Quantum Chemical Interaction Research Articles

Understanding solid nitrogen through molecular dynamics simulations with a machine-learning potential

We construct a fast, transferable, general purpose, machine-learning interatomic potential suitable for large-scale simulations of N2. The potential is trained only on high quality quantum chemical molecule-molecule interactions; no condensed phase information is used. Although there are no explicit or implicit many-molecule interaction terms, the potential reproduces the experimental phase diagram including the melt curve and the molecular solid phases of nitrogen up to 10GPa. This demonstrates that many-molecule interactions are unnecessary to explain the condensed phases of N2. With increased pressure, transitions are observed from cubic (α), which optimizes quadrupole-quadrupole interactions, through tetragonal (γ), which allows more efficient packing, to monoclinic (λ), which packs still more efficiently. On heating, we obtain the hcp three-dimensional (3D) rotor phase (β) and, at pressure, the cubic δ phase which contains both 3D and 2D rotors, tetragonal δ* phase with 2D rotors, and the rhombohedral ε. Molecular dynamics demonstrates where these phases are indeed rotors, rather than frustrated order. The model supports the metastability of the complex ι phase, but not the reported existence of the wide range of bond lengths. The thermodynamic transitions involve both shifts of molecular centers and rotations of molecules: the onset of rotation is rapid, whereas motion of molecular centers is inhibited and we suggest that this is the cause of the experimentally observed sluggishness of transitions. Routine density functional theory calculations give a similar picture to the potential. Published by the American Physical Society 2024

A quantum chemical interaction energy dataset for accurately modeling protein-ligand interactions

Fast and accurate calculation of intermolecular interaction energies is desirable for understanding many chemical and biological processes, including the binding of small molecules to proteins. The Splinter [“Symmetry-adapted perturbation theory (SAPT0) protein-ligand interaction”] dataset has been created to facilitate the development and improvement of methods for performing such calculations. Molecular fragments representing commonly found substructures in proteins and small-molecule ligands were paired into >9000 unique dimers, assembled into numerous configurations using an approach designed to adequately cover the breadth of the dimers’ potential energy surfaces while enhancing sampling in favorable regions. ~1.5 million configurations of these dimers were randomly generated, and a structurally diverse subset of these were minimized to obtain an additional ~80 thousand local and global minima. For all >1.6 million configurations, SAPT0 calculations were performed with two basis sets to complete the dataset. It is expected that Splinter will be a useful benchmark dataset for training and testing various methods for the calculation of intermolecular interaction energies.

A DFT study on 2X- imidazole derivatives (X = OH, NH2, and SH) as corrosion inhibitors on Cu surfaces: Tautomerism effect

Adsorption of different tautomers of 2-hydroxy, 2-amino, and 2-mercapto imidazole as corrosion inhibitors on the (1 1 1), (1 1 0), and (1 0 0) copper surfaces in parallel and perpendicular modes are compared and evaluated by the DFT approach. Among different tautomers, imidazole with thiol, thione, and 1 H-imidazole-2-amine in imine form exhibited the best inhibition efficiency. Also, the quantum chemical descriptors and interaction energy magnitudes, as well as PDOSs, were calculated and used to evaluation of the interaction of organic molecules with the copper surfaces. In addition, Cu (1 1 0) showed the best protection in combination with imidazole derivatives.

Quantum Chemical Interaction Analysis between SARS-CoV-2 Main Protease and Ensitrelvir Compared with Its Initial Screening Hit.

A non-covalent oral drug targeting SARS-CoV-2 main protease (Mpro), ensitrelvir (Xocova), has been developed using structure-based drug design (SBDD). To elucidate the factors responsible for enhanced inhibitory activities from an in silico screening hit compound to ensitrelvir, we analyzed the interaction energies of the inhibitors with each residue of Mpro using fragment molecular orbital (FMO) calculations. This analysis reveals that functional group conversion for P1' and P1 parts in the inhibitors increases the strength of existing interactions with Mpro and also provides novel interactions for ensitrelvir; the associated changes in the conformation of Mpro induce further interactions for ensitrelvir in other parts, including hydrogen bonds, a halogen bond, and π-orbital interactions. Thus, we illuminate the promising strategies of SBDD for leading ensitrelvir to get higher activity against Mpro by elucidating microscopic interactions through FMO-based analysis. These detailed mechanism findings, including water cross-linkings, will help to design novel inhibitors in SBDD.

