We consider wavefunctions built from antisymmetrized products of two-electron wavefunctions (geminals), which is arguably the simplest extension of the antisymmetrized product of one-electron wavefunctions (orbitals) (i.e., a Slater determinant). Extensive use of geminals in wavefunctions has been limited by their high cost stemming from the many combinations of the two-electron basis functions (orbital pairs) used to build the geminals. When evaluating the overlap of the APG wavefunction with an orthogonal Slater determinant, this cost can be interpreted as the cost of evaluating the permanent, resulting from the symmetry with respect to the interchange of orbital pairs, and the cost of assigning the occupied orbitals to the orbital pairs of the wavefunction. Focusing on the latter, we present a graphical interpretation of the Slater determinant and utilize the maximum weighted matching algorithm to estimate the combination of orbital pairs with the largest contribution to the overlap. Then, the cost due to partitioning the occupied orbitals in the overlap is reduced from to . Computational results show that many of these combinations are not necessary to obtain an accurate solution to the wavefunction. Because the APG wavefunction is the most general of the geminal wavefunctions, this approach can be applied to any of the simpler geminal wavefunction ansätze. In fact, this approach may even be extended to generalized quasiparticle wavefunctions, opening the door to tractable wavefunctions built using components of arbitrary numbers of electrons, not just two electrons.

Topological indices are an important method for understanding the fundamental topology of chemical structures. Quantitative structure properties relationship (QSPR) is an analytical approach for breaking down a molecule into a sequence of numerical values that describe the chemical and physical characteristics of the molecule. In this article, we have developed the QSPR analysis between eigenvalue-based topological indices and physical properties of COVID-19 drugs to predict the significance level of eigenvalue based indices. We have to use MATLAB for the computation of indices and SPSS for analysis. We show that positive interia index, signless Laplacian Estrada index and Randić energy are the best predictors of molar reactivity, polar surface area and molecular weight, respectively.

Histidine (an imidazole-based amino acid) is a promising building block for short aromatic peptides containing a proton donor/acceptor moiety. Previous studies have shown that polyalanine helical peptides substituted at regular intervals with histidine residues exhibit both structural stability as well as high proton affinity and high conductivity. Here, we present first-principle calculations of non-aqueous histidine-containing 3-, α- and π-helices and show that they are able to form hydrogen-bonded networks mimicking proton wires that have the ability to shuttle protons via the Grotthuss shuttling mechanism. The formation of these wires enhances the stability of the helices, and our structural characterizations confirm that the secondary structures are conserved despite distortions of the backbones. In all cases, the helices exhibit high proton affinity and proton transfer barriers on the order of 1~4 kcal/mol. Zero-point energy calculations suggest that for these systems, ground state vibrational energy can provide enough energy to cross the proton transport energy barrier. Additionally, molecular dynamics results suggests that the protons are transported unidirectionally through the wire at a rate of approximately 2 Å every 20 fs. These results demonstrate that efficient deprotonation-controlled proton wires can be formed using non-aqueous histidine-containing helical peptides.

Li-S batteries are a promising alternative to Li-ion batteries, offering large energy storage capacity and wide operating temperature range. However, their performance is heavily affected by the Li-polysulfide (LiPS) shuttling. Computational screening of LiPS adsorption on single-atom catalyst (SAC) substrates is of great aid to the design of Li-S batteries which are robust against the LiPS shuttling from the cathode to the anode and the electrolyte. To facilitate this process, we develop a machine learning (ML) protocol to accelerate the systematic mapping of dominant local energy minima found with calculations based on the density functional theory (DFT), and, in turn, fast screening of LiPS adsorption properties on SACs. We first validate the approach by probing the potential energy surface for LiPS adsorbed on graphene decorated with a Fe-N-C SAC. We identify minima whose binding energies are better or on par with the one previously reported in the literature. We then move to analyze the adsorption trends on Zn-N-C SAC and observe similar adsorption strength and behavior with the Fe-N-C SAC, highlighting the good predictive power of our protocol. Our approach offers a comprehensive and computationally efficient alternative to conventional approaches studying LiPS adsorption.

