Atomic Contributions Research Articles

A comparative analysis of UV–vis transitions in hetaryl and ferrocenyl thioketones

Electronic transitions in a series of symmetrical and nonsymmetrical hetaryl- and/or ferrocenyl-functionalized thioketones have been studied using quantum chemistry methods. An in-depth theoretical characterization was carried out for low-energy electronic transitions. The effects of hetaryl and ferrocenyl groups on the energy of these transitions were recognized and elucidated in terms of atomic and molecular orbital contributions involved in the transitions. A comparison was drawn between the low-energy transitions in the thioketones and in their carbonyl counterparts. The effect of solvents on the position of UV–vis absorption bands, in particular, on those originating in the low-energy transitions, is discussed. The theoretical calculations indicate that the introduction of ferrocenyl group into the hetaryl-functionalized thioketones changes the character of their first two electronic transitions from n → π* and π → π* into dominant d → π*. The most intense band of all studied thioketones appears in the near-UV region and undergoes a redshift upon solvation.

Planar σ-Aromaticity in Ga-Doped Au Clusters

Recently, the first example of Au-Ga clusters is synthesized and characterized, which can be described by the jellium model as a superatom with 8 valence electrons that come from the joint contribution of Au and Ga atoms, opening a whole new field for further research. Here, the structure features and stability of one Ga-doped Au cluster with magic number electrons (6 and 8) are analyzed in detail. Moreover, the valence electron fillings and chemical bonding of them are also further explored. It is found that Au3Ga and Au5Ga clusters present planar configurations, and they have higher stability than that of neighbor clusters. The AIMD simulations show that these two clusters still have a good thermal stability at 500 K. The molecular orbital analyses show that the Au3Ga and Au5Ga have three and one typical delocalization orbital throughout the whole planar spaces, respectively, following the planar σ-aromaticity rule. The ELF and LOL analyses are further performed, and the results are consistent with the molecular orbital analyses. The NICSzz-scan curves confirm that the Au3Ga is more aromatic than the Au5Ga, and the reason is that the former has more delocalized electrons than the latter. Our work opens up aromaticity studies in the Au-Ga clusters.

Theoretical survey on the electronic, linear and nonlinear optical properties of substituted benzenes and polycondensed π-systems. A density functional theory study

Herein dipole moments, static and dynamic (hyper)polarizabilities, delocalization energies, distortions of the phenyl rings of the substituted benzenes are computed using density functional theory procedure. It is revealed that the biphenyl molecule exhibits the largest frequency-dependent second order hyperpolarizabilities. Furthermore, the application of an external electric field along the direction parallel to the molecular plane induces a considerable decrease in the energy of the unoccupied orbitals of biphenyl, resulting in more red-shifted virtual orbitals compared with benzene and the highest static second-order hyperpolarizability for the molecule. It is also found that when the two adjacent rings share only one carbon atom, high σ and π-electronic contributions to the second-order hyperpolarizabilities are expected. Interactions of the type π* → π* with high delocalization energies are predicted for pyridine, nitrobenzene, chlorobenzene, bromobenzene, phenol, and benzoic acid. The quantum–mechanical calculations of the present work may provide theoretical insights into designing high (hyper)polarizability materials.

Decomposing Chemical Space: Applications to the Machine Learning of Atomic Energies.

We apply a number of atomic decomposition schemes across the standard QM7 data set─a small model set of organic molecules at equilibrium geometry─to inspect the possible emergence of trends among contributions to atomization energies from distinct elements embedded within molecules. Specifically, a recent decomposition scheme of ours based on spatially localized molecular orbitals is compared to alternatives that instead partition molecular energies on account of which nuclei individual atomic orbitals are centered on. We find these partitioning schemes to expose the composition of chemical compound space in very dissimilar ways in terms of the grouping, binning, and heterogeneity of discrete atomic contributions, e.g., those associated with hydrogens bonded to different heavy atoms. Furthermore, unphysical dependencies on the one-electron basis set are found for some, but not all of these schemes. The relevance and importance of these compositional factors for training tailored neural network models based on atomic energies are next assessed. We identify both limitations and possible advantages with respect to contemporary machine learning models and discuss the design of potential counterparts based on atoms and the intrinsic energies of these as the principal decomposition units.

