Directional ΔG Neural Network (DrΔG-Net): A Modular Neural Network Approach to Binding Free Energy Prediction

The protein-ligand binding free energy is a central quantity in structure-based computational drug discovery efforts. Although popular alchemical methods provide sound statistical means of computing the binding free energy of a large breadth of systems, they are generally too costly to be applied at the same frequency as end point or ligand-based methods. By contrast, these data-driven approaches are typically fast enough to address thousands of systems but with reduced transferability to unseen systems. We introduce DrΔG-Net (or simply Dragnet), an equivariant graph neural network that can blend ligand-based and protein-ligand data-driven approaches. It is based on a 3D fingerprint representation of the ligand alone and in complex with the protein target. Dragnet is a global scoring function to predict the binding affinity of arbitrary protein-ligand complexes, but can be easily tuned via transfer learning to specific systems or end points, performing similarly to common 2D ligand-based approaches in these tasks. Dragnet is evaluated on a total of 28 validation proteins with a set of congeneric ligands derived from the Binding DB and one custom set extracted from the ChEMBL Database. In general, a handful of experimental binding affinities are sufficient to optimize the scoring function for a particular protein and ligand scaffold. When not available, predictions from physics-based methods such as absolute free energy perturbation can be used for the transfer learning tuning of Dragnet. Furthermore, we use our data to illustrate the present limitations of data-driven modeling of binding free energy predictions.

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

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

Approximating large-basis coupled-cluster theory vibrational frequencies using focal-point approximations

The focal-point approximation can be used to estimate a high-accuracy, slow quantum chemistry computation by combining several lower-accuracy, faster computations. We examine the performance of focal-point methods by combining second-order Møller-Plesset perturbation theory (MP2) with coupled-cluster singles, doubles, and perturbative triples [CCSD(T)] for the calculation of harmonic frequencies and that of fundamental frequencies using second-order vibrational perturbation theory (VPT2). In contrast to standard CCSD(T), the focal-point CCSD(T) method approaches the complete basis set (CBS) limit with only triple-ζ basis sets for the coupled-cluster portion of the computation. The predicted harmonic and fundamental frequencies were compared with the experimental values for a set of 20 molecules containing up to six atoms. The focal-point method combining CCSD(T)/aug-cc-pV(T + d)Z with CBS-extrapolated MP2 has mean absolute errors vs experiment of only 7.3 cm-1 for the fundamental frequencies, which are essentially the same as the mean absolute error for CCSD(T) extrapolated to the CBS limit using the aug-cc-pV(Q + d)Z and aug-cc-pV(5 + d)Z basis sets. However, for H2O, the focal-point procedure requires only 3% of the computation time as the extrapolated CCSD(T) result, and the cost savings will grow for larger molecules.

A quantitative assessment of deformation energy in intermolecular interactions: How important is it?

Dimer interaction energies have been well studied in computational chemistry, but they can offer an incomplete understanding of molecular binding depending on the system. In the current study, we present a dataset of focal-point coupled-cluster interaction and deformation energies (summing to binding energies, De) of 28 organic molecular dimers. We use these highly accurate energies to evaluate ten density functional approximations for their accuracy. The best performing method (with a double-ζ basis set), B97M-D3BJ, is then used to calculate the binding energies of 104 organic dimers, and we analyze the influence of the nature and strength of interaction on deformation energies. Deformation energies can be as large as 50% of the dimer interaction energy, especially when hydrogen bonding is present. In most cases, two or more hydrogen bonds present in a dimer correspond to an interaction energy of -10 to -25 kcal mol-1, allowing a deformation energy above 1 kcal mol-1 (and up to 9.5 kcal mol-1). A lack of hydrogen bonding usually restricts the deformation energy to below 1 kcal mol-1 due to the weaker interaction energy.