The spread of novel virus SARS-CoV-2, well known as COVID-19 has become a major health issue currently which has turned up to a pandemic worldwide. The treatment recommendations are variable. Lack of appropriate medication has worsened the disease. On the basis of prior research, scientists are testing drugs based on medical therapies for SARS and MERS. Many drugs which include lopinavir, ritonavir and thalidomide are listed in the new recommendations. A topological index is a type of molecular descriptor that simply defines numerical values associated with the molecular structure of a compound that is effectively used in modeling many physicochemical properties in numerous quantitative structure-property/activity relationship (QSPR/QSAR) studies. In this study, several degree-based and neighborhood degree sum-based topological indices for several antiviral drugs were investigated by using a -polynomial and neighborhood -polynomial methods. In addition, a QSPR was established between the various topological indices and various physicochemical properties of these antiviral drugs along with remdesivir, chloroquine, hydroxychloroquine and theaflavin was performed in order to assess the efficacy of the calculated topological indices. The obtained results reveal that topological indices under study have strong correlation with the physicochemical characteristics of the potential antiviral drugs. A biological activity (pIC50) of these compounds were also investigated by using multiple linear regressions (MLR) analysis.

The entire world is struggling to control the spread of coronavirus (COVID-19) as there are no proper drugs for treating the disease. Under clinical trials, some of the repurposed antiviral drugs have been applied to COVID-19 patients and reported the efficacy of the drugs with the diverse inferences. Molecular topology has been developed in recent years as an influential approach for drug design and discovery in which molecules that are structurally related show similar pharmacological properties. It permits a purely mathematical description of the molecular structure so that in the development of identification of new drugs can be found through adequate topological indices. In this paper, we study the structural properties of the several antiviral drugs such as chloroquine, hydroxychloroquine, lopinavir, ritonavir, remdesivir, theaflavin, nafamostat, camostat, umifenovir and bevacizumab by considering the distance and bond measures of chemical compounds. Our quantitative values of the topological indices are extremely useful in the recent development of designing new drugs for COVID-19.

A generalization of the Hylleraas-Configuration Interaction method (Hy-CI) first proposed by Wang, et al., the Exponentially Correlated Hylleraas-Configuration Interaction method (E-Hy-CI) in which the single of an Hy-CI wave function is generalized to a form of the generic type , is explored. This type of correlation, suggested by Hirshfelder in 1960, has the right behavior both in the vicinity of the cusp as goes to 0 and as goes to infinity; this work explores whether wave functions containing both linear and exponential factors converge more rapidly than either one alone. The method of calculation of the two-electron E-Hy-CI kinetic energy and electron repulsion integrals in a stable and efficient way using recursion relations is discussed, and the relevant formulas are given. The convergence of the E-Hy-CI wave function expansion is compared with that of the Hy-CI wave function without exponential correlation factors, demonstrating both convergence acceleration and an improvement in the accuracy for the same basis. This makes the application of the E-Hy-CI method to systems with > 4, for which this formalism with at most a single factor per term leads to solvable integrals, very promising. E-Hy-CI method variational calculations with up to 10080 expansion terms are reported for the ground state of the neutral helium atom, with a resultant nonrelativistic energy of -2.9037 2437 7034 1195 9831 1084 hartree for the best expansion.

The unique-continuation property from sets of positive measure is here proven for the many-body magnetic Schrödinger equation. This property guarantees that if a solution of the Schrödinger equation vanishes on a set of positive measure, then it is identically zero. We explicitly consider potentials written as sums of either one-body or two-body functions, typical for Hamiltonians in many-body quantum mechanics. As a special case, we are able to treat atomic and molecular Hamiltonians. The unique-continuation property plays an important role in density-functional theories, which underpins its relevance in quantum chemistry.

In the modeling of spin-crossing reactions, it has become popular to directly explore the spin-adiabatic surfaces. Specifically, through constructing spin-adiabatic states from a two-state Hamiltonian (with spin-orbit coupling matrix elements) at each geometry, one can readily employ advanced geometry optimization algorithms to acquire a "transition state" structure, where the spin crossing occurs. In this work, we report the implementation of a fully-variational spin-adiabatic approach based on Kohn-Sham density functional theory spin states (sharing the same set of molecular orbitals) and the Breit-Pauli one-electron spin-orbit operator. For three model spin-crossing reactions [predissociation of NO, singlet-triplet conversion in CH, and CO addition to Fe(CO)], the spin-crossing points were obtained. Our results also indicated the Breit-Pauli one-electron spin-orbit coupling can vary significantly along the reaction pathway on the spin-adiabatic energy surface. On the other hand, due to the restriction that low-spin and high-spin states share the same set of molecular orbitals, the acquired spin-adiabatic energy surface shows a cusp (i.e. a first-order discontinuity) at the crossing point, which prevents the use of standard geometry optimization algorithms to pinpoint the crossing point. An extension with this restriction removed is being developed to achieve the smoothness of spin-adiabatic surfaces.