Americium Oxalate: An Experimental and Computational Investigation of Metal-Ligand Bonding.

A novel actinide-containing coordination polymer, [Am(C2O4)(H2O)3Cl] (Am-1), has been synthesized and structurally characterized. The crystallographic analysis reveals that the structure is two-dimensional and comprised of pseudo-dimeric Am3+ nodes that are bridged by oxalate ligands to form sheets. Each metal center is nine-coordinate, forming a distorted capped square antiprism geometry with a C1 symmetry, and features bound oxalate, aqua, and chloro ligands. The Am3+-ligand bonds were probed computationally using the quantum theory of atoms in molecules nd natural localized molecular orbital approaches to investigate the underlying mechanisms and hybrid atomic orbital contributions therein. The analyses indicate that the bonds within Am-1 are predominantly ionic and the 5f shell of the Am3+ metal centers does not add a significant covalent contribution to the bonds. Our bonding assessment is supported by measurements on the optical properties of Am-1 using diffuse reflectance and photoluminescence spectroscopies. The position of the principal absorption band at 507 nm (5L6' ← 7F0') is notable because it is consistent with previously reported americium oxalate complexes in solution, indicating similarities in the electronic structure and ionic bonding. Compound Am-1 is an active phosphor, featuring strong bright-blue oxalate-based luminescence with no evidence of metal-centered emission.

Exploring the Non-Covalent Bonding in Water Clusters.

QTAIM and source function analysis were used to explore the non-covalent bonding in twelve different water clusters (H2O)n obtained by considering n = 2-7 and various geometrical arrangements. A total of seventy-seven O-H⋯O hydrogen bonds (HBs) were identified in the systems under consideration, and the examination of the electron density at the bond critical point (BCP) of these HBs revealed the existence of a great diversity of O-H⋯O interactions. Furthermore, the analysis of quantities, such as |V(r)|/G(r) and H(r), allowed a further description of the nature of analogous O-H⋯O interactions within each cluster. In the case of 2-D cyclic clusters, the HBs are nearly equivalent between them. However, significant differences among the O-H⋯O interactions were observed in 3-D clusters. The assessment of the source function (SF) confirmed these findings. Finally, the ability of SF to decompose the electron density (ρ) into atomic contributions allowed the evaluation of the localized or delocalized character of these contributions to ρ at the BCP associated to the different HBs, revealing that weak O-H⋯O interactions have a significant spread of the atomic contributions, whereas strong interactions have more localized atomic contributions. These observations suggest that the nature of the O-H⋯O hydrogen bond in water clusters is determined by the inductive effects originated by the different spatial arrangements of the water molecules in the studied clusters.

Molecular electrostatics and pKa shifts calculations with the Generalized Born model. A tutorial through examples with Bluues2