Benchmark coupled-cluster lattice energy of crystalline benzene and assessment of multi-level approximations in the many-body expansion

The many-body expansion (MBE) is promising for the efficient, parallel computation of lattice energies in organic crystals. Very high accuracy should be achievable by employing coupled-cluster singles, doubles, and perturbative triples at the complete basis set limit [CCSD(T)/CBS] for the dimers, trimers, and potentially tetramers resulting from the MBE, but such a brute-force approach seems impractical for crystals of all but the smallest molecules. Here, we investigate hybrid or multi-level approaches that employ CCSD(T)/CBS only for the closest dimers and trimers and utilize much faster methods like Møller-Plesset perturbation theory (MP2) for more distant dimers and trimers. For trimers, MP2 is supplemented with the Axilrod-Teller-Muto (ATM) model of three-body dispersion. MP2(+ATM) is shown to be a very effective replacement for CCSD(T)/CBS for all but the closest dimers and trimers. A limited investigation of tetramers using CCSD(T)/CBS suggests that the four-body contribution is entirely negligible. The large set of CCSD(T)/CBS dimer and trimer data should be valuable in benchmarking approximate methods for molecular crystals and allows us to see that a literature estimate of the core-valence contribution of the closest dimers to the lattice energy using just MP2 was overbinding by 0.5 kJ mol-1, and an estimate of the three-body contribution from the closest trimers using the T0 approximation in local CCSD(T) was underbinding by 0.7 kJ mol-1. Our CCSD(T)/CBS best estimate of the 0 K lattice energy is -54.01 kJ mol-1, compared to an estimated experimental value of -55.3 ± 2.2 kJ mol-1.

High-Order Quantum-Mechanical Analysis of Hydrogen Bonding in Hachimoji and Natural DNA Base Pairs

High-order quantum chemistry is applied to hydrogen-bonded natural DNA nucleobase pairs [adenine:thymine (A:T) and guanine:cytosine (G:C)] and non-natural Hachimoji nucleobase pairs [isoguanine:1-methylcytosine (B:S) and 2-aminoimidazo[1,2a][1,3,5]triazin-4(1H)-one:6-amino-5-nitropyridin-2-one (P:Z)] to see how the intermolecular interaction energies and their energetic components (electrostatics, exchange-repulsion, induction/polarization, and London dispersion interactions) vary among the base pairs. We examined the Hoogsteen (HG) geometries in addition to the traditional Watson-Crick (WC) geometries. Coupled-cluster theory through perturbative triples [CCSD(T)] extrapolated to the complete basis set (CBS) limit and high-order symmetry-adapted perturbation theory (SAPT) at the SAPT2+(3)(CCD)δMP2/aug-cc-pVTZ level are used to estimate highly accurate noncovalent interaction energies. Electrostatic interactions are the most attractive component of the interaction energies, but the sum of induction/polarization and London dispersion is nearly as large, for all base pairs and geometries considered. Interestingly, the non-natural Hachimoji base pairs interact more strongly than the corresponding natural base pairs, by -21.8 (B:S) and -0.3 (P:Z) kcal mol^-1 in the WC geometries, according to CCSD(T)/CBS. This is consistent with the H-bond distances being generally shorter in the non-natural base pairs. The natural base pairs are energetically more stabilized in their Hoogsteen geometries than in their WC geometries. The Hoogsteen geometry makes the A:T base pair slightly more stable, by -0.8 kcal mol^-1, and it greatly stabilizes the G:C⁺ base pair, by -15.3 kcal mol^-1. The G:C⁺ stabilization is mainly due to the fact that C has typically added a proton when found in Hoogsteen geometries. By contrast, Hoogsteen geometries are substantially less favorable than WC geometries for non-natural Hachimoji base pairs, by 17.3 (B:S) and 13.8 (P:Z) kcal mol^-1.

Assessment of three-body dispersion models against coupled-cluster benchmarks for crystalline benzene, carbon dioxide, and triazine

To study the contribution of three-body dispersion to crystal lattice energies, we compute the three-body contributions to the lattice energies for crystalline benzene, carbon dioxide, and triazine using various computational methods. We show that these contributions converge quickly as the intermolecular distances between the monomers grow. In particular, the smallest value among the three pairwise intermonomer closest-contact distances, R_min, shows a strong correlation with the three-body contribution to the lattice energy, and, here, the largest of the closest-contact distances, R_max, serves as a cutoff criterion to limit the number of trimers to be considered. We considered all trimers up to R_max=15Å. The trimers with R_min<4Å contribute 90.4%, 90.6%, and 93.9% of the total three-body contributions for crystalline benzene, carbon dioxide, and triazine, respectively, for the coupled-cluster singles, doubles, and perturbative triples [CCSD(T)] method. For trimers with R_min>4Å, the second-order Møller-Plesset perturbation theory (MP2) supplemented with the Axilrod-Teller-Muto (ATM) three-body dispersion correction reproduces the CCSD(T) values for the cumulative three-body contributions with errors of less than 0.1 kJ mol^-1. Moreover, three-body contributions are converged within 0.15 kJ mol^-1 by R_max=10Å. From these results, it appears that in molecular crystals where dispersion dominates the three-body contribution to the lattice energy, the trimers with R_min>4Å can be computed with the MP2+ATM method to reduce the computational cost, and those with R_max>10Å appear to be basically negligible.

