Psi4: an open-source ab initio electronic structure program

Quantification of Anisotropy in Exchange and Dispersion Interactions: A Simple Model for Physics-Based Force Fields

In some compounds, exchange repulsion is orientation dependent. However, in contrast to quantum chemical methods that treat exchange explicitly, empirical models assume exchange to be spherically symmetric, yielding an average description only. Here we quantify the anisotropy of exchange and dispersion energy for hydrogen halides and water by probing these compounds with a helium atom using the symmetry-adapted perturbation theory (SAPT). The exchange interaction is reduced by up to 33% due to the σ-hole in hydrogen iodide, depending on the location of the probe. We demonstrate how this anisotropy can be modeled in empirical force fields either using an angle-dependent potential or by introducing virtual sites, reducing the error in the empirical model by a factor of 5 compared to isotropic atoms. Lone-pairs on water, positioned close to perpendicular to the plane of the molecule, on a line with the oxygen atom, and, surprisingly, σ-holes on water both modulate the exchange interaction strongly. Both lone-pairs and σ-holes can be modeled by virtual sites, leading to an 80% reduced error.

A Green Host-Guest Protocol to Improve Water Solubility of Fluorescent Dyes

Improving fluorescence emission efficiency is essential to develop novel luminescent materials. However, the low water solubility of conventional fluorescent dyes is a serious obstacle to broadening the application scope. Herein, a green protocol have been proposed: Two poorly water-soluble naphthalimide derivatives MONI and MANI with high fluorescent quantum yields (larger than 0.95 in toluene solution) were loaded in three different sizes of cyclodextrin (CD; α, β, γ-CD) with high water solubility. To further check the feasibility of the proposal, density functional theory (DFT) and time dependent-DFT (TD-DFT) methods combining the Own N-layer Integrated molecular Orbital molecular Mechanics (ONIOM) model with dispersion correction were employed to investigate the geometric and electronic structures of complexes CD·MXNI (X = N, O) in the excited-state process. TD-DFT calculations predict that the fantastic emission behavior of MXNI can be reserved after binding with CD, even improving fluorescent intensity in aqueous solution. Basis set superposition error (BSSE) correction and symmetry adapted perturbation theory (SAPT) were adopted to estimate the complexation energies and weak noncovalent interactions. The middle-sized β-CD is the perfect candidate to allow fluorescent molecules to settle into its cavity, forming an inclusion complex. Energy decomposition analysis (EDA) indicates that dispersion is superior to electrostatics interaction in embedding-type β-CD·MXNI, while it is contrary in α,γ-CD·MXNI. NMR calculations further prove the existence of a strong intermolecular hydrogen bond interaction between host and guest. Weak interactions that limited molecular vibration and hampered the nonradiative inactivation channel are conducive to the enhanced emission intensity.

van der Waals Radii of Free and Bonded Atoms from Hydrogen (Z = 1) to Oganesson (Z = 118)

Reliable numerical values of van der Waals (vdW) radii are required for constructing empirical force fields, vdW-inclusive density functional, and quantum-chemical methods, as well as for implicit solvent models. However, multiple definitions exist for vdW radii, involving either equilibrium or the closest contact distances between free or bonded atoms within molecules or crystals. For the paradigmatic case of the hydrogen atom, its reported vdW radius fluctuates between 2.15 and 3.70 Bohr depending on the definition, leading to a high uncertainty in calculations and different conceptual interpretations of noncovalent interactions. In this work, we systematically review different definitions and methodologies to establish the free and bonded vdW radii for hydrogen, based on equilibrium vdW distances in noncovalently bonded molecules, enveloping electron density cutoffs, noncovalent positron bonds in hydrogen anion dimer, vacuum virtual photon cloud caused by the hydrogen atom, and atomic dipole polarizability. By doing so, we show that the vdW radius of the free hydrogen atom is 3.16 ± 0.06 Bohr. By employing the most general and elegant definition of atomic vdW radius as a function of the atomic polarizability, we tabulate consistent values of vdW radii for all atoms in the periodic table up to Z = 118.

Structure-Spectroscopy Correlation in the Self-Assembled Perylene Diimide-Based Dimers via Inter-Chromophore Coupling

The impact of conformational change on the ground and excited states of seven perylene diimide (PDI)-based dimeric systems is examined by introducing longitudinal shift, transverse shift, and rotation of one monomer with respect to another. The minimum energy conformations are compared via an energy decomposition analysis. The heteroatom-substituted dimeric systems, such as B2 N2-embedded PDI, trans-thio-PDI (trans-S2-PDI), and N-PDI, show BN···π, C═S···π, and N···H interactions that survive over a longer range of longitudinal and transverse shifts. The excitonic coupling analysis reveals that both Coulomb- and CT-mediated couplings are crucial for understanding aggregate absorption spectra. While the Coulomb coupling exhibits a monotonic behavior with conformation changes, the CT component changes significantly with minor geometrical deviations. The interplay between the two couplings leads to J-type, H-type, and null aggregates, depending on the conformations of the dimers. The overall trend of both couplings is consistent across all systems, although they differ in magnitude. The trans-S2-PDI shows the strongest Coulomb and CT couplings, while it is weak in perylene and B2N2-PDI dimers. The resonant model for strongly coupled Frenkel excitonic (FE) and CT states successfully characterizes the single- and double-band nature of absorption spectra in dimers. In strong coupling regions, the dimers show blue-shifted single-band excitation to the upper FE state. In contrast, excitation to the lower FE and upper CT states produces a red-shifted two-band spectrum in the weakly coupled regions. The intensity of the CT band diminishes with the monomer separation. In most cases, the perpendicularly stacked structures show null-aggregate behavior with no spectral shift due to the absence of Coulomb and CT couplings. The exciton relaxation pathway of the heteroatom-substituted PDIs is found to be influenced by the presence of nπ* states between the FE and CT states.

DASH properties: Estimating atomic and molecular properties from a dynamic attention-based substructure hierarchy

Recently, we presented a method to assign atomic partial charges based on the DASH (dynamic attention-based substructure hierarchy) tree with high efficiency and quantum mechanical (QM)-like accuracy. In addition, the approach can be considered "rule based"-where the rules are derived from the attention values of a graph neural network-and thus, each assignment is fully explainable by visualizing the underlying molecular substructures. In this work, we demonstrate that these hierarchically sorted substructures capture the key features of the local environment of an atom and allow us to predict different atomic properties with high accuracy without building a new DASH tree for each property. The fast prediction of atomic properties in molecules with the DASH tree can, for example, be used as an efficient way to generate feature vectors for machine learning without the need for expensive QM calculations. The final DASH tree with the different atomic properties as well as the complete dataset with wave functions is made freely available.

Forte: A suite of advanced multireference quantum chemistry methods

Forte is an open-source library specialized in multireference electronic structure theories for molecular systems and the rapid prototyping of new methods. This paper gives an overview of the capabilities of Forte, its software architecture, and examples of applications enabled by the methods it implements.

Allyl-Allyl Coupling Promoted by Catalyst Systems with two Palladium Atoms - A Plethora of Potentially Pericyclic Processes

Recently, Huang and co-workers reported a catalytic reaction that utilizes H2 as the sole reductant for a C-C coupling of allyl groups with yields up to 96 %. Here we use computational quantum chemistry to identify several key features of this reaction that provide clarity on how it proceeds. We propose the involvement of a Pd-Pd bound dimer precatalyst, demonstrate the importance of ligand π-π interactions and counterions, and identify a new, energetically viable, mechanism involving two dimerized, outer-sphere reductive elimination transition structures that determine both the rate and selectivity. Although we rule out the previously proposed transmetalation step on energetic grounds, we show it to have an unusual aromatic transition structure in which two Pd atoms support rearranging electrons. The prevalence of potential metal-supported pericyclic reactions in this system suggests that one should consider such processes regularly, but the results of our calculations also indicate that one should do so with caution.