Biomolecular electrostatics is of key importance for biological function and recognition. The continuum electrostatic model based on the Poisson-Boltzmann (PB) equation has been widely used to study biomolecular electrostatics. The solution of the PB equation gives the electrostatic potential over the space enclosing the molecule(s) of interest, typically obtained at points of a suitable grid.The Generalized Born (GB) model has been used to provide a useful approximation to the solution obtained by solving numerically the PB equation. The main advantage of the GB approach is to express the electrostatic energy of the system as the sum of pairwise interactions. The latter depend on geometric parameters (the GB radii) which depend on all atoms, and their radii, of the system. In this work we present a tutorial through examples for a more efficient and general version of the program Bluues which is able to compute:1) the generalized Born radius of each atom;2) the electrostatic potential at the surface of the molecule mapped to solvent accessible atoms;3) the solvent accessible surface in a PDB formatted file;4) the electrostatic potential in the volume surrounding the molecule;5) the electrostatic free energy and different contributions to it;6) the pH-dependent properties of proteins (total charge and pH-dependent free energy of folding) in the pH range −4 to 18;7) the pKa shifts due to molecular structure of all ionizable groups. Program summaryProgram Title: bluues2CPC Library link to program files:https://doi.org/10.17632/bx98gcrzbg.1Developer's repository link:https://github.com/federico-fogolari/bluues2Code Ocean capsule:https://codeocean.com/capsule/9338710Licensing provisions: GPLv3Programming language: CNature of problem: Biomolecular electrostatics is of key importance for biological function and recognition. Computation of electrostatic effects and their dissection in atomic contributions is a general problem in molecular modeling.Solution method: The GBR6 version of the Generalized Born (GB) model is implemented through surface integrals and all common molecular electrostatic analyses are performed by a single command line program.Additional comments including restrictions and unusual features: The program requires, as input, files in pqr format, which may be generated by independent software (e.g. babel, pdb2pqr). For the optional generation of the solvent excluded surface, the software msms must be installed and present in the path.

Plasma Parameters and Kinetics of Reactive Ion Etching of SiO2 and Si3N4 in an HBr/Cl2/Ar Mixture

The parameters of the gas phase and the kinetics of reactive ion etching of SiO2 and Si3N4 under conditions of an induction RF (13.56 MHz) discharge with a varying HBr/Cl2 ratio is studied. The study includes plasma diagnostics using Langmuir probes, plasma modeling to find stationary concentrations of active particles, measuring velocities, and analyzing etching mechanisms in the effective interaction prob-ability approximation. It is found that the substitution of HBr by Cl2 at a constant argon content (a) is accompanied by a noticeable change in the electrical parameters of the plasma; (b) leads to a weak increase in the intensity of ion bombardment of the treated surface; and (c) causes a significant increase in the total concentration and flux density of reactive particles. It is shown that the etching rates of SiO2 and Si3N4 increase monotonically as the proportion of Cl2 increases in a mixture, while the main etching mechanism is an ion-stimulated chemical reaction. The model description of the kinetics of such a reaction in the first approximation assumes (a) the additive contribution of bromine and chlorine atoms and (b) the direct pro-portional dependence of their effective interaction probabilities on the intensity of ion bombardment. The existence of an additional channel of heterogeneous interaction with the participation of HCl molecules is proposed.

Semiclassical Dynamics on Machine-Learned Coupled Multireference Potential Energy Surfaces: Application to the Photodissociation of the Simplest Criegee Intermediate.

Determination of high-dimensional potential energy surfaces (PESs) and nonadiabatic couplings have always been quite challenging. To this end, machine learning (ML) models, trained with a finite set of ab initio data, allow accurate prediction of such properties. To express the PESs in terms of atomic contributions is the cornerstone of any ML based technique because it can be easily scaled to large systems. In this work, we have constructed high fidelity PESs and nonadiabatic coupling terms at the CASSCF level of ab initio data using a machine learning technique, namely, kernel-ridge regression. Additional MRCI-level calculations were carried out to assess the quality of the PESs. We use these machine-learned PESs and nonadiabatic couplings to simulate excited-state molecular dynamics based on Tully's fewest-switches surface hopping method (FSSH). FSSH is a semiclassical method in which nuclei move on the PESs due to the electrons according to the laws of classical mechanics. Nonadiabatic effects are taken into account in terms of transitions between PESs. We apply this scheme to study the O-O photodissociation of the simplest Criegee intermediate (CH2OO). The FSSH trajectories were initiated on the lowest optically bright singlet excited state (S2) and propagated along the three most important internal coordinates, namely, O-O and C-O bond distances and the COO bond angle. Some of the trajectories end up on energetically lower PESs as a result of radiationless transfer through conical intersections. All of the trajectories lead to the dissociation of the O-O bond due to the dissociative nature of the excited PESs through one of the two dissociative channels. The simulation reveals that there is about 88.4% probability of dissociation through the lower channel leading to the H2CO (X1A1) and O (1D) products, whereas there is only 11.6% probability of dissociation through the upper channel leading to H2CO (a3A″) and O (3P) products.