The role of Virtual Reality (VR) tools in molecular sciences is analyzed in this contribution through the presentation of the Caffeine software to the quantum chemistry community. Caffeine, developed at Scuola Normale Superiore, is specifically tailored for molecular representation and data visualization with VR systems, such as VR theaters and helmets. Usefulness and advantages that can be gained by exploiting VR are here reported, considering few examples specifically selected to illustrate different level of theory and molecular representation.

Models going beyond the rigid-rotor and the harmonic oscillator levels are mandatory for providing accurate theoretical predictions for several spectroscopic properties. Different strategies have been devised for this purpose. Among them, the treatment by perturbation theory of the molecular Hamiltonian after its expansion in power series of products of vibrational and rotational operators, also referred to as vibrational perturbation theory (VPT), is particularly appealing for its computational efficiency to treat medium-to-large systems. Moreover, generalized (GVPT) strategies combining the use of perturbative and variational formalisms can be adopted to further improve the accuracy of the results, with the first approach used for weakly coupled terms, and the second one to handle tightly coupled ones. In this context, the GVPT formulation for asymmetric, symmetric, and linear tops is revisited and fully generalized to both minima and first-order saddle points of the molecular potential energy surface. The computational strategies and approximations that can be adopted in dealing with GVPT computations are pointed out, with a particular attention devoted to the treatment of symmetry and degeneracies. A number of tests and applications are discussed, to show the possibilities of the developments, as regards both the variety of treatable systems and eligible methods.

The rapid growth of the available crystallographic information about proteins and binding pockets creates remarkable opportunities for enriching the drug research pipelines with computational prediction of novel protein-ligand interactions. While quantum mechanical approaches are known to provide unprecedented accuracy in structure-based binding energy calculations, they are limited to only small systems of dozens of atoms. In the structural chemogenomics era, it is critical that new approaches are developed that enable application of QM methodologies to non-covalent interactions in systems as large as protein-ligand complexes and conformational ensembles. This perspective highlights recent advances towards bridging the gap between high accuracy and high volume computations in drug research.

Ligands that activate the serotonin 5-HT G protein-coupled receptor (GPCR) may be therapeutic for psychoses, addiction, and other neuropsychiatric disorders. Ligands that are antagonists at the closely related 5-HT GPCR also may treat neuropsychiatric disorders; in contrast, 5-HT activation may cause hallucinations. 5-HT-specific agonist drug design is challenging because 5-HT GPCRs share 80% transmembrane (TM) homology, same second messenger signaling, and no crystal structures are reported. To help delineate molecular determinants underlying differential binding and activation of 5-HT GPCRs, 5-HT, and 5-HT homology models were built from the -adrenergic GPCR crystal structure and equilibrated in a lipid phosphatidyl choline bilayer performing molecular dynamics simulations. Ligand docking studies at the 5-HT receptor models were conducted with the (2, 4)- and (2, 4)-enantiomers of the novel 5-HT agonist/5-HT antagonist -4-phenyl--dimethyl-2-aminotetralin (PAT) and its 4'-chlorophenyl congners. Results indicate PAT-5-HT molecular interactions especially in TM domain V are important for the (2, 4) enantiomer, whereas, TM domain VI and VII interactions are more important for the (2, 4) enantiomer.

Activation of the serotonin (5-hydroxytryptamine, 5-HT) 5HT G protein-coupled receptor (GPCR) is proposed as novel pharmacotherapy for obesity and neuropsychiatric disorders. In contrast, activation of the 5-HT and 5-HT GPCRs is associated with untoward hallucinogenic and cardiopulmonary effects, respectively. There is no crystal structure available to guide design of 5-HT receptor-specific ligands. For this reason, a homology model of the 5-HT receptor was built based on the crystal structure of the human adrenoceptor GPCR to delineate molecular determinants of ligand-receptor interactions for drug design purposes. Computational and experimental studies were carried out to validate the model. Binding of N(CH)-PAT [(1, 3)-(-)--1-phenyl-3-,-dimethylamino-1,2,3,4-tetrahydronaphthalene], a novel 5-HT agonist/5-HT inverse agonist, and its secondary [NH(CH)-PAT] and primary (NH-PAT) amine analogs were studied at the 5-HT wild type (WT) and D3.32A, S3.36A, and Y7.43A 5-HT point-mutated receptors. Reference ligands included the tertiary amines lisuride and mesulergine and the primary amine 5-HT. Modeling results indicated that 5-HT residues D3.32, S3.36, and Y7.43 play a role in ligand binding. Experimental ligand binding results with WT and point-mutated receptors confirmed the impact of D3.32, S3.36, and Y7.43 on ligand affinity.