Benchmarking two-body contributions to crystal lattice energies and a range-dependent assessment of approximate methods

Using the many-body expansion to predict crystal lattice energies (CLEs), a pleasantly parallel process, allows for flexibility in the choice of theoretical methods. Benchmark-level two-body contributions to CLEs of 23 molecular crystals have been computed using interaction energies of dimers with minimum inter-monomer separations (i.e., closest contact distances) up to 30 Å. In a search for ways to reduce the computational expense of calculating accurate CLEs, we have computed these two-body contributions with 15 different quantum chemical levels of theory and compared these energies to those computed with coupled-cluster in the complete basis set (CBS) limit. Interaction energies of the more distant dimers are easier to compute accurately and several of the methods tested are suitable as replacements for coupled-cluster through perturbative triples for all but the closest dimers. For our dataset, sub-kJ mol^-1 accuracy can be obtained when calculating two-body interaction energies of dimers with separations shorter than 4 Å with coupled-cluster with single, double, and perturbative triple excitations/CBS and dimers with separations longer than 4 Å with MP2.5/aug-cc-pVDZ, among other schemes, reducing the number of dimers to be computed with coupled-cluster by as much as 98%.

A nonconjugated radical polymer with stable red luminescence in the solid state

Organic radicals are unstable and stable radicals usually display non-luminescent properties. Luminescent radicals possess the all-in-one properties of optoelectronics, electronics, and magnetics. To date, the reported structures of luminescent radicals are limited to triphenylmethyl radical derivatives and their analogues, which are stabilized with extended π-conjugation. Here, we demonstrate the first example of a nonconjugated luminescent radical. In spite of the lack of delocalized π-stabilization, the radical polymer readily emits red luminescence in the solid state. A traditional luminescent quencher, 2,2,6,6-tetramethylpiperidin-1-yl turned into a red chromophore when grafted onto a polymer backbone. Experimental data confirm that the emission is associated with the nitroxide radicals and is also affected by the packing of the polymer. This work discloses a novel class of luminescent radicals and a distinctive pathway for luminescence from open-shell materials.

Range-dependence of two-body intermolecular interactions and their energy components in molecular crystals

Routinely assessing the stability of molecular crystals with high accuracy remains an open challenge in the computational sciences. The many-body expansion decomposes computation of the crystal lattice energy into an embarrassingly parallel collection of computations over molecular dimers, trimers, and so forth, making quantum chemistry techniques tractable for many crystals of small organic molecules. By examining the range-dependence of different types of energetic contributions to the crystal lattice energy, we can glean qualitative understanding of solid-state intermolecular interactions as well as practical, exploitable reductions in the number of computations required for accurate energies. Here, we assess the range-dependent character of two-body interactions of 24 small organic molecular crystals using the physically interpretable components from symmetry-adapted perturbation theory (electrostatics, exchange repulsion, induction/polarization, and London dispersion). We also examine correlations between the convergence rates of electrostatics and London dispersion terms with molecular dipole moments and polarizabilities, to provide guidance for estimating convergence rates in other molecular crystals.

Implementation of Symmetry-Adapted Perturbation Theory based on density functional theory and using hybrid exchange-correlation kernels for dispersion terms

We report the implementation of a symmetry-adapted perturbation theory algorithm based on a density functional theory description of the monomers [SAPT(DFT)]. The implementation adopts a density-fitting treatment of hybrid exchange-correlation kernels to enable the description of monomers with hybrid functionals, as in the algorithm by Bukowski, Podeszwa, and Szalewicz [Chem. Phys. Lett. 414, 111(2005)]. We have improved the algorithm by increasing numerical stability with QR factorization, and optimized the computation of the exchange-correlation kernel with its 2-index density-fitted representation. The algorithm scales as O(N5) formally and is usable for systems with up to ∼3000 basis functions, as demonstrated forthe C60-buckycatcher complex with the aug-cc-pVDZ basis set. The hybrid-kernel-based SAPT(DFT) algorithm is shown to be as accurate as SAPT(DFT) implementations based on local effective exact exchange potentials obtained from the local Hartree-Fock (LHF) method, while avoiding the lower-scaling [O(N4)] but iterative and sometimes hard-to-converge LHF process. The hybrid-kernel algorithm outperforms Hartree-Fock-based SAPT (SAPT0) for the S66 test set, and its accuracy is comparable to the many-body perturbation theory based SAPT2+ approach, which scales as O(N7), although SAPT2+ exhibits a more narrow distribution of errors.