PyDFT-QMMM: A modular, extensible software framework for DFT-based QM/MM molecular dynamics

PyDFT-QMMM is a Python-based package for performing hybrid quantum mechanics/molecular mechanics (QM/MM) simulations at the density functional level of theory. The program is designed to treat short-range and long-range interactions through user-specified combinations of electrostatic and mechanical embedding procedures within periodic simulation domains, providing necessary interfaces to external quantum chemistry and molecular dynamics software. To enable direct embedding of long-range electrostatics in periodic systems, we have derived and implemented force terms for our previously described QM/MM/PME approach [Pederson and McDaniel, J. Chem. Phys. 156, 174105 (2022)]. Communication with external software packages Psi4 and OpenMM is facilitated through Python application programming interfaces (APIs). The core library contains basic utilities for running QM/MM molecular dynamics simulations, and plug-in entry-points are provided for users to implement custom energy/force calculation and integration routines, within an extensible architecture. The user interacts with PyDFT-QMMM primarily through its Python API, allowing for complex workflow development with Python scripting, for example, interfacing with PLUMED for free energy simulations. We provide benchmarks of forces and energy conservation for the QM/MM/PME and alternative QM/MM electrostatic embedding approaches. We further demonstrate a simple example use case for water solute in a water solvent system, for which radial distribution functions are computed from 100 ps QM/MM simulations; in this example, we highlight how the solvation structure is sensitive to different basis-set choices due to under- or over-polarization of the QM water molecule's electron density.

Software Infrastructure for Next-Generation QM/MM-ΔMLP Force Fields

We present software infrastructure for the design and testing of new quantum mechanical/molecular mechanical and machine-learning potential (QM/MM-ΔMLP) force fields for a wide range of applications. The software integrates Amber's molecular dynamics simulation capabilities with fast, approximate quantum models in the xtb package and machine-learning potential corrections in DeePMD-kit. The xtb package implements the recently developed density-functional tight-binding QM models with multipolar electrostatics and density-dependent dispersion (GFN2-xTB), and the interface with Amber enables their use in periodic boundary QM/MM simulations with linear-scaling QM/MM particle-mesh Ewald electrostatics. The accuracy of the semiempirical models is enhanced by including machine-learning correction potentials (ΔMLPs) enabled through an interface with the DeePMD-kit software. The goal of this paper is to present and validate the implementation of this software infrastructure in molecular dynamics and free energy simulations. The utility of the new infrastructure is demonstrated in proof-of-concept example applications. The software elements presented here are open source and freely available. Their interface provides a powerful enabling technology for the design of new QM/MM-ΔMLP models for studying a wide range of problems, including biomolecular reactivity and protein-ligand binding.

Broadening access to small-molecule parameterization with the force field toolkit

Access to accurate force-field parameters for small molecules is crucial for computational studies of their interactions with proteins. Although a number of general force fields for small molecules exist, e.g., CGenFF, GAFF, and OPLS, they do not cover all common chemical groups and their combinations. The Force Field Toolkit (ffTK) provides a comprehensive graphical interface that streamlines the development of classical parameters for small molecules directly from quantum mechanical (QM) calculations, allowing for force-field generation for almost any chemical group and validation of the fit relative to the target data. ffTK relies on supported external software for the QM calculations, but it can generate the necessary QM input files and parse and analyze the QM output. In previous ffTK versions, support for Gaussian and ORCA QM packages was implemented. Here, we add support for Psi4, an open-source QM package free for all users, thereby broadening user access to ffTK. We also compare the parameter sets obtained with the new ffTK version using Gaussian, ORCA, and Psi4 for three molecules: pyrrolidine, n-propylammonium cation, and chlorobenzene. Despite minor differences between the resulting parameter sets for each compound, most prominently in the dihedral and improper terms, we show that conformational distributions sampled in molecular dynamics simulations using these parameter sets are quite comparable.

Picking up Good Vibrations through Quartic Force Fields and Vibrational Perturbation Theory

Quartic force fields (QFFs) define sparse potential energy surfaces (compared to semiglobal surfaces) that are the cheapest and easiest means of computing anharmonic vibrational frequencies, especially when utilized with second-order vibrational perturbation theory (VPT2). However, flat and shallow potential surfaces are exceedingly difficult for QFFs to treat through a combination of numerical noise in the often numerically computed derivatives and in competing energy factors in the composite energies often utilized to provide high-level spectroscopic predictions. While some of these issues can be alleviated with analytic derivatives, hybrid QFFs, and intelligent choices in coordinate systems, the best practice is for predicting good molecular vibrations via QFFs is to understand what they cannot do, and this manuscript documents such cases where QFFs may fail.

Plugin-based interoperability and ecosystem management for the MolSSI Driver Interface Project

The MolSSI Driver Interface (MDI) Project is an effort to simplify and standardize the process of enabling tight interoperability between independently developed code bases and is supported by numerous software packages across the domain of chemical physics. It enables a wide variety of use cases, including quantum mechanics/molecular mechanics, advanced sampling, path integral molecular dynamics, machine learning, ab initio molecular dynamics, etc. We describe two major developments within the MDI Project that provide novel solutions to key interoperability challenges. The first of these is the development of the MDI Plugin System, which allows MDI-supporting libraries to be used as highly modular plugins, with MDI enforcing a standardized application programming interface across plugins. Codes can use these plugins without linking against them during their build process, and end-users can select which plugin(s) they wish to use at runtime. The MDI Plugin System features a sophisticated callback system that allows codes to interact with plugins on a highly granular level and represents a significant advancement toward increased modularity among scientific codes. The second major development is MDI Mechanic, an ecosystem management tool that utilizes Docker containerization to simplify the process of developing, validating, maintaining, and deploying MDI-supporting codes. Additionally, MDI Mechanic provides a framework for launching MDI simulations in which each interoperating code is executed within a separate computational environment. This eliminates the need to compile multiple production codes within a single computational environment, reducing opportunities for dependency conflicts and lowering the barrier to entry for users of MDI-enabled codes.

Noncovalent and Covalent O-H···O Interactions in PPh3O Cocrystals: A Correlation Study Involving QTAIM, SAPT, NBO, and IBSI Methods

PPh3O.hemihydrate polymorphs and 11 assorted PPh3O cocrystals collectively constitute a reliable stock to pursue a systematic analysis aiming to investigate the impacts of some vital issues on the TPPO.H-bond donor aggregates. The issues highlighted herein are (i) effect of varying acidity of H-bond donors on the degeneracy of lone pairs of the H-bond acceptor (PPh3O), (ii) effectiveness of the |V(r)|/G(r) and H(r)/ρ(r) parameters as a covalency metric, (iii) 3c-4e bonding in the covalent PPh3O.nitric acid cocrystal, (iv) salient features of H-bond interaction energy and an interplay of its components, (v) an intrinsic bond strength scale for the PPh3O cocrystals, and (vi) reliable empirical relations between several bond descriptors for a quick estimation of interaction energy. To be specific about point (vi), we have propounded two promising avenues for a fast semiquantitative calculation of interaction energy from an endearing nonenergetic parameter, viz., bond length: dO-H···O → ρBCP (MAPE = 2.36%) → ESAPT0 (MAPE = 9.26%), and dO-H···O → IBSI (MAPE = 1.87%) → ESAPT0 (MAPE = 9.66%). All the aforesaid issues have been explored in detail through the QTAIM, NBO, and IBSI analyses (M06-2X-D3/def2-TZVP level), as well as by the SAPT study at the SAPT0/aug-cc-pVDZ platform. The statistically valid correlation studies can be particularly conducive for practical purposes as a transformative extension of the established facts into postulates for the unknown cocrystals.