Additions of methylphenylsulfonium methylide onto chiral non-racemic N-sulfinyl imines (R'-SO-N=CH-R, R'=t-butyl, R=protected diol), followed by ring closure, yield terminal aziridines with high diastereoselectivity. Control reactions have established that both N- and C- iminyl substituents impact product preference, and when properly matched, one addition product is selected almost exclusively. Using solution-phase density functional computational methods, minima and transition state searches have been performed to reveal the structural origins of the diastereoselectivity. Our computational findings indicate that ring closure is fast and irreversible, and consequently, the relative energies of the transition states for the competing Re/Si addition steps determine the product diastereomeric ratios. Analysis of addition transition state structures reveals the causes of selectivity as arising from the N- and C- iminyl substituents, and we identify the S (R) configuration of the N-sulfinyl sulfur atom as the dominant director of Si (Re) addition. The control attributed to the sulfur configuration is tied to an important favorable internal interaction between the sulfinyl oxygen and the iminyl hydrogen. The protected diol acts as a secondary director, owing to steric/electrostatic interactions with the approaching ylide.

We presented a novel way to numerically characterize DNA sequences based on the graphical representation for the sequences comparison and analysis. Instead of calculating the leading eigenvalues of the matrix for graphical representation, we computed curvature and torsion of curves as the descriptor to numerically characterize DNA sequences. The new method was tested on three data sets: the coding sequences of β-globin gene, all of their exons, and 24 coronavirus geneomes from NCBI. The similarities/dissimilarities and phylogenetic tree of these species verify the validity of our method. © 2010 Wiley Periodicals, Inc. Int J Quantum Chem, 2011.

We investigate the post-translational generation of Gla (γ-carboxy glutamic acid) from Glu (glutamic acid) by vitamin K carboxylase (VKC) in solvent. VKC is thought to convert vitamin K, in the vitamin K cycle, to an alkoxide-epoxide form, which then reacts with CO(2) to generate an essential ingredient in blood coagulation, γ-carboxyglutamic acid (Gla). The generation of Gla from Glu is found to be exergenic (-15 kcal/mol) in aqueous solution with the SM6 method. We also produced the free energy profile for this model biochemical process with other solvent methods (polarizable continuum model, dielectric polarizable continuum model) and different dielectric constants. The biological implications are discussed.

In the current work, we found aqueous enzyme phase reaction pathways for the reactivation of the exogenously inhibited [Fe-Fe]-hydrogenases by O, or OH, which metabolizes to HO. We used the hybrid quantum mechanics/molecular mechanics (QM/MM) method to study the reactivation pathways of the exogenously inhibited enzyme matrix. The ONIOM calculations performed on the enzyme agree with experimental results, i.e., wild-type [Fe-Fe]-hydrogenase H-cluster is inhibited by oxygen metabolites. An enzyme spherical region with a radius of 8 Å (from the distal iron, Fe) has been screened for residues that prevent HO from leaving the catalytic site and reactivate the [Fe-Fe]-hydrogenase H-cluster. In the screening process, polar residues were removed, one at a time, and frequency calculations provided the change in the Gibbs' energy for the dissociation of water (due to their deletion). When residue deletion resulted in significant Gibbs' energy decrease, further residue substitutions have been carried out. Following each substitution, geometry optimization and frequency calculations have been performed to assess the change in the Gibbs' energy for the elimination HO. Favorable thermodynamic results have been obtained for both single residue removal (ΔG = -1.6 kcal/mol), single substitution (ΔG = -3.1 kcal/mol), and combined residue substitutions (ΔG = -7.5 kcal/mol). Because the wild-type enzyme has only an endergonic step to overcome, i.e., for HO removal, by eliminating several residues, one at a time, the endergonic step was made to proceed spontaneously. Thus, the most promising residue deletions which enhance HO elimination are ΔArg, ΔThr, ΔSer, ΔGlu, ΔGlu, and ΔTyr. The thermodynamics and electronic structure analyses show that the bridging carbonyl (CO) of the H-cluster plays a concomitant role in the enzyme inhibition/reactivation. In gas phase, CO shifts towards Fe to compensate for the electron density donated to oxygen upon the elimination of HO. However, this is not possible in the wild-type enzyme because the protein matrix hinders the displacement of CO towards Fe, which leads to enzyme inhibition. However, enzyme reactivation can be achieved by means of appropriate amino acid substitutions.