The influence of a solvent environment on direct non-covalent interactions between two molecules: A symmetry-adapted perturbation theory study of polarization tuning of π-π interactions by water

High-level quantum chemical computations have provided significant insight into the fundamental physical nature of non-covalent interactions. These studies have focused primarily on gas-phase computations of small van der Waals dimers; however, these interactions frequently take place in complex chemical environments, such as proteins, solutions, or solids. To better understand how the chemical environment affects non-covalent interactions, we have undertaken a quantum chemical study of π-π interactions in an aqueous solution, as exemplified by T-shaped benzene dimers surrounded by 28 or 50 explicit water molecules. We report interaction energies (IEs) using second-order Møller-Plesset perturbation theory, and we apply the intramolecular and functional-group partitioning extensions of symmetry-adapted perturbation theory (ISAPT and F-SAPT, respectively) to analyze how the solvent molecules tune the π-π interactions of the solute. For complexes containing neutral monomers, even 50 explicit waters (constituting a first and partial second solvation shell) change total SAPT IEs between the two solute molecules by only tenths of a kcal mol^-1, while significant changes of up to 3 kcal mol^-1 of the electrostatic component are seen for the cationic pyridinium-benzene dimer. This difference between charged and neutral solutes is attributed to large non-additive three-body interactions within solvated ion-containing complexes. Overall, except for charged solutes, our quantum computations indicate that nearby solvent molecules cause very little "tuning" of the direct solute-solute interactions. This indicates that differences in binding energies between the gas phase and solution phase are primarily indirect effects of the competition between solute-solute and solute-solvent interactions.

Tuning DNA Supramolecular Polymers by the Addition of Small, Functionalized Nucleobase Mimics

Nucleobase mimicking small molecules able to reconfigure DNA are a recently discovered strategy that promises to extend the structural and functional diversity of nucleic acids. However, only simple, unfunctionalized molecules such as cyanuric acid and melamine have so far been used in this approach. In this work, we show that the addition of substituted cyanuric acid molecules can successfully program polyadenine strands to assemble into supramolecular fibers. Unlike conventional DNA nanostructure functionalization, which typically end-labels DNA strands, our approach incorporates functional groups into DNA with high density using small molecules and results in new DNA triple helices coated with alkylamine or alcohol units that grow into micrometer-long fibers. We find that small changes in the small molecule functional group can result in large structural and energetic variation in the overall assembly. A combination of circular dichroism, atomic force microscopy, molecular dynamics simulations, and a new thermodynamic method, transient equilibrium mapping, elucidated the molecular factors behind these large changes. In particular, we identify substantial DNA sugar and phosphate group deformations to accommodate a hydrogen bond between the phosphate and the small-molecule functional groups, as well as a critical chain length of the functional group which switches this interaction from intra- to interfiber. These parameters allow the controlled formation of hierarchical, hybrid DNA assemblies simply through the addition and variation of small, functionalized molecules.

Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEngine): Automation and interoperability among computational chemistry programs

Community efforts in the computational molecular sciences (CMS) are evolving toward modular, open, and interoperable interfaces that work with existing community codes to provide more functionality and composability than could be achieved with a single program. The Quantum Chemistry Common Driver and Databases (QCDB) project provides such capability through an application programming interface (API) that facilitates interoperability across multiple quantum chemistry software packages. In tandem with the Molecular Sciences Software Institute and their Quantum Chemistry Archive ecosystem, the unique functionalities of several CMS programs are integrated, including CFOUR, GAMESS, NWChem, OpenMM, Psi4, Qcore, TeraChem, and Turbomole, to provide common computational functions, i.e., energy, gradient, and Hessian computations as well as molecular properties such as atomic charges and vibrational frequency analysis. Both standard users and power users benefit from adopting these APIs as they lower the language barrier of input styles and enable a standard layout of variables and data. These designs allow end-to-end interoperable programming of complex computations and provide best practices options by default.