FFParam-v2.0: A Comprehensive Tool for CHARMM Additive and Drude Polarizable Force-Field Parameter Optimization and Validation

Developing production quality CHARMM force-field (FF) parameters is a very detailed process involving a variety of calculations, many of which are specific for the molecule of interest. The first version of FFParam was developed as a standalone Python package designed for the optimization of electrostatic and bonded parameters of the CHARMM additive and polarizable Drude FFs by using quantum mechanical (QM) target data. The new version of FFParam has multiple new capabilities for FF parameter optimization and validation, with an emphasis on the ability to use condensed-phase target data in optimization. FFParam-v2 allows optimization of Lennard-Jones (LJ) parameters using potential energy scans of interactions between selected atoms in a molecule and noble gases, viz., He and Ne, and through condensed-phase calculations, from which experimental observables such as heats of vaporization and free energies of solvation may be obtained. This functionality serves as a gold standard for both optimizing parameters and validating the performance of the final parameters. A new bonded parameter optimization algorithm has been introduced to account for simultaneously optimizing multiple molecules sharing parameters. FFParam-v2 also supports the comparison of normal modes and the potential energy distribution of internal coordinates towards each normal mode obtained from QM and molecular mechanics calculations. Such comparison capability is vital to validate the balance among various bonded parameters that contribute to the complex normal modes of molecules. User interaction has been extended beyond the original graphical user interface to include command-line interface capabilities that allow for integration of FFParam in workflows, thereby facilitating the automation of parameter optimization. With these new functionalities, FFParam is a more comprehensive parameter optimization tool for both beginners and advanced users.

In-Silico Aided Screening and Characterization Results in Stability Enhanced Novel Roxadustat Co-Crystal

Roxadustat (RXD) is an approved drug substances for the treatment of renal anemia. It has poor aqueous solubility and photochemical stability. This study employs a comprehensive approach to enhance the stability and physicochemical properties RXD through coformer selection and characterization. The investigation integrates delta pKa analysis, molecular complementary assessment, molecular electrostatic potential surface analysis, and machine learning techniques to predict potential co-crystal formation and binding interactions between drug molecules and coformers. The co-crystal screening which lead to in a novel RXD-nicotinamide co-crystal (RXD-NA). Experimental characterization underscores the physical and chemical stability of the co-crystals. To elucidate the supramolecular synthons and understand the intermolecular interactions in the RXD-NA co-crystal, Hirshfeld surfaces analysis, quantum theory of atoms in molecules (QTAIM) analysis and non-covalent interaction (NCI) analysis were performed. Computational analysis of photo-isomer formation aligns with experimental observations, further enhancing our understanding of RXD-coformer interactions. RXD-NA co-crystal was found photo-chemically stable as compared to free base API drug substance. This integrated methodology provides a systematic framework for informed co-crystal design, holding promise for optimizing RXD formulations based on molecular interactions and stability considerations. Consequently, this study contributes valuable insights to the field of rational drug design and formulation optimization.

Spurious Oscillations Caused by Density Functional Approximations: Who is to Blame? Exchange or Correlation?

We analyze the varying susceptibilities of different density functional approximations (DFAs) to present spurious oscillations on the profiles of several vibrational properties. Among other problems, these spurious oscillations cause significant errors in harmonic and anharmonic IR and Raman frequencies and intensities. This work hinges on a judicious strategy to dissect the exchange and correlation components of DFAs and pinpoint the origins of these oscillations. We identify spurious oscillations in derivatives of all energy components with respect to nuclear displacements, including those energy terms that do not involve numerical integrations. These indirect spurious oscillations are attributed to suboptimal electron densities resulting from a self-consistent field procedure using a DFA that exhibits direct spurious oscillations. Direct oscillations stem from inaccurate numerical integration of the exchange and correlation energy density functionals. A thorough analysis of direct spurious oscillations reveals that only a handful of exchange and correlation components are insensitive to spurious oscillations, giving rise to three families of functionals, BH&H, LSDA, and BLYP. Among the functionals in these families, we encounter four widespread DFAs: BLYP, B3LYP, LC-BLYP, and CAM-B3LYP. Certain DFAs like PBE appear less sensitive to spurious oscillations due to compensatory cancellations between their energy components. Additionally, we found non-negligible but small oscillations in PBE and TPSS, which could be safely employed provided a sufficiently large integration grid is used in the calculations. These findings hint at the key components of current approximations to be improved and emphasize the necessity to develop accurate DFAs suitable for studying molecular spectroscopies.

Relative cooperativity in neutral and charged molecular clusters using QM/MM calculations

QM/MM methods have been used to study electronic structure properties and chemical reactivity in complex molecular systems where direct electronic structure calculations are not feasible. In our previous work, we showed that non-polarizable force fields, by design, describe intermolecular interactions through pairwise interactions, overlooking many-body interactions involving three or more particles. In contrast, polarizable force fields account partially for many-body effects through polarization, but still handle van der Waals and permanent electrostatic interactions pairwise. We showed that despite those limitations, polarizable and non-polarizable force fields can reproduce relative cooperativity achieved using density functional theory due to error compensation mechanisms. In this contribution, we assess the performance of QM/MM methods in reproducing these phenomena. Our study highlights the significance of the QM region size and force field choice in QM/MM calculations, emphasizing the importance of parameter validation to obtain accurate interaction energy predictions.

De novo design of drug-binding proteins with predictable binding energy and specificity

The de novo design of small molecule-binding proteins has seen exciting recent progress; however, high-affinity binding and tunable specificity typically require laborious screening and optimization after computational design. We developed a computational procedure to design a protein that recognizes a common pharmacophore in a series of poly(ADP-ribose) polymerase-1 inhibitors. One of three designed proteins bound different inhibitors with affinities ranging from <5 nM to low micromolar. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free energy calculations performed directly on the designed models were in excellent agreement with the experimentally measured affinities. We conclude that de novo design of high-affinity small molecule-binding proteins with tuned interaction energies is feasible entirely from computation.

Impact of Combination Rules, Level of Theory, and Potential Function on the Modeling of Gas- and Condensed-Phase Properties of Noble Gases

The systems of noble gases are particularly instructive for molecular modeling due to the elemental nature of their interactions. They do not normally form bonds nor possess a (permanent) dipole moment, and the only forces determining their bonding/clustering stems from van der Waals forces─dispersion and Pauli repulsion, which can be modeled by empirical potential functions. Combination rules, that is, formulas to derive parameters for pair potentials of heterodimers from parameters of corresponding homodimers, have been studied at length for the Lennard-Jones 12-6 potentials but not in great detail for other, more accurate, potentials. In this work, we examine the usefulness of nine empirical potentials in their ability to reproduce quantum mechanical (QM) benchmark dissociation curves of noble gas dimers (He, Ne, Ar, Kr, and Xe homo- and heterodimers), and we systematically study the efficacy of different permutations of combination relations for each parameter of the potentials. Our QM benchmark comprises dissociation curves computed by several different coupled cluster implementations as well as symmetry-adapted perturbation theory. The two-parameter Lennard-Jones potentials were decisively outperformed by more elaborate potentials that sport a 25-30 times lower root-mean-square error (RMSE) when fitted to QM dissociation curves. Very good fits to the QM dissociation curves can be achieved with relatively inexpensive four- or even three-parameter potentials, for instance, the damped 14-7 potential (Halgren, J. Am. Chem. Soc. 1992, 114, 7827-7843), a four-parameter Buckingham potential (Werhahn et al., Chem. Phys. Lett. 2015, 619, 133-138), or the three-parameter Morse potential (Morse, Phys. Rev. 1929, 34, 57-64). Potentials for heterodimers that are generated from combination rules have an RMSE that is up to 20 times higher than potentials that are directly fitted to the QM dissociation curves. This means that the RMSE, in particular, for light atoms, is comparable in magnitude to the well-depth of the potential. Based on a systematic permutation of combination rules, we present one or more combination rules for each potential tested that yield a relatively low RMSE. Two new combination rules are introduced that perform well, one for the van der Waals radius σij as ( 1 2 ( σ i 3 + σ j 3 ) ) 1 / 3 and one for the well-depth ϵij as ( 1 2 ( ϵ i - 2 + ϵ j - 2 ) ) - 1 / 2 . The QM data and the fitted potentials were evaluated in the gas phase against experimental second virial coefficients for homo- and heterodimers, the latter of which allowed evaluation of the combination rules. The fitted models were used to perform condensed phase molecular dynamics simulations to verify the melting points, liquid densities at the melting point, and the enthalpies of vaporization produced by the models for pure substances. Subtle differences in the benchmark potentials, in particular, the well-depth, due to the level of theory used were found here to have a profound effect on the macroscopic properties of noble gases: second virial coefficients or the bulk properties in simulations. By explicitly including three-body dispersion in molecular simulations employing the best pair potential, we were able to obtain accurate melting points as well as satisfactory densities and enthalpies of vaporization.

