code for real-time excited-state calculations of chemical and material systems.

Efficacy and safety are among the most desirable characteristics of an ideal drug. The tremendous increase in computing power and the entry of artificial intelligence into the field of computational drug design are accelerating the process of identifying, developing, and optimizing potential drugs. Here, we present novel approach to design new molecules with desired properties. We combined various neural networks and linear regression algorithms to build models for cytotoxicity and anti-HIV activity based on Continual Molecular Interior analysis (CoMIn) and Cinderella's Shoe (CiS) derived molecular descriptors. After validating the reliability of the models, a genetic algorithm was coupled with the Des-Pot Grid algorithm to generate new molecules from a predefined pool of molecular fragments and predict their bioactivity and cytotoxicity. This combination led to the proposal of 16 hit molecules with high anti-HIV activity and low cytotoxicity. The anti-SARS-CoV-2 activity of the hits was predicted.

Elemental sulfur is often used in organic synthesis as its low cost and high abundance make it a highly desirable source of sulfur atoms. However, sulfur's unpredictable catenation behavior poses challenges to its widespread usage due to difficulties in designing new reactions that can account for its multifaceted reactivity. In order to accurately model sulfur's mechanisms using computational approaches, it is necessary to identify density functional theory (DFT) methods that are accurate on these systems. This study benchmarks 12 well-known DFT functionals that include local, non-local, and hybrid methods against DLPNO-CCSD(T)/aug-cc-pV(Q+d)Z//MP2/aug-cc-pV(T+d)Z/SMD(MeCN) for the accurate treatment of organic polysulfides, taking cyanide as a nucleophile. Our benchmarking results indicate that the M06-2X and B3LYP-D3(BJ) density functionals are the most accurate for calculating reaction energies, while local functionals performed the worst. For activation energies, MN15, MN15-L, M06-2X, and ωB97X-D are the most accurate. Our analysis of structural parameters shows that all functionals perform well for ground state optimizations except B97D3, while MN15-L and M06-2X performed best for transition structure optimizations. Overall, the four hybrid functionals MN15, M06-2X, ωB97X-D, and B3LYP-D3(BJ) appear adequate for studying the reaction mechanisms of polysulfides.

DNA damages are regarded as having harmful effects on cell. The base excision repair mechanism combats these effects by removing damaged bases. The deglycosylation mechanism of excising damaged bases by DNA glycosylase and the state of the leaving base have been controversial. The enzymatic reaction of DNA glycosylase to remove the damaged bases involves not only the formation and breaking of chemical bonds, but also complex polarization effect and charge transfer, which cannot be accurately simulated by the QM/MM method combined with the fixed charge force field. This work has developed the ABEEM fluctuating polarizable force field combining with the QM method, that is (QM/MM[ABEEM]), to accurately simulate the proton transfer, charge transfer and the charge distribution. The piecewise function is used as the valence-state electronegativity in the QM/MM (ABEEM) to realize the accurate fitting of the charge distribution in reaction. And the charge transfer is accurately simulated by the local charge conservation conditions. Four deglycosylation mechanisms including the monofunctional and difunctional mechanisms of four neutral and protonated cytosine derivatives are explored. It is confirmed that the monofunctional mechanism of Asp-activated nucleophile water is a better deglycosylation mechanism and the base is protonated before the reaction occurs. Protonization of the base reduced the activation energy by 10.00-17.00 kcal/mol. Asp provides the necessary charge for the reaction, and DNA glycosylase preferentially cleaves ɛC. This work provides a theoretical basis for the research of excising damaged bases by DNA glycosylase.