Optimized damping parameters for empirical dispersion corrections to symmetry-adapted perturbation theory

Symmetry-adapted perturbation theory (SAPT) has become an invaluable tool for studying the fundamental nature of non-covalent interactions by directly computing the electrostatics, exchange (steric) repulsion, induction (polarization), and London dispersion contributions to the interaction energy using quantum mechanics. Further application of SAPT is primarily limited by its computational expense, where even its most affordable variant (SAPT0) scales as the fifth power of system size [O(N⁵)] due to the dispersion terms. The algorithmic scaling of SAPT0 is reduced from O(N⁵)→O(N⁴) by replacing these terms with the empirical D3 dispersion correction of Grimme and co-workers, forming a method that may be termed SAPT0-D3. Here, we optimize the damping parameters for the -D3 terms in SAPT0-D3 using a much larger training set than has previously been considered, namely, 8299 interaction energies computed at the complete-basis-set limit of coupled cluster through perturbative triples [CCSD(T)/CBS]. Perhaps surprisingly, with only three fitted parameters, SAPT0-D3 improves on the accuracy of SAPT0, reducing mean absolute errors from 0.61 to 0.49 kcal mol^-1 over the full set of complexes. Additionally, SAPT0-D3 exhibits a nearly 2.5× speedup over conventional SAPT0 for systems with ∼300 atoms and is applied here to systems with up to 459 atoms. Finally, we have also implemented a functional group partitioning of the approach (F-SAPT0-D3) and applied it to determine important contacts in the binding of salbutamol to G-protein coupled β₁-adrenergic receptor in both active and inactive forms. SAPT0-D3 capabilities have been added to the open-source Psi4 software.

Cartesian message passing neural networks for directional properties: Fast and transferable atomic multipoles

The message passing neural network (MPNN) framework is a promising tool for modeling atomic properties but is, until recently, incompatible with directional properties, such as Cartesian tensors. We propose a modified Cartesian MPNN (CMPNN) suitable for predicting atom-centered multipoles, an essential component of ab initio force fields. The efficacy of this model is demonstrated on a newly developed dataset consisting of 46 623 chemical structures and corresponding high-quality atomic multipoles, which was deposited into the publicly available Molecular Sciences Software Institute QCArchive server. We show that the CMPNN accurately predicts atom-centered charges, dipoles, and quadrupoles and that errors in the predicted atomic multipoles have a negligible effect on multipole-multipole electrostatic energies. The CMPNN is accurate enough to model conformational dependencies of a molecule's electronic structure. This opens up the possibility of recomputing atomic multipoles on the fly throughout a simulation in which they might exhibit strong conformational dependence.

CLIFF: A component-based, machine-learned, intermolecular force field

Computation of intermolecular interactions is a challenge in drug discovery because accurate ab initio techniques are too computationally expensive to be routinely applied to drug-protein models. Classical force fields are more computationally feasible, and force fields designed to match symmetry adapted perturbation theory (SAPT) interaction energies can remain accurate in this context. Unfortunately, the application of such force fields is complicated by the laborious parameterization required for computations on new molecules. Here, we introduce the component-based machine-learned intermolecular force field (CLIFF), which combines accurate, physics-based equations for intermolecular interaction energies with machine-learning models to enable automatic parameterization. The CLIFF uses functional forms corresponding to electrostatic, exchange-repulsion, induction/polarization, and London dispersion components in SAPT. Molecule-independent parameters are fit with respect to SAPT2+(3)δMP2/aug-cc-pVTZ, and molecule-dependent atomic parameters (atomic widths, atomic multipoles, and Hirshfeld ratios) are obtained from machine learning models developed for C, N, O, H, S, F, Cl, and Br. The CLIFF achieves mean absolute errors (MAEs) no worse than 0.70 kcal mol^-1 in both total and component energies across a diverse dimer test set. For the side chain-side chain interaction database derived from protein fragments, the CLIFF produces total interaction energies with an MAE of 0.27 kcal mol^-1 with respect to reference data, outperforming similar and even more expensive methods. In applications to a set of model drug-protein interactions, the CLIFF is able to accurately rank-order ligand binding strengths and achieves less than 10% error with respect to SAPT reference values for most complexes.