σ-Hole Site-Based Interactions within Hypervalent Pnicogen, Halogen, and Aerogen-Bearing Molecules with Lewis Bases: A Comparative Study

σ-Hole site-based interactions in the trigonal bipyramidal geometrical structure of hypervalent pnicogen, halogen, and aerogen-bearing molecules with pyridine and NCH Lewis bases (LBs) were comparatively examined. In this respect, the ZF5···, XF3O2···, and AeF2O3···LB complexes (where Z = As, Sb; X = Br, I; Ae = Kr, Xe; and LB = pyridine and NCH) were investigated. The electrostatic potential (EP) analysis affirmations outlined the occurrence of σ-holes on the systems under consideration with disparate magnitudes that increased according to the following order: AeF2O3 < XF3O2 < ZF5. In line with EP outcomes, the proficiency of σ-hole site-based interactions increased as the atomic size of the central atom increased with a higher favorability for the pyridine-based complexes over NCH-based ones. The interaction energy showed the most favorable negative values of -35.97, -44.53, and -56.06 kcal/mol for the XeF2O3···, IF3O2···, and SbF5···pyridine complexes, respectively. The preferentiality pattern of the studied interactions could be explained as a consequence of (i) the dramatic rearrangement of ZF5 molecules from the trigonal bipyramid geometry to the square pyramidal one, (ii) the significant and tiny deformation energy in the case of the interaction of XF3O2 molecules with pyridine and NCH, respectively, and (iii) the absence of geometrical deformation within the AeF2O3···pyridine and ···NCH complexes other than the XeF2O3···pyridine one. Quantum theory of atoms in molecules and noncovalent interaction index findings reveal the partially covalent nature of most of the investigated interactions. Symmetry-adapted perturbation theory affirmations declared that the electrostatic component was the driving force beyond the occurrence of the considered interactions. The obtained findings will help in improving our understanding of the effect of geometrical deformation on intermolecular interactions.

Building an ab initio solvated DNA model using Euclidean neural networks

Accurately modeling large biomolecules such as DNA from first principles is fundamentally challenging due to the steep computational scaling of ab initio quantum chemistry methods. This limitation becomes even more prominent when modeling biomolecules in solution due to the need to include large numbers of solvent molecules. We present a machine-learned electron density model based on a Euclidean neural network framework that includes a built-in understanding of equivariance to model explicitly solvated double-stranded DNA. By training the machine learning model using molecular fragments that sample the key DNA and solvent interactions, we show that the model predicts electron densities of arbitrary systems of solvated DNA accurately, resolves polarization effects that are neglected by classical force fields, and captures the physics of the DNA-solvent interaction at the ab initio level.

Capturing CO2 in Quadrupolar Binding Pockets: Broadband Microwave Spectroscopy of Pyrimidine-(CO2)n, n = 1,2

Pyrimidine has two in-plane CH(δ+)/N̈(δ-)/CH(δ+) binding sites that are complementary to the (δ-/2δ+/δ-) quadrupole moment of CO2. We recorded broadband microwave spectra over the 7.5-17.5 GHz range for pyrimidine-(CO2)n with n = 1 and 2 formed in a supersonic expansion. Based on fits of the rotational transitions, including nuclear hyperfine splitting due to the two 14N nuclei, we have assigned 313 hyperfine components across 105 rotational transitions for the n = 1 complex and 208 hyperfine components across 105 rotational transitions for the n = 2 complex. The pyrimidine-CO2 complex is planar, with CO2 occupying one of the quadrupolar binding sites, forming a structure in which the CO2 is stabilized in the plane by interactions with the C-H hydrogens adjacent to the nitrogen atom. This structure is closely analogous to that of the pyridine-CO2 complex studied previously by (Doran, J. L. J. Mol. Struct. 2012, 1019, 191-195). The fit to the n = 2 cluster gives rotational constants consistent with a planar cluster of C2v symmetry in which the second CO2 molecule binds in the second quadrupolar binding pocket on the opposite side of the ring. The calculated total binding energy in pyrimidine-CO2 is -13.7 kJ mol-1, including corrections for basis set superposition error and zero-point energy, at the CCSD(T)/ 6-311++G(3df,2p) level, while that in pyrimidine-(CO2)2 is almost exactly double that size, indicating little interaction between the two CO2 molecules in the two binding sites. The enthalpy, entropy, and free energy of binding are also calculated at 300 K within the harmonic oscillator/rigid-rotor model. This model is shown to lack quantitative accuracy when it is applied to the formation of weakly bound complexes.

Accelerating Pythonic Coupled-Cluster Implementations: A Comparison Between CPUs and GPUs

In this work, we benchmark several Python routines for time and memory requirements to identify the optimal choice of the tensor contraction operations available. We scrutinize how to accelerate the bottleneck tensor operations of Pythonic coupled-cluster implementations in the Cholesky linear algebra domain, utilizing a NVIDIA Tesla V100S PCIe 32GB (rev 1a) graphics processing unit (GPU). The NVIDIA compute unified device architecture API interacts with CuPy, an open-source library for Python, designed as a NumPy drop-in replacement for GPUs. Due to the limitations of video memory, the GPU calculations must be performed batch-wise. Timing results of some contractions containing large tensors are presented. The CuPy implementation leads to a factor of 10-16 speed-up of the bottleneck tensor contractions compared to computations on 36 central processing unit (CPU) cores. Finally, we compare example CCSD and pCCD-LCCSD calculations performed solely on CPUs to their CPU-GPU hybrid implementation, which leads to a speed-up of a factor of 3-4 compared to the CPU-only variant.

New Aspects of Alcohol-Alcohol and Alcohol-Water Interactions: Crystallographic and Quantum Chemical Studies of Antiparallel O-H/O-H Interactions

New modes of interaction, antiparallel O-H/O-H interactions of alcohol-alcohol dimers and alcohol-water dimers, were studied by analyzing data in the Cambridge Structural Database (CSD) and by calculating potential energy surfaces at a very accurate quantum chemical CCSD(T)/CBS level. The data reveal the existence of antiparallel interactions in crystal structures and significant interaction energies. Data from the CSD for alcohol-alcohol dimers show 49.2% of contacts with classical hydrogen bonds and 10.1% of contacts with antiparallel interactions, while for alcohol-water dimers, 59.4% of contacts are classical hydrogen bonds and only 0.6% of contacts are antiparallel interactions. The calculations were performed on methanol, ethanol, and n-propanol dimers. Classical hydrogen-bonded alcohol-alcohol and alcohol-water dimers have interaction energies of up to -6.2 kcal/mol and up to -5.5 kcal/mol, respectively. Antiparallel interactions in alcohol-alcohol and alcohol-water dimers have interaction energies of up to -4.7 kcal/mol and up to -4.4 kcal/mol, respectively. Symmetry-adapted perturbation theory analysis for antiparallel interactions shows their electrostatic nature.

All-Purpose Measure of Electron Correlation for Multireference Diagnostics

We present an analytical relationship between two natural orbital occupancy-based indices, I N D ¯ and INDmax, and two established electron correlation metrics: the leading term of a configuration interaction expansion, c0, and the D2 diagnostic. Numerical validation revealed that I N D ¯ and INDmax can effectively substitute for c0 and D2, respectively. These indices offer three distinct advantages: (i) they are universally applicable across all electronic structure methods, (ii) their interpretation is more intuitive, and (iii) they can be readily incorporated into the development of hybrid electronic structure methods. Additionally, we draw a distinction between correlation measures and correlation diagnostics, establishing MP2 and CCSD numerical thresholds for INDmax, which are to be used as a multireference diagnostic. Our findings further demonstrate that establishing thresholds for other electronic structure methods can be easily accomplished using small data sets.