SBETHE: Stopping powers of materials for swift charged particles from the corrected Bethe formula

The Fortran program sbethe calculates the stopping power of materials for swift charged particles with small charges (electrons, muons, protons, their antiparticles, and alphas). The electronic stopping power is computed from the corrected Bethe formula, with the shell correction derived from numerical calculations with the plane-wave Born approximation (PWBA) for atoms, which were based on an independent-electron model with the Dirac–Hartree–Fock–Slater self-consistent potential for the ground-state configuration of the target atom. The density effect correction is evaluated from an empirical optical oscillator strength (OOS) model based on atomic subshell contributions obtained from PWBA calculations. For projectiles heavier than the electron, the Barkas correction is evaluated from the OOS model, and the Lindhard–Sørensen correction is estimated from an accurate parameterization of its numerical values. The calculated electronic stopping power is completely determined by a single empirical parameter, the mean excitation energy or I value of the material. The radiative stopping power for electrons, and positrons, is evaluated by means of Seltzer and Berger's cross section tables for bremsstrahlung emission. The program yields reliable stopping powers and particle ranges for arbitrary materials and projectiles with kinetic energy larger than a certain cutoff value Ecut, which is specific of each projectile kind. The program is accompanied by an extensive database that contains tables of relevant energy-dependent atomic quantities for all the elements from hydrogen to einsteinium. sbethe may be used to generate basic information for dosimetry calculations and Monte Carlo simulations of radiation transport, and as a pedagogical tool. Program summaryProgram title:sbetheCPC Library link to program files:https://doi.org/10.17632/7zw25f428t.1Licensing provisions: CC by NC 3.0Programming language: Fortran 90/95Nature of problem: The program calculates the stopping power of arbitrary materials for swift charged projectiles with small charges. The material is characterized by its chemical composition, mass density, and the empirical I value. The considered projectiles are electrons, positrons, negative muons, antimuons, protons, antiprotons, and alphas, which are described as point particles characterized by their mass and charge. If the actual I value of the material is known, the results from the program are expected to be reliable for projectiles with kinetic energy higher than a value Ecut, of the order of 1 keV for electrons and positrons, 150 keV for muons and antimuons, 0.75 MeV for protons and antiprotons, and 5 MeV for alpha particles.Solution method: The electronic stopping power is calculated by means of a corrected Bethe formula [1], which combines the conventional Bethe logarithm with the following corrections,1) the shell correction obtained from calculations based on the plane-wave Born approximation with the self-consistent Dirac–Hartree–Fock–Slater (DHFS) potential of neutral atoms in their ground-state configuration [2],2) the density effect correction, which accounts for the reduction of the stopping power caused by the dielectric polarization of the medium,3) a parameterization of the Lindhard–Sørensen correction, which generalizes the Bloch correction for relativistic projectiles, and4) the Barkas correction, which accounts for differences between the stopping powers of particles and their antiparticles.The density-effect and the Barkas corrections are calculated from a model of the optical oscillator strength (OOS) of the material, which combines the contributions of inner atomic subshells calculated with the DHFS potential, with a classical oscillator model for the contribution of valence electrons,A simple extrapolation formula is used to extend the calculated electronic stopping power to energies less than Ecut to allow the calculation of particle ranges.For electrons and positrons, the radiative stopping power is calculated from numerical tables prepared by Seltzer and Berger [3].Additional comments including restrictions and unusual features: The calculated stopping power is determined by a single parameter, the mean excitation energy or I value. The program assigns to each material a default I value, derived from the recommendations in the ICRU Report 37, which can be changed by the user. The distribution package includes text files with tables of atomic energy-dependent quantities (subshell optical oscillator strengths, shell corrections, scaled cross sections for bremsstrahlung emission) that are used in the calculations.