A network of hydrogen bonds in the lattice of heavy atoms of single crystals of the KDP group: quantum nature of dipole interactions

In the work presented, the distinctive features of temperature behavior of dielectric permittivity ε, dielectric loss tangent tanδ and pyroelectric coefficient γ of classical ferroelectric KDP and crystals of its family, which have a network of strong OH…O hydrogen bonds, are discussed. Particular attention is focused on the evidence of quantum-chemical interactions in network of hydrogen bonds in the matrix of heavy nuclei.

Quantitative Structure-Activity Relationship (QSAR) modelling of the activity of anti-colorectal cancer agents featuring quantum chemical predictors and interaction terms

A Quantitative Structure-Activity Relationship (QSAR) study was performed to 1) predict the activity of new compounds as anti-colorectal cancer agents and 2) select chemical predictors that accurately model relationships between molecular structures and bioactivity against colon cancer cell lines. Logistic regression was used to obtain coefficients for the QSAR classification model. Quantum chemical predictors were found to be significant predictors, such as the total electronic energy (ET), charge of the most positive atom (Qmax) and electrophilicity (ω), thus validating the need to consider them besides those routinely used in anti-colorectal cancer agents QSAR. The model selected simple and significant predictors that can be obtained directly using information from gaseous-state Gaussian optimisation at HF/3-21G in a vacuum, with no external calculation software, providing an inexpensive yet robust QSAR model. In addition, two interaction terms were proven to be significant at 95 % confidence level, reiterating the importance of interaction between predictors that is not commonly seen in QSAR models.

Influence of Water on the Quantum Chemical Interactions in Coal Flotation

Influence of Water on the Quantum Chemical Interactions in Coal Flotation

Химические свойства и электронная структура пленок оксисульфидов молибдена для перспективных фотоэлектрокатализаторов получения водорода

The effect of sulfur and oxygen concentrations on the formation of chemical bonds in films based on the ternary compound Mo – S – O, which is of interest for solving the problem of obtaining effective thin-film catalysts for electrochemical, especially photo-activated, water splitting reaction, has been studied. The films were created by pulsed laser deposition in a mixture of gases (argon and oxygen) at room temperature of the substrate. Factors that have an important effect on the position of the Fermi level in the band gap of a ternary compound are revealed, which largely determines the choice of components in hybrid and heterostructures for photoelectrodes. The change in the chemical state of Mo – S – O films in the electrochemical process of hydrogen evolution in an acid solution has been studied. Character of changes in the local packing of atoms (self-organization) are revealed, manifested in a decrease in the concentration of metal oxide clusters and an increase in the concentration of Mo – S clusters on the surface of such films. The thermodynamic analysis which was carried out using the density functional theory showed that when oxygen is removed from the surface of Mo – S – O films and, as a result, the hybrid structure MoSx/(Mo – S – O) is formed, the efficiency of hydrogen evolution can be controlled by the quantum chemical interaction of different clusters. In this case, only certain combinations of clusters can provide a sufficiently high catalytic activity.

σ-Donation and π-Backdonation Effects in Dative Bonds of Main-Group Elements.

The nature of donor-acceptor interactions is important for the understanding of dative bonding and can provide vital insights into many chemical processes. Here, we have performed a computational study to elucidate substantial differences between different types of dative interactions. For this purpose, a data set of 20 molecular complexes stabilized by dative bonds was developed (DAT20). A benchmark study that considers many popular density functionals with respect to accurate quantum chemical interaction energies and geometries revealed two different trends between the complexes of DAT20. This behavior was further explored by means of frontier molecular orbitals, extended-transition-state natural orbitals for chemical valence (ETS-NOCV), and natural energy decomposition analysis (NEDA). These methods revealed the extent of the forward and backdonation between the donor and acceptor molecules and how they influence the total interaction energies and molecular geometries. A new classification of dative bonds is suggested.

Imidazole derivatives as corrosion inhibitors for copper: A DFT and reactive force field study

We have investigated the corrosion inhibition mechanisms of imidazole, adenine, purine and 6-benzylaminopurine for copper using density functional theory (DFT) and reactive force fields (ReaxFF). The computed quantum chemical descriptors and interaction energy magnitudes correlate well with the experimental corrosion inhibition efficiencies: BAP > Adenine > Purine > Imidazole. The optimized geometries indicate formation of strong chemical bonds between surface Cu-atoms and N-atoms of the adsorbed molecules. This work shows the tremendous potential of ReaxFF calculations in successfully modeling adsorption of inhibitor molecules on metal surfaces at much lower computational costs compared to DFT.