Development and Comprehensive Benchmark of a High-Quality AMBER-Consistent Small Molecule Force Field with Broad Chemical Space Coverage for Molecular Modeling and Free Energy Calculation

Biomolecular simulations have become an essential tool in contemporary drug discovery, and molecular mechanics force fields (FFs) constitute its cornerstone. Developing a high quality and broad coverage general FF is a significant undertaking that requires substantial expert knowledge and computing resources, which is beyond the scope of general practitioners. Existing FFs originate from only a limited number of groups and organizations, and they either suffer from limited numbers of training sets, lower than desired quality because of oversimplified representations, or are costly for the molecular modeling community to access. To address these issues, in this work, we developed an AMBER-consistent small molecule FF with extensive chemical space coverage, and we provide Open Access parameters for the entire modeling community. To validate our FF, we carried out benchmarks of quantum mechanics (QM)/molecular mechanics conformer comparison and free energy perturbation calculations on several benchmark data sets. Our FF achieves a higher level of performance at reproducing QM energies and geometries than two popular open-source FFs, OpenFF2 and GAFF2. In relative binding free energy calculations for 31 protein-ligand data sets, comprising 1079 pairs of ligands, the new FF achieves an overall root-mean-square error of 1.19 kcal/mol for ΔΔG and 0.92 kcal/mol for ΔG on a subset of 463 ligands without bespoke fitting to the data sets. The results are on par with those of the leading commercial series of OPLS FFs.

Water Electric Field Induced Modulation of the Wetting of Hexagonal Boron Nitride: Insights from Multiscale Modeling of Many-Body Polarization

Understanding the behavior of water contacting two-dimensional materials, such as hexagonal boron nitride (hBN), is important in practical applications, including seawater desalination and energy harvesting. Water, being a polar solvent, can strongly polarize the hBN surface via the electric fields that it generates. However, there is a lack of molecular-level understanding about the role of polarization effects at the hBN/water interface, including its effect on the wetting properties of water. In this study, we develop a theoretical framework that introduces an all-atomistic polarizable force field to accurately model the interactions of water molecules with hBN surfaces. The force field is then utilized to self-consistently describe the water-induced polarization of hBN using the classical Drude oscillator model, including predicting the hBN-water binding energies which are found to be in excellent agreement with diffusion Monte Carlo (DMC) predictions. By carrying out molecular dynamics (MD) simulations, we demonstrate that the polarizable force field yields a water contact angle on multilayered hBN which is in close agreement with the recent experimentally reported values. Conversely, an implicit modeling of the hBN-water polarization energy utilizing a Lennard-Jones (LJ) potential, a commonly utilized approximation in previous MD simulation studies, leads to a considerably lower water contact angle. This difference in the predicted contact angles is attributed to the significant energy-entropy compensation resulting from the incorporation of polarization effects at the hBN-water interface. Our work highlights the importance of self-consistently modeling the hBN-water polarization energy and offers insights into the wetting-related interfacial phenomena of water on polarizable materials.

Benchmarking Swaths of Intermolecular Interaction Components with Symmetry-Adapted Perturbation Theory

A benchmark database for interaction energy components of various noncovalent interactions (NCIs) along their dissociation curve is one of the essential needs in theoretical chemistry, especially for the development of force fields and machine-learning methods. We utilize DFT-SAPT or SAPT(DFT) as one of the most accurate methods to generate an extensive stock of the energy components, including dispersion energies extrapolated to the complete basis set limit (CBS). Precise analyses of the created data, and benchmarking the total interaction energies against the best available CCSD(T)/CBS values, reveal different aspects of the methodology and the nature of NCIs. For example, error cancellation effects between the S2 approximation and nonexact xc-potentials occur, and large charge transfer energies in some systems, including heavy atoms, can explain the lower accuracy of DFT-SAPT. This method is perfect for neutral complexes containing light nonmetals, while other systems with heavier atoms should be treated carefully. In the last part, a representative data set for all NCIs is extracted from the original data.

Efficient and Parallel Implementation of Real and Complex Response Functions Employing the Second-Order Algebraic-Diagrammatic Construction Scheme for the Polarization Propagator

We present the implementation of an efficient matrix-folded formalism for the evaluation of complex response functions and the calculation of transition properties at the level of the second-order algebraic-diagrammatic construction (ADC(2)) scheme. The underlying algorithms, in combination with the adopted hybrid MPI/OpenMP parallelization strategy, enabled calculations of the UV/vis spectra of a guanine oligomer series ranging up to 1032 contracted basis functions, thereby utilizing vast computational resources from up to 32,768 CPU cores. Further analysis of the convergence behavior of the involved iterative subspace algorithms revealed the superiority of a frequency-separated treatment of response equations even for a large spectral window, including 101 frequencies. We demonstrate the applicability to general quantum mechanical operators by the first reported electronic circular dichroism spectrum calculated with a complex polarization propagator approach at the ADC(2) level of theory.

Assessing toxicity mechanism of silver nanoparticles by using brine shrimp (Artemia salina) as model

The acute toxicity of silver nanoparticles (AgNPs) in Artemia salina is primarily attributed to the interaction between silver ions (Ag+) and chitin, which constitutes the main structural component of the organism's cuticle. To investigate this interaction and gain a deeper understanding of its nature, geometric optimization calculations and symmetry-adapted perturbation theory (SAPT0) analysis were performed. These calculations aimed to determine the most favorable conformation based on the binding energies of silver ions with chitin and to elucidate the underlying mechanisms of their interaction. The results indicate an ionic effect dependent on the ion state, with simulations revealing that Ag3+ ions have the potential to cause significant deformation of the chitin structure. Furthermore, this study evaluated the behavior of AgNPs using nauplii of A. salina instar I, assessing both mortality rates and cell damage. Toxicity of AgNPs was observed in A. salina at concentrations of 50 and 100 ppm within a timeframe of 24-48 h. The toxicity of AgNPs can be attributed to their interaction with the cuticle and subsequent modification of the chitin structure through the binding of ionic silver. Light microscopy (LM) analysis confirmed the presence of AgNPs in the cuticle, while confocal laser scanning microscopy (CLSM) revealed cellular damage. In addition, this research offers new perspectives on the toxicity mechanism of AgNPs by introducing a novel model that explores the interaction of silver ions with the cuticle of A. salina. These insights are derived from a combination of atomistic models and ecotoxicology assays.

De novo design of drug-binding proteins with predictable binding energy and specificity

The de novo design of small-molecule-binding proteins has seen exciting recent progress; however, the ability to achieve exquisite affinity for binding small molecules while tuning specificity has not yet been demonstrated directly from computation. Here, we develop a computational procedure that results in the highest affinity binders to date with predetermined relative affinities, targeting a series of PARP1 inhibitors. Two of four designed proteins bound with affinities ranging from < 5 nM to low μM, in a predictable manner. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free-energy calculations performed directly on the designed models are in excellent agreement with the experimentally measured affinities, suggesting that the de novo design of small-molecule-binding proteins with tuned interaction energies is now feasible entirely from computation. We expect these methods to open many opportunities in biomedicine, including rapid sensor development, antidote design, and drug delivery vehicles.

Insight into the Binding of Argon to Cyclic Water Clusters from Symmetry-Adapted Perturbation Theory

This work systematically examines the interactions between a single argon atom and the edges and faces of cyclic H2O clusters containing three-five water molecules (Ar(H2O)n=3-5). Full geometry optimizations and subsequent harmonic vibrational frequency computations were performed using MP2 with a triple-ζ correlation consistent basis set augmented with diffuse functions on the heavy atoms (cc-pVTZ for H and aug-cc-pVTZ for O and Ar; denoted as haTZ). Optimized structures and harmonic vibrational frequencies were also obtained with the two-body-many-body (2b:Mb) and three-body-many-body (3b:Mb) techniques; here, high-level CCSD(T) computations capture up through the two-body or three-body contributions from the many-body expansion, respectively, while less demanding MP2 computations recover all higher-order contributions. Five unique stationary points have been identified in which Ar binds to the cyclic water trimer, along with four for (H2O)4 and three for (H2O)5. To the best of our knowledge, eleven of these twelve structures have been characterized here for the first time. Ar consistently binds more strongly to the faces than the edges of the cyclic (H2O)n clusters, by as much as a factor of two. The 3b:Mb electronic energies computed with the haTZ basis set indicate that Ar binds to the faces of the water clusters by at least 3 kJ mol-1 and by nearly 6 kJ mol-1 for one Ar(H2O)5 complex. An analysis of the interaction energies for the different binding motifs based on symmetry-adapted perturbation theory (SAPT) indicates that dispersion interactions are primarily responsible for the observed trends. The binding of a single Ar atom to a face of these cyclic water clusters can induce perturbations to the harmonic vibrational frequencies on the order of 5 cm-1 for some hydrogen-bonded OH stretching frequencies.