Band Structure Calculation and Optical Properties of Ag3AsS3 Crystals

In the study, band structure calculation in the points of high symmetry of the first Brillouin zone and alongside the lines that connect them has been derived by using CASTEP programs in which the pseudopotential method with the basis in the form of plane-waves is realized. The calculated value of the lattice parameters using GGA functional is well correlated with experimental data. According to the band diagram that was built for the Ag3AsS3 crystal using GGA method, band gap has an indirect type. The calculated value of the band gap is = 1.22 еV. The experimental value of the band gap obtained by Tauc’s method is = 2.01 еV, = 2.17 еV. Full and partial density of N(E) states for contributions of separate atoms has been calculated. As a result, the top of the valence band is formed by 3p-states of S atoms and the bottom of the conduction band is formed by 5s-states of Ag atoms and 3p-states of S atoms.

Combined experimental and theoretical studies of bis-chalcone: Estimation of non-covalent interactions

A new bischalcone BCH (2E,2′E)-1,1′-(((1,4-phenylenebis(methylene))bis(oxy))bis(2,1-phenylene))bis(3-(4-(benzyloxy)phenyl)prop‑2-en-1-one) has been synthesized and characterized by spectroscopic and single crystal X-ray diffraction techniques. The C–H···O and C–H···π intermolecular non-covalent interactions play crucial contribution in the formation of supramolecular architecture. A comprehensive Hirshfeld surface analysis and 2D fingerprint plots reveal the presence of intermolecular non-covalent interactions and percentage contributions of individual atoms. Hirshfeld energy framework calculations demonstrate dominance of dispersion energy. DFT calculations have been carried out energetic evaluation of non-covalent interactions. The charge distribution is rationalized by MEP surfaces. NCI Plot and QTAIM analysis have been computed to quantification of non-covalent interactions in the stabilization of the molecular crystal packing.

Identification of metal ion-binding sites in RNA structures using deep learning method.

Metal ion is an indispensable factor for the proper folding, structural stability and functioning of RNA molecules. However, it is very difficult for experimental methods to detect them in RNAs. With the increase of experimentally resolved RNA structures, it becomes possible to identify the metal ion-binding sites in RNA structures through in-silico methods. Here, we propose an approach called Metal3DRNA to identify the binding sites of the most common metal ions (Mg2+, Na+ and K+) in RNA structures by using a three-dimensional convolutional neural network model. The negative samples, screened out based on the analysis for binding surroundings of metal ions, are more like positive ones than the randomly selected ones, which are beneficial to a powerful predictor construction. The microenvironments of the spatial distributions of C, O, N and P atoms around a sample are extracted as features. Metal3DRNA shows a promising prediction power, generally surpassing the state-of-the-art methods FEATURE and MetalionRNA. Finally, utilizing the visualization method, we inspect the contributions of nucleotide atoms to the classification in several cases, which provides a visualization that helps to comprehend the model. The method will be helpful for RNA structure prediction and dynamics simulation study. Availability and implementation: The source code is available at https://github.com/ChunhuaLiLab/Metal3DRNA.

Identification and low-frequency vibrational analysis of three free anthraquinones via terahertz spectroscopy

In this study, terahertz time-domain spectroscopy (THz-TDS) was used to obtain the terahertz absorption spectra of three free anthraquinones (Chrysophanol, Emodin, Physcion) in the frequency range of 0.2–4.3 THz. The results show that terahertz spectroscopy is an effective detecting such compounds. Meanwhile, the theoretical spectrum using density functional theory calculations agrees well with the experimental spectrum. A modal decoupling method was used to identify each low-frequency vibrational mode and determine the average contribution of different atoms and groups. Modal decoupling provides a better understanding of molecules' mixed vibrational modes and enables quantifying the atoms' vibrational contributions. Results show that the substituent group facilitates the transition between the fundamental vibrational modes; subsequently, the substituent group shifts the vibrational centre of gravity of the three molecules and affects the vibrational contribution of hydrogen bonds. Furthermore, insignificant Emodin absorption is related to the nearly symmetrical structure formed by the substituents. The feasibility of terahertz analysis of differential molecular structures has also been confirmed.