Novel agents to treat invasive fungal infections are urgently needed because the small number of established targets in pathogenic fungi makes the existing drug repertoire particularly vulnerable to the emergence of resistant strains. Recently, we reported that Candida albicans Bdf1, a bromodomain and extra-terminal domain (BET) bromodomain with paired acetyl-lysine (AcK) binding sites (BD1 and BD2) is essential for fungal cell growth and that an imidazopyridine (1) binds to BD2 with selectivity versus both BD1 and human BET bromodomains. Bromodomain binding pockets contain a conserved array of structural waters. Molecular dynamics simulations now reveal that one water molecule is less tightly bound to BD2 than to BD1, explaining the site selectivity of 1. This insight is useful in the performance of ligand docking studies to guide design of more effective Bdf1 inhibitors, as illustrated by the design of 10 new imidazopyridine BD2 ligands 1a-j, for which experimental binding and site selectivity data are presented.

Coupled cluster calculations are traditionally performed over Hartree-Fock reference orbitals (HF-CC methodology). However, in the literature it has been repeatedly raised whether the use of a Kohn-Sham reference (KS-CC methodology) might result in improved performance relative to HF-CC. In the present study, we re-examine the relation of HF-CC and KS-CC methods by comparing the results of widely applied truncated CC calculations (CCSD, CCSD(T), CCSDT) to the limit of full configuration interaction (FCI), which serves as an undebatable reference point of accuracy. Based on a series of CC calculations on diatoms and transition metal complexes, we demonstrate that no systematic improvement of coupled cluster electronic energies, densities and chemical reaction energies is expected when changing from HF to a KS reference. Nevertheless, fortuitous error cancellations might occasionally result in illusory improvement compared to HF-CC. Altogether, the application of KS-CC is not advantageous over HF-CC, but it is also not unreasonable as the choice of reference has negligible influence on the results at sufficiently high CC levels. In addition, KS-CC can be a particularly useful alternative if difficulties are encountered in HF or HF-CC convergence. It is also notable that KS-CC results are found to be practically independent of the chosen density functional, which implies that almost any KS-CC method can be used in place of HF-CC.

The prediction of (un)binding rates and free energies is of great significance to the drug design process. Although many enhanced sampling algorithms and approaches have been developed, there is not yet a reliable workflow to predict these quantities. Previously we have shown that free energies and transition rates can be calculated by directly simulating the binding and unbinding processes with our variant of the WE algorithm "Resampling of Ensembles by Variation Optimization", or "REVO". Here, we calculate binding free energies retrospectively for three SAMPL6 host-guest systems and prospectively for a SAMPL9 system to test a modification of REVO that restricts its cloning behavior in quasi-unbound states. Specifically, trajectories cannot clone if they meet a physical requirement that represents a high likelihood of unbinding, which in the case of this work is a center-of-mass to center-of-mass distance. The overall effect of this change was difficult to predict, as it results in fewer unbinding events each of which with a much higher statistical weight. For all four systems tested, this new strategy produced either more accurate unbinding free energies or more consistent results between simulations than the standard REVO algorithm. This approach is highly flexible, and any feature of interest for a system can be used to determine cloning eligibility. These findings thus constitute an important improvement in the calculation of transition rates and binding free energies with the weighted ensemble method.

Described are the first two molecular designs of the triply periodic Schwarz P surface using merely the Schläfli t{3,7} pattern of sp2 -hybridized carbon atoms. Each atom is exactly part of one heptagon and two hexagon rings so that two heptagons do not share the same edge or vertex. Such pattern, called hyperbolic soccer ball obeys the isolated-heptagon rule with the minimum possible number of hexagons between heptagons similar to the isolation of pentagons from hexagons in the C60 fullerene. Both of the designed P surfaces are unbalanced, that is, they have two unequal sides, and belong to space groups P432 of the cubic system, and P4/ncc of the tetragonal system, respectively. Unit cells have a multiple of 24 heptagons similar to the only one previously known in literature Schwarzite with the hyperbolic soccer ball pattern-the D surface of Vanderbilt and Tersoff. The geometry of the periodic structures and unit cell parameters were fully optimized by DFT calculations using CASTEP software with PBE and PBESOL functionals under generalized gradient approximation. The effect of P and D surface dilution by hexagons on the calculated density, elastic and electronic properties is discussed.