Theoretical study to gain fundamental insight into reaction mechanism of N-S acyl transfer of N-sulfanylethylanilide-based protein labeling reagent on protein surface

Elucidation of protein function is one of the central issues in the field of life sciences. To study the function of proteins not in isolation, but in a cell or its lysate, thus, it is necessary to selectively label the target protein in a mixture. Affinity labeling is one of several widely used methods for selective labeling; however, this method has the disadvantage that the labeling reagent is always activated, albeit weakly. Therefore, fine-tuning of the reactivity and/or reaction conditions is generally required for successful target-selective labeling. We previously developed a new affinity labeling reagent with N-sulfanylethylanilide (SEAlide) as a key reactive unit. It was designed based on the following hypotheses. SEAlide is less reactive and does not label in the absence of a target protein. Upon target binding, amino acid side-chain functional groups on the target surface convert SEAlide into a thioester form via N-S acyl transfer, allowing the target to be labeled. However, no evidence has been obtained so far to directly prove the hypothesis. In this study, we examine whether amino acid side-chain functional groups can activate SEAlide from the viewpoint of theoretical chemistry. The theoretical studies show that the activation free energy and enthalpy of the acyl transfer of SEAlide are reduced in the presence of methylammonium, which is a model for the protonated side chain of Lys, and acetate, which is a model for the deprotonated side chain of Asp/Glu. It suggests that Lys and Asp/Glu side chains could potentially stabilize the activation transition states to accelerate the thioester formation. Furthermore, the significant decrease in the activation enthalpy indicates that the contribution of entropy to the transition state is large. This result supports the original hypothesis that the SEAlide-based labeling reagent is efficiently activated by binding to the target protein.

Hole interactions of aerogen oxides with Lewis bases: an insight into σ-hole and lone-pair-hole interactions

σ-Hole and lone-pair (lp)-hole interactions of aerogen oxides with Lewis bases (LB) were comparatively inspected in terms of quantum mechanics calculations. The ZOn ⋯ LB complexes (where Z = Kr and Xe, n = 1, 2, 3 and 4, and LB = NH3 and NCH) showed favourable negative interaction energies. The complexation features were explained in light of σ-hole and lp-hole interactions within optimum distances lower than the sum of the respective van der Waals radii. The emerging findings outlined that σ-hole interaction energies generally enhanced according to the following order: KrO4 ⋯ < KrO⋯ < KrO3⋯ < KrO2⋯LB and XeO4⋯ < XeO⋯ < XeO2⋯ < XeO3⋯LB complexes with values ranging from -2.23 to -12.84 kcal mol-1. Lp-hole interactions with values up to -5.91 kcal mol-1 were shown. Symmetry-adapted perturbation theory findings revealed the significant contributions of electrostatic forces accounting for 50-65% of the total attractive forces within most of the ZOn⋯LB complexes. The obtained observations would be useful for the understanding of hole interactions, particularly for the aerogen oxides, with application in supramolecular chemistry and crystal engineering.

AutoParams: An Automated Web-Based Tool To Generate Force Field Parameters for Molecular Dynamics Simulations

Many research questions benefit from molecular dynamics simulations to observe the motions and conformations of molecules over time, which rely on force fields that describe sets of common molecules by category. With the increase of importance for large data sets used in machine learning and growing computational efficiency, the ability to rapidly create large numbers of force field inputs is of high importance. Unusual molecules, such as nucleotide analogues, functionalized carbohydrates, and modified amino acids, are difficult to describe consistently using standard force fields, requiring the development of custom parameters for each unique molecule. While these parameters may be created by individual users, the process can become time-consuming or may introduce errors that may not be immediately apparent. We present an open-source automated parameter generation service, AutoParams, which requires minimal input from the user and creates useful Amber force field parameter sets for most molecules, particularly those that combine molecular types (e.g., a carbohydrate functionalized with a benzene). We include hierarchical atom-typing logic that makes it straightforward to expand with additional force fields and settings, and options for creating monomers in polymers, such as functionalized amino acids. It can be straightforwardly linked to any charge generation program and currently has interfaces to Psi4, PsiRESP, and TeraChem. It is open source and is available via GitHub. It includes error checking and testing protocols to ensure the parameters will be sufficient for subsequent molecular dynamics simulations and streamlines the creation of force field databases.

Conformational equilibria and interaction preference in the complex of isoprene-maleic anhydride

The rotational spectrum of the isoprene-maleic anhydride complex has been investigated by pulsed jet Fourier transform microwave spectroscopy and interpreted with complementary quantum chemical calculations. Theoretical predictions have yielded four plausible isomers, all residing within an energy window of 12 kJ mol-1. However, two distinct isomers characterized by a π-π stacked configuration have been experimentally observed in pulsed jets, which have differed in the orientation of isoprene over maleic anhydride. The relative population ratio of the two detected isomers has been estimated to be NI/NII ≈ 3/1 from rigorous measurements of the relative intensity on a set of μc-type transitions. Remarkably, this study underscores the pivotal role played by the interaction between the CC bonding orbital (π) of isoprene and the CC antibonding orbital (π*) of maleic anhydride in stabilizing the target complex.

Development of scalable and generalizable machine learned force field for polymers

Understanding and predicting the properties of polymers is vital to developing tailored polymer molecules for desired applications. Classical force fields may fail to capture key properties, for example, the transport properties of certain polymer systems such as polyethylene glycol. As a solution, we present an alternative potential energy surface, a charge recursive neural network (QRNN) model trained on DFT calculations made on smaller atomic clusters that generalizes well to oligomers comprising larger atomic clusters or longer chains. We demonstrate the validity of the polymer QRNN workflow by modeling the oligomers of ethylene glycol. We apply two rounds of active learning (addition of new training clusters based on current model performance) and implement a novel model training approach that uses partial charges from a semi-empirical method. Our developed QRNN model for polymers produces stable molecular dynamics (MD) simulation trajectory and captures the dynamics of polymer chains as indicated by the striking agreement with experimental values. Our model allows working on much larger systems than allowed by DFT simulations, at the same time providing a more accurate force field than classical force fields which provides a promising avenue for large-scale molecular simulations of polymeric systems.

Growth Reduction of Similarity-Transformed Electronic Hamiltonians in Qubit Space

Accurately solving the electronic structure problem through the variational quantum eigensolver (VQE) is hindered by the available quantum resources of current and near-term devices. One approach to relieving the circuit depth requirements for VQE is to "pre-process" the electronic Hamiltonian by a similarity transformation incorporating some degree of electronic correlation, with the remaining correlation left to be addressed by the circuit ansatz. This often comes at the price of a substantial increase in the number of terms to measure in the similarity-transformed Hamiltonian. In this work, we propose an efficient approach to sampling elements from the complete Pauli group for N qubits which minimizes the onset of new terms in the transformed Hamiltonian while facilitating substantial energy lowering. We benchmark the growth-mitigating generator selection technique for ground state energy estimations applied to models of the H4, N2, and H2O molecular systems. It is found that utilizing a selection procedure which obtains the growth-minimizing generator from the set of operators with the maximal energy gradient is the most competitive approach to reducing the onset of Hamiltonian terms while achieving systematic energy lowering of the reference state.

DASH: Dynamic Attention-Based Substructure Hierarchy for Partial Charge Assignment

We present a robust and computationally efficient approach for assigning partial charges of atoms in molecules. The method is based on a hierarchical tree constructed from attention values extracted from a graph neural network (GNN), which was trained to predict atomic partial charges from accurate quantum-mechanical (QM) calculations. The resulting dynamic attention-based substructure hierarchy (DASH) approach provides fast assignment of partial charges with the same accuracy as the GNN itself, is software-independent, and can easily be integrated in existing parametrization pipelines, as shown for the Open force field (OpenFF). The implementation of the DASH workflow, the final DASH tree, and the training set are available as open source/open data from public repositories.