Hierarchies of quantum chemical descriptors induced by statistical analyses of domain occupation number operators

AbstractAs approximations to the wave functions governing quantum chemical systems become more and more complex, it is becoming increasingly important to devise descriptors that help understand the practical results of those approximations by condensing information in insightful ways. Quantum chemical descriptors that are able to capture the statistical signatures of quantum chemical interactions provide such conceptual building blocks. Central to an understanding of these descriptors is the concept of a “domain occupation number operator,” which allows the so‐called “real space” and Hilbert space partitionings to be treated on the same footing. Many of the existing descriptors can be expressed as the (central) densities and density cumulants associated with the domain operators. These densities can be obtained by successive differentiation of generating functions, effectively structuring domain associated densities into hierarchies. Not only do the resulting hierarchies indicate how many of the previously reported descriptors are related, they also show which areas have not yet been explored.This article is categorized under:Electronic Structure Theory > Ab Initio Electronic Structure Methods

Electrostatics and polarization determine the strength of the halogen bond: a red card for charge transfer

A series of 20 halogen bonded complexes of the types R–Br•••Br− (R is a substituted methyl group) and R´–C≡C–Br•••Br− are investigated at the M06-2X/6–311+G(d,p) level of theory. Computations using a point-charge (PC) model, in which Br− is represented by a point charge in the electronic Hamiltonian, show that the halogen bond energy within this set of complexes is completely described by the interaction energy (ΔEPC) of the point charge. This is demonstrated by an excellent linear correlation between the quantum chemical interaction energy and ΔEPC with a slope of 0.88, a zero intercept, and a correlation coefficient of R2 = 0.9995. Rigorous separation of ΔEPC into electrostatics and polarization shows the high importance of polarization for the strength of the halogen bond. Within the data set, the electrostatic interaction energy varies between 4 and −18 kcal mol–1, whereas the polarization energy varies between −4 and −10 kcal mol–1. The electrostatic interaction energy is correlated to the sum of the electron-withdrawing capacities of the substituents. The polarization energy generally decreases with increasing polarizability of the substituents, and polarization is mediated by the covalent bonds. The lower (more favorable) ΔEPC of CBr4---Br− compared to CF3Br•••Br− is found to be determined by polarization as the electrostatic contribution is more favorable for CF3Br•••Br−. The results of this study demonstrate that the halogen bond can be described accurately by electrostatics and polarization without any need to consider charge transfer.

Chalcogen Bonding in Protein-Ligand Complexes: PDB Survey and Quantum Mechanical Calculations.

A chalcogen bond is a nonclassical noncovalent interaction which can stabilise small-molecule crystals as well as protein structures. Here, we systematically explore the stabilising potential of chalcogen bonding in protein-ligand complexes in the Protein Data Bank (PDB). We have found that a large fraction (23 %) of complexes with a S/Se-containing ligand feature close S/Se⋅⋅⋅O/N/S contacts. Eleven non-redundant representative potential S/Se⋅⋅⋅O chalcogen-bond motifs were selected and truncated to model systems and seven more model systems were prepared by S-to-Se substitution. These systems were then subjected to analysis by quantum chemical (QM) methods-electrostatic potential, geometry optimisation or interaction energy calculations, including solvent effects. The QM calculations indicate that chalcogen bonding does indeed play a dominant role in stabilising some of the interaction motifs studied. We thus advocate further exploration of chalcogen bonding with the aim of potential future use in structure-based drug design.

Hierarchy of the Collective Effects in Water Clusters.

The results of dipole moment as well as of intra- and intermolecular bond order calculations indicate the big importance of collective electrostatic effects caused by the nonimmediate environment in liquid water models. It is also discussed how these collective effects are built up as consequences of the electrostatic and quantum chemical interactions in water clusters.