Chiral Magnetic Interactions in Small Fe Clusters Triggered by Symmetry-Breaking Adatoms

The chirality of the interaction between the local magnetic moments in small transition-metal alloy clusters is investigated in the framework of density-functional theory. The Dzyaloshinskii–Moriya (DM) coupling vectors Dij between the Fe atoms in Fe2X and Fe3X with X = Cu, Pd, Pt, and Ir are derived from independent ground-state energy calculations for different noncollinear orientations of the local magnetic moments. The local-environment dependence of Dij and the resulting relative stability of different chiral magnetic orders are analyzed by contrasting the results for different adatoms X and by systematically varying the distance between the adatom X and the Fe clusters. One observes that the adatoms trigger most significant DM couplings in Fe2X, often in the range of 10–30 meV. Thus, the consequences of breaking the inversion symmetry of the Fe dimer are quantified. Comparison between the symmetric and antisymmetric Fe-Fe couplings shows that the DM couplings are about two orders of magnitude weaker than the isotropic Heisenberg interactions. However, they are in general stronger than the anisotropy of the symmetric couplings. In Fe3X, alloying induces interesting changes in both the direction and strength of the DM couplings, which are the consequence of breaking the reflection symmetry of the Fe trimer and which depend significantly on the adatom-trimer distance. A local analysis of the chirality of the electronic energy shows that the DM interactions are dominated by the spin-orbit coupling at the adatoms and that the contribution of the Fe atoms is small but not negligible.

Algorithms and programs for the shell decomposition of oscillating functions in space

Real-space refinement of atomic models in macromolecular crystallography and cryo-electron microscopy fits a model to a map obtained with experimental data. To do so, the atomic model is converted into a map of limited resolution and then this map is compared quantitatively with the experimental one. For an appropriate comparison, the atomic contributions comprising the model map should reflect the resolution of the experimental map and the atomic displacement parameter (ADP) values. Such contributions are spherically symmetric oscillating functions, different for chemically different kinds of atoms, different ADPs and different resolution values, and their derivatives with respect to atomic parameters rule the model refinement. For given parameter values, every contribution may be calculated numerically using two Fourier transforms, which is highly time consuming and makes calculation of the respective derivatives problematic. Alternatively, for an atom of each required type its contribution can be expressed in an analytical form as a sum of specially designed terms. Each term is different from zero essentially inside a spherical shell, and changing the ADP value does not change its form but rather changes the value of one of its arguments. In general, these terms become a convenient tool for the decomposition of oscillating spherically symmetric functions. This work describes the algorithms and respective software, named dec3D, to carry out such a shell decomposition for density contributions of different kinds of atoms and ions.

A simple assessment of enthalpy of fusion of non-aromatic organic compounds as smokeless fuels for correcting thermochemical data to a standard state

The knowledge of the enthalpy of fusion of different categories of non-aromatic organic compounds, which have wide applications as smokeless fuels, is important in Chemical Thermodynamics but its experimental determination is complicated. An improved model is developed based on the additive contribution of different atoms of a non-aromatic compound with the general formula CaHbNcOdSeFfClgBrhIi and two non-additive correcting parameters. The largest reported data of 639 non-aromatic organic compounds (corresponding to 949 experimental values) were collected from different sources to derive and test the new model. Errors maximum value (ErrorMax), root-mean-square error (RMSE), and mean error (ME) of the new model are compared with one of the best methods for 513 and 126 data of two sets of training and test, respectively. ErrorMax, RMSE, and ME values of the novel method for training/test sets are 19.68/16.24, 4.393/4.668, and 0.000/0.230, respectively, but the results of the comparative model are 39.74/26.00, 7.004/5.666, and 1.645/1.940, respectively. The results confirmed that the new model can predict the enthalpy of fusion of non-aromatic organic compounds more accurately than a more complex comparative method.