Deciphering the non-covalent interactions in the furan⋯hexane complex using rotational spectroscopy and theoretical analyses

The rotational spectrum of a binary complex formed between furan and n-hexane was investigated using a chirped pulse Fourier transform microwave spectrometer in the range of 2-6 GHz. While furan has only one conformer, n-hexane exists in multiple conformations. The conformational landscape of the binary complex was systematically explored by using a semiempirical conformational search tool, namely CREST. The CREST conformational candidates were subjected to further geometry optimization and harmonic frequency calculations at the B3LYP-D3BJ/def2-TZVP level of theory, resulting in 34 minima within an energy window of 5 kJ mol-1. The three most stable furan⋯hexane minima all contain the most stable n-hexane conformer subunit and are separated by relatively low conformational conversion barriers. Additional calculations were carried out to support the conclusive identification of the global minimum structure responsible for the set of assigned rotational transitions. These include calculations at the B3LYP-D3BJ level with the aug-cc-pVTZ and 6-311++G(d,p) basis sets and the MP2/def2-TZVP level, as well as the single point energy calculations at the CCSD(T)-F12/cc-pVDZ level. Further non-covalent interaction and principal interacting orbital analyses show that the synergy of the πfuran → σ*hexane and σhexane → π*furan interactions plays an important role in stabilizing the observed furan-hexane conformer.

Combination of High-Throughput Screening and Assembly to Discover Efficient Metal-Organic Frameworks on Kr/Xe Adsorption Separation

Recycling Kr and Xe from used nuclear fuel (UNF) is conducive to regenerating economy and protecting the environment, and it is urgent to screen or design high-performance cutting-edge metal-organic framework (MOF) materials for Kr/Xe adsorption separation. After grand canonical Monte Carlo (GCMC) simulations of Kr/Xe adsorption separation on 11,000 frameworks in CoRE MOFs (2019), the important structure-adsorption property relationship (SAPR) was induced; that is, the porosity (φ) at 0.30-0.40, LCD/PLD at 1.00-1.49, density (ρ) range between 1.20 and 2.30 g/cm3, and PLD at 2.40-3.38 Å can be utilized to screen for high-performance G-MOFs and hMOFs. In addition, the key "genes" (metal nodes and linkers) of MOFs determining the Kr/Xe adsorption separation were data-mined by a machine learning technique, which were assembled into novel MOFs. After comprehensive consideration of thermal stability and the adsorbent performance score (APS), eight promising MOFs on Kr/Xe separation with the APS more than 1290.89 were screened out and assembled, which are better than most of the reported frameworks. Note that the adsorption isotherms of these MOFs on Kr and Xe belong to type I curve with the thermodynamic equilibrium mechanism on Kr/Xe based on the confinement effect. Furthermore, according to the electronic structure calculations of the independent gradient model based on Hirshfeld partition (IGMH) and energy decomposition analysis, it is found that the interactions between guests and frameworks are vdW forces with dominant induction energy (Eind). In addition, the electrostatic potential gradients of frameworks are generally linearly negative correlated with Kr uptakes. Therefore, both the geometrical and electronic structures dominate the adsorption separation performance on Kr/Xe. Interestingly, these eight MOFs are also suitable for the separation of CH4/H2 with considerable selectivities and CH4 uptakes of up to 2566.67 and 3.04 mmol/g, respectively. Herein, the accurately constructed SAPR and material genomics strategy should be helpful for the experimental discovery of novel MOFs on Kr/Xe separation experimentally.

Strong Be-N Interaction Induced Complementary Chemical Tuning to Design a Dual-gated Single Molecule Junction

The interaction between pyridines and the π-hole of BeH2 leads to the formation of strong beryllium-bonded complexes. Theoretical investigations demonstrate that the Be-N bonding interaction can effectively regulate the electronic current through a molecular junction. The electronic conductance exhibits distinct switching behavior depending on the substituent groups at the para position of pyridine, highlighting the role of Be-N interaction as a potent chemical gate in the proposed device. The complexes exhibit short intermolecular distances ranging from 1.724 to 1.752 Å, emphasizing their strong binding. Detailed analysis of electronic rearrangements and geometric perturbations upon complex formation provides insights into the underlying reasons for the formation of such strong Be-N bonds, with bond strengths varying from -116.25 to -92.96 kJ/mol. Moreover, the influence of chemical substituents on the local electronic transmission of the beryllium-bonded complex offers valuable insights for the implementation of a secondary chemical gate in single-molecule devices. This study paves the way for the development of chemically gateable, functional single-molecule transistors, advancing the design and fabrication of multifunctional single-molecule devices in the nanoscale regime.

Sigma-Hole and Lone-Pair-Hole Site-Based Interactions of Seesaw Tetravalent Chalcogen-Bearing Molecules with Lewis Bases

For the first time, sigma (σ)- and lone-pair (lp)-hole site-based interactions of SF4 and SeF4 molecules in seesaw geometry with NH3 and FH Lewis bases were herein comparatively investigated. The obtained findings from the electrostatic potential analysis outlined the emergence of sundry holes on the molecular entity of the SF4 and SeF4 molecules, dubbed the σ- and lp-holes. The energetic viewpoint announced splendid negative binding energy values for σ-hole site-based interactions succeeded by lp-hole analogues, which were found to be -9.21 and -0.50 kcal/mol, respectively, for SeF4···NH3 complex as a case study. Conspicuously, a proper concurrence between the strength of chalcogen σ-hole site-based interactions and the chalcogen's atomic size was obtained, whereas a reverse pattern was proclaimed for the lp-hole counterparts. Further, a higher preference for the YF4···NH3 complexes with elevated negative binding energy was promulgated over the YF4···FH ones, indicating the eminent role of Lewis basicity. The indications of the quantum theory of atoms in molecules generally asserted the closed-shell nature of all the considered interactions. The observation of symmetry-adapted perturbation theory revealed the substantial contributing role of the electrostatic forces beyond the occurrence of σ-hole site-based interactions. In comparison, the dispersion forces were specified to govern the lp-hole counterparts. Such emerging findings would be a gate for the fruitful forthcoming applications of chalcogen bonding interactions in crystal engineering and biological systems.

Application of a Fluctuating Charge Polarization Model to Large Polyaromatic Hydrocarbons and Graphene Nanoflakes

We present a polarization model incorporating coupled fluctuating charges and point inducible dipoles that is able to accurately describe the dipole polarizabilities of small hydrocarbons and, for sufficiently large graphene nanoflakes, reproduce the classical image potential of an infinite conducting sheet. When our fluctuating charge model is applied to the hexagonal carbon nanoflake C60000 we attain excellent agreement with the image potential and induced charge distribution of a conducting sheet. With the inclusion of inducible dipole terms, the model predicts an image plane of zim = 1.3334 a0, which falls in line with prior estimates for graphene. We consider the case of two charges placed on opposite sides of C60000 and find that the fluctuating charge model reproduces classical electrostatics once again. By testing opposing and similar signs of the external charges, we conclude that an atomically thin molecule or extended system does not fully screen their interaction.

Halogen Bonding Involving Isomeric Isocyanide/Nitrile Groups

2,3,5,6-Tetramethyl-1,4-diisocyanobenzene (1), 1,4-diisocyanobenzene (2), and 1,4-dicyanobenzene (3) were co-crystallized with 1,3,5-triiodotrifluorobenzene (1,3,5-FIB) to give three cocrystals, 1·1,3,5-FIB, 2·2(1,3,5-FIB), and 3·2(1,3,5-FIB), which were studied by X-ray diffraction. A common feature of the three structures is the presence of I···Cisocyanide or I···Nnitrile halogen bonds (HaBs), which occurs between an iodine σ-hole and the isocyanide C-(or the nitrile N-) atom. The diisocyanide and dinitrile cocrystals 2·2(1,3,5-FIB) and 3·2(1,3,5-FIB) are isostructural, thus providing a basis for accurate comparison of the two types of noncovalent linkages of C≡N/N≡C groups in the composition of structurally similar entities and in one crystal environment. The bonding situation was studied by a set of theoretical methods. Diisocyanides are more nucleophilic than the dinitrile and they exhibit stronger binding to 1,3,5-FIB. In all structures, the HaBs are mostly determined by the electrostatic interactions, but the dispersion and induction components also provide a noticeable contribution and make the HaBs attractive. Charge transfer has a small contribution (<5%) to the HaB and it is higher for the diisocyanide than for the dinitrile systems. At the same time, diisocyanide and dinitrile structures exhibit typical electron-donor and π-acceptor properties in relation to the HaB donor.