[Fe-Fe]-hydrogenases are enzymes that reversibly catalyze the reaction of protons and electrons to molecular hydrogen, which occurs in anaerobic media. In living systems, [Fe-Fe]-hydrogenases are mostly used for H(2) production. The [Fe-Fe]-hydrogenase H-cluster is the active site, which contains two iron atoms. The latest theoretical investigations1,2 advocate that the structure of di-iron air inhibited species are either Fe(p) (II)-Fe(d) (II)-O-H(-), or Fe(p) (II)-Fe(d) (II)-O-O-H, thus O(2) has to be prevented from binding to Fe(d) in all di-iron subcluster oxidation states in order to retain a catalytically active enzyme. By performing residue mutations on [Fe-Fe]-hydrogenases, we were able to weaken O(2) binding to distal iron (Fe(d)) of Desulfovibrio desulfuricans hydrogenase (DdH). Individual residue deletions were carried out in the 8 A apoenzyme layer radial outward from Fe(d) to determine what residue substitutions should be made to weaken O(2) binding. Residue deletions and substitutions were performed for three di-iron subcluster oxidation states, Fe(p) (II)-Fe(d) (II), Fe(p) (II)-Fe(d) (I), and Fe(p) (I)-Fe(d) (I) of [Fe-Fe]-hydrogenase. Two deletions (DeltaThr(152) and DeltaSer(202)) were found most effective in weakening O(2) binding to Fe(d) in Fe(p) (II)-Fe(d) (I) hydrogenase (DeltaG(QM/MM) = +5.4 kcal/mol). An increase in Gibbs' energy (+2.2 kcal/mol and +4.4 kcal/mol) has also been found for Fe(p) (II)-Fe(d) (II), and Fe(p) (I)-Fe(d) (I) hydrogenase respectively. pi-backdonation considerations for frontier molecular orbital and geometrical analysis corroborate the Gibbs's energy results.

The nudged elastic band method (NEB) can be used to find a minimum energy path between two given starting structures. This method has been available in the standard release of the Amber9 and Amber10 suite of programs. In this paper a novel implementation of this method will be discussed, in which the nudged elastic band method is applied to only a specific, user-defined subset of atoms in a particular system, returning comparable results and minimum energy pathways as the standard implementation for an alanine dipeptide test system. This allows incorporation of explicit solvent with simulated systems, which may be preferred in many cases to an implicit solvent model. From a computational standpoint, this implementation of NEB also reduces the communication overhead inside the code, resulting in better performance for larger systems.

The oxidation of H-cluster in gas phase, and in aqueous enzyme phase, has been investigated by means of quantum mechanics (QM) and combined quantum mechanics-molecular mechanics (QM/MM). Several potential reaction pathways (in the above mentioned chemical environments) have been studied, wherein only the aqueous enzyme phase has been found to lead to an inhibited hydroxylated cluster. Specifically, the inhibitory process occurs at the distal iron (Fe(d)) of the catalytic H-cluster (which is also the atom involved in H(2) synthesis). The processes involved in the H-cluster oxidative pathways are O(2) binding, e(-) transfer, protonation, and H(2)O removal.We found that oxygen binding is non-spontaneous in gas phase, and spontaneous for aqueous enzyme phase where both Fe atoms have oxidation state II; however, it is spontaneous for the partially oxidized and reduced clusters in both phases. Hence, in the protein environment the hydroxylated H-cluster is obtained by means of completely exergonic reaction pathway starting with proton transfer.A unifying endeavor has been carried out for the purpose of understanding the thermodynamic results vis-à-vis several other performed electronic structural methods, such as frontier molecular orbitals (FMO), natural bond orbital partial charges (NBO), and H-cluster geometrical analysis. An interesting result of the FMO examination (for gas phase) is that an e(-) is transferred to LUMO(alpha) rather than to SOMO(beta), which is unexpected because SOMO(beta) usually resides in a lower energy rather than LUMO(alpha) for open-shell clusters.