Leveraging scaffold information to predict protein-ligand binding affinity with an empirical graph neural network.

Protein-ligand binding affinity prediction is an important task in structural bioinformatics for drug discovery and design. Although various scoring functions (SFs) have been proposed, it remains challenging to accurately evaluate the binding affinity of a protein-ligand complex with the known bound structure because of the potential preference of scoring system. In recent years, deep learning (DL) techniques have been applied to SFs without sophisticated feature engineering. Nevertheless, existing methods cannot model the differential contribution of atoms in various regions of proteins, and the relationship between atom properties and intermolecular distance is also not fully explored. We propose a novel empirical graph neural network for accurate protein-ligand binding affinity prediction (EGNA). Graphs of protein, ligand and their interactions are constructed based on different regions of each bound complex. Proteins and ligands are effectively represented by graph convolutional layers, enabling the EGNA to capture interaction patterns precisely by simulating empirical SFs. The contributions of different factors on binding affinity can thus be transparently investigated. EGNA is compared with the state-of-the-art machine learning-based SFs on two widely used benchmark data sets. The results demonstrate the superiority of EGNA and its good generalization capability.

Multitask Deep Ensemble Prediction of Molecular Energetics in Solution: From Quantum Mechanics to Experimental Properties.

The past few years have witnessed significant advances in developing machine learning methods for molecular energetics predictions, including calculated electronic energies with high-level quantum mechanical methods and experimental properties, such as solvation free energy and logP. Typically, task-specific machine learning models are developed for distinct prediction tasks. In this work, we present a multitask deep ensemble model, sPhysNet-MT-ens5, which can simultaneously and accurately predict electronic energies of molecules in gas, water, and octanol phases, as well as transfer free energies at both calculated and experimental levels. On the calculated data set Frag20-solv-678k, which is developed in this work and contains 678,916 molecular conformations, up to 20 heavy atoms, and their properties calculated at B3LYP/6-31G* level of theory with continuum solvent models, sPhysNet-MT-ens5 predicts density functional theory (DFT)-level electronic energies directly from force field-optimized geometry within chemical accuracy. On the experimental data sets, sPhysNet-MT-ens5 achieves state-of-the-art performances, which predict both experimental hydration free energy with a RMSE of 0.620 kcal/mol on the FreeSolv data set and experimental logP with a RMSE of 0.393 on the PHYSPROP data set. Furthermore, sPhysNet-MT-ens5 also provides a reasonable estimation of model uncertainty which shows correlations with prediction error. Finally, by analyzing the atomic contributions of its predictions, we find that the developed deep learning model is aware of the chemical environment of each atom by assigning reasonable atomic contributions consistent with our chemical knowledge.

AlteQ: a new complementarity principle-centered method for the evaluation of docking poses

Molecular docking is the most popular and widely used method for identifying novel molecules against a target of interest. However, docking procedures and their validation are still under intense development. In the present investigation, we evaluate a quantum free-orbital AlteQ method for evaluating docking complexes generated by taking EGFR complexes as an example. The AlteQ method calculates the electron density using Slater’s type atomic contributions in the interspace between the receptor and the ligand. Since the interactions are determined by the overlap of electron clouds, they follow the complementarity principle, and an equation can be obtained that describes these interactions. The AlteQ method evaluates the quality of the interaction between the receptor and the ligand, how complementary the interactions are, and due to this, it is used to reject less realistic structures obtained by docking methods. Here, three different equations were used to determine the quality of the interactions in experimental complexes and docked complexes obtained using AutoDock Vina and AutoDock 4.2.6. Communicated by Ramaswamy H. Sarma