The proto-Nucleic Acid Builder: a software tool for constructing nucleic acid analogs

The helical structures of DNA and RNA were originally revealed by experimental data. Likewise, the development of programs for modeling these natural polymers was guided by known structures. These nucleic acid polymers represent only two members of a potentially vast class of polymers with similar structural features, but that differ from DNA and RNA in the backbone or nucleobases. Xeno nucleic acids (XNAs) incorporate alternative backbones that affect the conformational, chemical, and thermodynamic properties of XNAs. Given the vast chemical space of possible XNAs, computational modeling of alternative nucleic acids can accelerate the search for plausible nucleic acid analogs and guide their rational design. Additionally, a tool for the modeling of nucleic acids could help reveal what nucleic acid polymers may have existed before RNA in the early evolution of life. To aid the development of novel XNA polymers and the search for possible pre-RNA candidates, this article presents the proto-Nucleic Acid Builder (https://github.com/GT-NucleicAcids/pnab), an open-source program for modeling nucleic acid analogs with alternative backbones and nucleobases. The torsion-driven conformation search procedure implemented here predicts structures with good accuracy compared to experimental structures, and correctly demonstrates the correlation between the helical structure and the backbone conformation in DNA and RNA.

Electron-Passing Neural Networks for Atomic Charge Prediction in Systems with Arbitrary Molecular Charge

Atomic charges are critical quantities in molecular mechanics and molecular dynamics, but obtaining these quantities requires heuristic choices based on atom typing or relatively expensive quantum mechanical computations to generate a density to be partitioned. Most machine learning efforts in this domain ignore total molecular charges, relying on overfitting and arbitrary rescaling in order to match the total system charge. Here, we introduce the electron-passing neural network (EPNN), a fast, accurate neural network atomic charge partitioning model that conserves total molecular charge by construction. EPNNs predict atomic charges very similar to those obtained by partitioning quantum mechanical densities but at such a small fraction of the cost that they can be easily computed for large biomolecules. Charges from this method may be used directly for molecular mechanics, as features for cheminformatics, or as input to any neural network potential.

Psi4 1.4: Open-source software for high-throughput quantum chemistry

PSI4 is a free and open-source ab initio electronic structure program providing implementations of Hartree-Fock, density functional theory, many-body perturbation theory, configuration interaction, density cumulant theory, symmetry-adapted perturbation theory, and coupled-cluster theory. Most of the methods are quite efficient, thanks to density fitting and multi-core parallelism. The program is a hybrid of C++ and Python, and calculations may be run with very simple text files or using the Python API, facilitating post-processing and complex workflows; method developers also have access to most of PSI4's core functionalities via Python. Job specification may be passed using The Molecular Sciences Software Institute (MolSSI) QCSCHEMA data format, facilitating interoperability. A rewrite of our top-level computation driver, and concomitant adoption of the MolSSI QCARCHIVE INFRASTRUCTURE project, makes the latest version of PSI4 well suited to distributed computation of large numbers of independent tasks. The project has fostered the development of independent software components that may be reused in other quantum chemistry programs.

Techniques for high-performance construction of Fock matrices

This paper presents techniques for Fock matrix construction that are designed for high performance on shared and distributed memory parallel computers when using Gaussian basis sets. Four main techniques are considered. (1) To calculate electron repulsion integrals, we demonstrate batching together the calculation of multiple shell quartets of the same angular momentum class so that the calculation of large sets of primitive integrals can be efficiently vectorized. (2) For multithreaded summation of entries into the Fock matrix, we investigate using a combination of atomic operations and thread-local copies of the Fock matrix. (3) For distributed memory parallel computers, we present a globally accessible matrix class for accessing distributed Fock and density matrices. The new matrix class introduces a batched mode for remote memory access that can reduce the synchronization cost. (4) For density fitting, we exploit both symmetry (of the Coulomb and exchange matrices) and sparsity (of 3-index tensors) and give a performance comparison of density fitting and the conventional direct calculation approach. The techniques are implemented in an open-source software library called GTFock.