Drug Discovery of β-Secretase Inhibitors Based on Quantum Chemical Interactions for the Treatment of Alzheimer's Disease

Alzheimer’s disease, which is the most common cause of dementia, is characterized by progressive intellectual deterioration. According to the amyloid hypothesis, a transmembrane aspartic protease, β-secretase (BACE1), is a promising molecular target for development anti-Alzheimer drugs. This protease triggers amyloid β (Aβ) formation, which is involved in the development of Alzheimer’s disease. Many research groups have shown various BACE1 inhibitors to be efficacious in the treatment of Alzheimer’s disease. Given the fact that Swedish-mutant amyloid precursor protein (APP) is cleaved faster than wild-type APP, early BACE1 inhibitors were designed on the basis of the Swedish-mutant APP amino acid sequence and possess a substrate transition-state analogue. At an early stage of this research, we also reported a series of peptidic BACE1 inhibitors possessing a substrate transition-state analogue. Subsequently, nonpeptidic BACE1 inhibitors were designed using the peptidic inhibitors as lead compounds and an in-silico conformational structure-based drug design approach. These inhibitors showed potent inhibitory activities. Among these, some inhibitors exhibited effective BACE1 inhibition in cultured cells and significant reduction of Aβ production in vivo. In the process, we found that a quantum chemical interaction between the inhibitors and an arginine side chain at the active site of BACE1 plays a crucial role in the mechanism of BACE1 inhibition. In fact, out of the publicly available X-ray crystal structures of BACE1-inhibitor complexes, most interact with the Arg235 side chain of BACE1 by a quantum chemical interaction. It is known that quantum chemical interactions involving an arginine side chain play an important role in molecular recognition in proteins. Hence, a series of potent BACE1 inhibitors that were optimized to focus on the quantum chemical interaction with the arginine side chain of BACE1 were designed. Furthermore, based on these quantum chemical interactions, we proposed a novel concept in medicinal science, the electron donor/acceptor bioisostere. Although the bioisostere is an important concept in the design of practical drugs, the classical bioisostere concept does not assume interactions by such quantum chemical effects. This review describes our peptidic BACE1 inhibitors produced using substrate-based design and non-peptidic BACE1 inhibitors produced using structure-based design approaches. Subsequently, the significance of quantum chemical interaction in medicinal chemistry is discussed, and potent small-sized BACE1 inhibitors and the first peptides with BACE1 inhibitory activities, which were designed based on quantum chemical interactions, are described.

Critic2: A program for real-space analysis of quantum chemical interactions in solids

We present critic2, a program for the analysis of quantum-mechanical atomic and molecular interactions in periodic solids. This code, a greatly improved version of the previous critic program (Otero-de-la Roza et al., 2009), can: (i) find critical points of the electron density and related scalar fields such as the electron localization function (ELF), Laplacian, … (ii) integrate atomic properties in the framework of Bader’s Atoms-in-Molecules theory (QTAIM), (iii) visualize non-covalent interactions in crystals using the non-covalent interactions (NCI) index, (iv) generate relevant graphical representations including lines, planes, gradient paths, contour plots, atomic basins, … and (v) perform transformations between file formats describing scalar fields and crystal structures. Critic2 can interface with the output produced by a variety of electronic structure programs including WIEN2k, elk, PI, abinit, Quantum ESPRESSO, VASP, Gaussian, and, in general, any other code capable of writing the scalar field under study to a three-dimensional grid. Critic2 is parallelized, completely documented (including illustrative test cases) and publicly available under the GNU General Public License. Program summaryProgram title: CRITIC2Catalogue identifier: AECB_v2_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AECB_v2_0.htmlProgram obtainable from: CPC Program Library, Queen’s University, Belfast, N. IrelandLicensing provisions: yesNo. of lines in distributed program, including test data, etc.: 11686949No. of bytes in distributed program, including test data, etc.: 337020731Distribution format: tar.gzProgramming language: Fortran 77 and 90.Computer: Workstations.Operating system: Unix, GNU/Linux.Has the code been vectorized or parallelized?: Shared-memory parallelization can be used for most tasks.Classification: 7.3.Catalogue identifier of previous version: AECB_v1_0Journal reference of previous version: Comput. Phys. Comm. 180 (2009) 157Nature of problem:Analysis of quantum-chemical interactions in periodic solids by means of atoms-in-molecules and related formalisms.Solution method:Critical point search using Newton’s algorithm, atomic basin integration using bisection, qtree and grid-based algorithms, diverse graphical representations and computation of the non-covalent interactions index on a three-dimensional grid.Additional comments:!!!!! The distribution file for this program is over 330 Mbytes and therefore is not delivered directly when download or Email is requested. Instead a html file giving details of how the program can be obtained is sent. !!!!!Running time:Variable, depending on the crystal and the source of the underlying scalar field.