Open-Source Machine Learning in Computational Chemistry

The field of computational chemistry has seen a significant increase in the integration of machine learning concepts and algorithms. In this Perspective, we surveyed 179 open-source software projects, with corresponding peer-reviewed papers published within the last 5 years, to better understand the topics within the field being investigated by machine learning approaches. For each project, we provide a short description, the link to the code, the accompanying license type, and whether the training data and resulting models are made publicly available. Based on those deposited in GitHub repositories, the most popular employed Python libraries are identified. We hope that this survey will serve as a resource to learn about machine learning or specific architectures thereof by identifying accessible codes with accompanying papers on a topic basis. To this end, we also include computational chemistry open-source software for generating training data and fundamental Python libraries for machine learning. Based on our observations and considering the three pillars of collaborative machine learning work, open data, open source (code), and open models, we provide some suggestions to the community.

AMOEBA Force Field Predicts Accurate Hydrogen Bond Counts of Nitriles in SNase by Revealing Water-Protein Interaction in Vibrational Absorption Frequencies

Precisely quantifying the magnitude and direction of electric fields in proteins has long been an outstanding challenge in understanding biological functions. Nitrile vibrational Stark effect probes have been shown to be minimally disruptive to the protein structure and can be better direct reporters of local electrostatic field in the native state of a protein than other measures such as pKa shifts of titratable residues. However, interpretations of the connection between measured vibrational energy and electric field rely on the accurate molecular understanding of interactions of the nitrile group and its environment, particularly from hydrogen bonding. In this work, we compared the extent of hydrogen bonding calculated in two common force fields, the fixed charge force field Amber03 and polarizable force field AMOEBA, at 10 locations of cyanocysteine (CNC) in staphylococcal nuclease (SNase) against the experimental nitrile absorption frequency in terms of full width at half-maximum (FWHM) and frequency temperature line slope (FTLS). We observed that the number of hydrogen bonds correlated well in AMOEBA trajectories with respect to both the FWHM (r = 0.88) and the FTLS (r = -0.85), whereas the correlation of Amber03 trajectories was less reliable because the Amber03 force field predicted more hydrogen bonds in some mutants. Moreover, we demonstrated that contributions from the interactions between CNC and nearby water molecules were significant in AMOEBA trajectories but were not predicted by Amber03. We conclude that although the nitrile absorption peak shape could be qualitatively predicted by the fixed charge Amber03 force field, the detailed electrostatic environment measured by the nitrile probe in terms of the extent of hydrogen bonding could only be accurately observed in the AMOEBA trajectories, where the permanent dipole, quadrupole, and dipole-induced-dipole polarizable interactions were all taken into account. The significance of this finding to the goal of accurately predicting electric fields in complex biomolecular environments is discussed.

Free Energy Calculations and Conformational Analysis of Dibenzo-30-crown-10 with Sm2+, Eu2+, and Three Halide Salts in THF Using the AMOEBA Force Field

Crown ether complexes have been tailored for use in industrial separations of lanthanides (Ln) as a part of rare earth mining and refining. Dibenzo-30-crown-10 (DB30C10) is one of the most efficient complexants for the separation of rare earth mixtures based on the cation size. To understand the origin of this complexation, molecular dynamics (MD) simulations of DB30C10 have been performed using different combinations of divalent Sm and Eu and three halide salts Cl^-, Br^-, and I^- in tetrahydrofuran (THF) solvent. DB30C10 was parameterized here for the polarizable atomic multipole optimized energetics for biomolecular simulation (AMOEBA) force field, and the existing parameters of THF, Sm²⁺, and Eu²⁺ were employed from our previous efforts. The large conformational fluctuations present in the DB30C10 systems were found to be dependent both on the identity of the lanthanide and halide complexes. For Cl^- and Br^- systems, there were no observed conformational changes at 200 ns, while in I^- systems, there were two conformational changes with Sm²⁺ and one with Eu²⁺ within that same timeframe. In SmI₂-DB30C10, there were three stages of conformational changes. In the first stage, the molecule is unfolded, in the second stage, the molecule is partly folded, and finally, in the third stage, the molecule is completely folded. Lastly, the Gibbs binding free energies of DB30C10 with SmBr₂ and EuBr₂ have been computed, which resulted in nearly identical ΔG_comp values for each lanthanide with Sm²⁺ being slightly more favorable. Considering the folding mechanism of the SmI₂ system with DB30C10, the Gibbs binding free energies of DB30C10 and dicyclohexano-18-crown-6 (DCH18C6) with SmI₂ were calculated separately and compared to probe their complexation affinities, in which the former was found to be more favorable.

Development and Benchmarking of Open Force Field 2.0.0: The Sage Small Molecule Force Field

We introduce the Open Force Field (OpenFF) 2.0.0 small molecule force field for drug-like molecules, code-named Sage, which builds upon our previous iteration, Parsley. OpenFF force fields are based on direct chemical perception, which generalizes easily to highly diverse sets of chemistries based on substructure queries. Like the previous OpenFF iterations, the Sage generation of OpenFF force fields was validated in protein-ligand simulations to be compatible with AMBER biopolymer force fields. In this work, we detail the methodology used to develop this force field, as well as the innovations and improvements introduced since the release of Parsley 1.0.0. One particularly significant feature of Sage is a set of improved Lennard-Jones (LJ) parameters retrained against condensed phase mixture data, the first refit of LJ parameters in the OpenFF small molecule force field line. Sage also includes valence parameters refit to a larger database of quantum chemical calculations than previous versions, as well as improvements in how this fitting is performed. Force field benchmarks show improvements in general metrics of performance against quantum chemistry reference data such as root-mean-square deviations (RMSD) of optimized conformer geometries, torsion fingerprint deviations (TFD), and improved relative conformer energetics (ΔΔE). We present a variety of benchmarks for these metrics against our previous force fields as well as in some cases other small molecule force fields. Sage also demonstrates improved performance in estimating physical properties, including comparison against experimental data from various thermodynamic databases for small molecule properties such as ΔHmix, ρ(x), ΔGsolv, and ΔGtrans. Additionally, we benchmarked against protein-ligand binding free energies (ΔGbind), where Sage yields results statistically similar to previous force fields. All the data is made publicly available along with complete details on how to reproduce the training results at https://github.com/openforcefield/openff-sage.

Single-Point Extrapolation to the Complete Basis Set Limit through Deep Learning

Machine learning (ML) offers an attractive method for making predictions about molecular systems while circumventing the need to run expensive electronic structure calculations. Once trained on ab initio data, the promise of ML is to deliver accurate predictions of molecular properties that were previously computationally infeasible. In this work, we develop and train a graph neural network model to correct the basis set incompleteness error (BSIE) between a small and large basis set at the RHF and B3LYP levels of theory. Our results show that, when compared to fitting to the total potential, an ML model fitted to correct the BSIE is better at generalizing to systems not seen during training. We test this ability by training on single molecules while evaluating on molecular complexes. We also show that ensemble models yield better behaved potentials in situations where the training data is insufficient. However, even when only fitting to the BSIE, acceptable performance is only achieved when the training data sufficiently resemble the systems one wants to make predictions on. The test error of the final model trained to predict the difference between the cc-pVDZ and cc-pV5Z potential is 0.184 kcal/mol for the B3LYP density functional, and the ensemble model accurately reproduces the large basis set interaction energy curves on the S66x8 dataset.