CrystaLattE: Automated computation of lattice energies of organic crystals exploiting the many-body expansion to achieve dual-level parallelism

We present an algorithm to compute the lattice energies of molecular crystals based on the many-body cluster expansion. The required computations on dimers, trimers, etc., within the crystal are independent of each other, leading to a naturally parallel approach. The algorithm exploits the long-range three-dimensional periodic order of crystals to automatically detect and avoid redundant or unnecessary computations. For this purpose, Coulomb-matrix descriptors from machine learning applications are found to be efficient in determining whether two N-mers are identical. The algorithm is implemented as an open-source Python program, CrystaLattE, that uses some of the features of the Quantum Chemistry Common Driver and Databases library. CrystaLattE is initially interfaced with the quantum chemistry package Psi4. With CrystaLattE, we have applied the fast, dispersion-corrected Hartree-Fock method HF-3c to the lattice energy of crystalline benzene. Including all 73 symmetry-unique dimers and 7130 symmetry-unique trimers that can be formed from molecules within a 15 Å cutoff from a central reference monomer, HF-3c plus an Axilrod-Teller-Muto estimate of three-body dispersion exhibits an error of only -1.0 kJ mol^-1 vs the estimated 0 K experimental lattice energy of -55.3 ± 2.2 kJ mol^-1. The convergence of the HF-3c two- and three-body contributions to the lattice energy as a function of intermonomer distance is examined.

Intramolecular Noncovalent Interactions Facilitate Thermally Activated Delayed Fluorescence (TADF)

In the conventional molecular design of thermally activated delayed fluorescence (TADF) organic emitters, simultaneously achieving a fast rate of reverse intersystem crossing (RISC) from the triplet to the singlet manifold and a fast rate of radiative decay is a challenging task. A number of recent experimental data, however, point to TADF emitters with intramolecular π-π interactions as a potential pathway to overcome the issue. Here, we report a comprehensive investigation of TADF emitters with intramolecular π···π or lone-pair···π noncovalent interactions. We uncover the impact of those intramolecular noncovalent interactions on the TADF properties. In particular, we find that folded geometries in TADF molecules can trigger lone-pair···π interactions, introduce a n → π* character of the relevant transitions, enhance the singlet-triplet spin-orbit coupling, and ultimately greatly facilitate the RISC process. This work provides a robust foundation for the molecular design of a novel class of highly efficient TADF emitters in which intramolecular noncovalent interactions play a critical function.

Tipping the Balance between S-π and O-π Interactions

A comprehensive experimental survey consisting of 36 molecular balances was conducted to compare 18 pairs of S-π versus O-π interactions over a wide range of structural, geometric, and solvent parameters. A strong linear correlation was observed between the folding energies of the sulfur and oxygen balances across the entire library of balance pairs. The more stable interaction systematically switched from the O-π to S-π interaction. Computational studies of bimolecular PhSCH₃-arene and PhOCH₃-arene complexes were able to replicate the experimental trends in the molecular balances. The change in preference for the O-π to S-π interaction was due to the interplay of stabilizing (dispersion and solvophobic) and destabilizing (exchange-repulsion) terms arising from the differences in size and polarizability of the oxygen and sulfur atoms.

Analysis of transition state stabilization by non-covalent interactions in organocatalysis: application of atomic and functional-group partitioned symmetry-adapted perturbation theory to the addition of organoboron reagents to fluoroketones

This work seeks to apply symmetry-adapted perturbation theory (SAPT) to the recent study of Hoveyda and co-workers [K. A. Lee et al., Nat. Chem. 2016, 8, 768] where an allyl addition to a ketone became enantioselective when the ketone was fluorinated. Through the application of atomic SAPT (A-SAPT) and functional-group SAPT (F-SAPT), the non-covalent interactions between specific atoms and functional groups in the transition states associated with the fluoroketone reactions can be quantified. Our A-SAPT analysis confirms that a HF contact thought to enhance stereoselectivity shows a strong preference for one of the transition states leading to the experimentally observed product enantiomer. Other key atom-atom contacts invoked to rationalize relative transition state energies are also found to behave as expected based on chemical intuition and contact distances. On the other hand, hypothesized steric clashes between substrate phenyl or ortho-methyl phenyl groups and the catalyst are not supported by F-SAPT computations, and indeed, these are actually favorable π-π interactions.