The Significance of Quantum Chemical Interactions for Medicinal Science and Design of β-Secretase Inhibitors

This review discusses the importance of quantum chemical interactions in biomolecules for medicinal science and their relevance to the author's β-secretase (BACE1) inhibitor drug discovery research. Although molecular mechanics/dynamics (MM/MD) methods are available in many in silico design tools used for drug discovery, they cannot accurately evaluate quantum effects between biomolecules and drugs. The key roles of biomolecular quantum chemical interactions in drug discovery are discussed using the arginine side chain as an example. Arginine is recognized as a charged amino acid in commonly used drug design software, unlike other amino acids with π-electron orbitals, such as phenylalanine, tyrosine, and tryptophan. Quantum chemical interactions via the arginine side chain are crucial for molecular recognition, and are found in many X-ray crystal structures, such as protein-protein, protein homodimer, RNA aptamer-protein, and enzyme-inhibitor complexes. This review describes the essential role of quantum chemical interactions via the arginine side chain in the mechanism of BACE1 inhibition, and proposes an "electron donor/acceptor bioisostere" concept for medicinal science based on quantum chemical interactions. Several potent BACE1 inhibitors, as well as the first peptides with BACE1 inhibiting activity were designed and synthesized based on studies of quantum chemical interactions via arginine side chain and the "electron donor bioisostere" concept.

Quantum Size Effects in the Optical Properties of Ligand Stabilized Aluminum Nanoclusters

Here we describe an approach to the synthesis of small ligand stabilized Al nanoclusters by catalytic decomposition of alane using Ti(OiPr)4 as catalyst. The selected area electron diffraction (SAED) and elemental analysis are consistent with the presence of Al in the clusters. The cluster sizes are measured by the small-angle X-ray scattering method in air-free conditions. The absorption maximum exhibits red shifts when cluster sizes decrease from 4 to 1.5 nm. A two-layer Mie theory model indicates that the electron conductivity in the Al core is reduced due to a combination of quantum size effects and chemical interaction with the ligand shell resulting in the observed red shift with decreasing size. The red shift is shown to scale with the inverse radius in good agreement with a spill-out model. Furthermore, the results are consistent with time-dependent density functional simulations for a small ligand stabilized Al cluster. Remarkably, we find that the absorption maximum is significantly red-shifted ...

Kernel energy method applied to an energetic nitrate ester

AbstractA recent synthesis results in a nitrate ester explosive C6N6O16H8 (Hisk75), composed of four nitrate ester groups (ONO2) and two nitro groups (NO2), with the property of being solid at room temperature with a low‐melting point allowing the convenience of poured mold casting (Chavez et al., Angew Chem Int Ed 2008, 47, 8307). Using the crystal geometry, we have calculated the quantum chemical interaction energies, including basis set superposition errors between nearest neighboring molecules. Using quantum mechanics and the computer program CHEETA, we have calculated the explosive parameters of this new molecule, comparing to those of HMX, corroborating previous estimates of these same parameters. Calculations confirm this compound to be one of the best performing high‐energy/high‐density explosives. © 2010 Wiley Periodicals, Inc. Int J Quantum Chem, 2011

Further evaluation of quantum chemical methods for the prediction of non-specific binding of positron emission tomography tracers

The non-specific binding of candidate positron emission tomography (PET) radiotracers causes resulting PET images to have poor contrast and is a key determinant for the success or failure of imaging drugs. Non-specific binding is thought to arise when radiotracers bind to cell membranes and moieties other than their intended target. Our previous preliminary work has proposed the use of the drug-lipid interaction energy descriptor to predict the level of non-specific binding in vivo using a limited set of ten well known PET radiotracers with kinetic modelling data taken from the literature. This work validates and extends the use of the drug-lipid interaction energy descriptor using a new set of twenty-two candidate PET radiotracers with non-specific binding data recently collected at the same imaging centre with consistent methodology. As with the previous set of radiotracers, a significant correlation is found between the quantum chemical drug-lipid interaction energy and in vivo non-specific binding experimental values. In an effort to speed up the calculation process, several semi-empirical quantum chemical methods were assessed for their ability to reproduce the ab initio results. However no single semi-empirical method was found to consistently reproduce the level of correlation achieved with ab initio quantum chemical methods.