The BioFragment Database (BFDb): An open-data platform for computational chemistry analysis of noncovalent interactions

Accurate potential energy models are necessary for reliable atomistic simulations of chemical phenomena. In the realm of biomolecular modeling, large systems like proteins comprise very many noncovalent interactions (NCIs) that can contribute to the protein's stability and structure. This work presents two high-quality chemical databases of common fragment interactions in biomolecular systems as extracted from high-resolution Protein DataBank crystal structures: 3380 sidechain-sidechain interactions and 100 backbone-backbone interactions that inaugurate the BioFragment Database (BFDb). Absolute interaction energies are generated with a computationally tractable explicitly correlated coupled cluster with perturbative triples [CCSD(T)-F12] "silver standard" (0.05 kcal/mol average error) for NCI that demands only a fraction of the cost of the conventional "gold standard," CCSD(T) at the complete basis set limit. By sampling extensively from biological environments, BFDb spans the natural diversity of protein NCI motifs and orientations. In addition to supplying a thorough assessment for lower scaling force-field (2), semi-empirical (3), density functional (244), and wavefunction (45) methods (comprising >1M interaction energies), BFDb provides interactive tools for running and manipulating the resulting large datasets and offers a valuable resource for potential energy model development and validation.

Analytic energy gradients for the coupled-cluster singles and doubles with perturbative triples method with the density-fitting approximation

An efficient implementation of analytic gradients for the coupled-cluster singles and doubles with perturbative triples [CCSD(T)] method with the density-fitting (DF) approximation, denoted as DF-CCSD(T), is reported. For the molecules considered, the DF approach substantially accelerates conventional CCSD(T) analytic gradients due to the reduced input/output time and the acceleration of the so-called "gradient terms": formation of particle density matrices (PDMs), computation of the generalized Fock-matrix (GFM), solution of the Z-vector equation, formation of the effective PDMs and GFM, back-transformation of the PDMs and GFM, from the molecular orbital to the atomic orbital (AO) basis, and computation of gradients in the AO basis. For the largest member of the molecular test set considered (C₆H₁₄), the computational times for analytic gradients (with the correlation-consistent polarized valence triple-ζ basis set in serial) are 106.2 [CCSD(T)] and 49.8 [DF-CCSD(T)] h, a speedup of more than 2-fold. In the evaluation of gradient terms, the DF approach completely avoids the use of four-index two-electron integrals. Similar to our previous studies on DF-second-order Møller-Plesset perturbation theory and DF-CCSD gradients, our formalism employs 2- and 3-index two-particle density matrices (TPDMs) instead of 4-index TPDMs. Errors introduced by the DF approximation are negligible for equilibrium geometries and harmonic vibrational frequencies.

Assessment of Density Functional Methods for Geometry Optimization of Bimolecular van der Waals Complexes

We explore the suitability of three popular density functionals (B97-D3, B3LYP-D3, M05-2X) for producing accurate equilibrium geometries of van der Waals (vdW) complexes with diverse binding motifs. For these functionals, optimizations using Dunning's aug-cc-pVDZ basis set best combine accuracy and a reasonable computational expense. Each DFT/aug-cc-pVDZ combination produces optimized equilibrium geometries for 21 small vdW complexes of organic molecules (up to four non-hydrogen atoms total) that agree with high-level CCSD(T)/CBS reference geometries to within ±0.1 Å for the averages of the center-of-mass displacement and the mean least root-mean-squared displacement. The DFT/aug-cc-pVDZ combinations are also able to reproduce the optimal center-of-mass displacements interpolated from CCSD(T)/CBS radial potential energy surfaces in both NBC7x and HBC6 test sets to within ±0.1 Å. We therefore conclude that each of these denisty functional methods, together with the aug-cc-pVDZ basis set, is suitable for producing equilibrium geometries of generic nonbonded complexes.

C-H···O Hydrogen Bonding. The Prototypical Methane-Formaldehyde System: A Critical Assessment

Distinguishing the functionality of C-H···O hydrogen bonds (HBs) remains challenging, because their properties are difficult to quantify reliably. Herein, we present a study of the model methane-formaldehyde complex (MFC). Six stationary points on the MFC potential energy surface (PES) were obtained at the CCSD(T)/ANO2 level. The CCSDT(Q)/CBS interaction energies of the conformers range from only -1.12 kcal mol^-1 to -0.33 kcal mol^-1, denoting a very flat PES. Notably, only the lowest energy stationary point (MFC1) corresponds to a genuine minimum, whereas all other stationary points-including the previously studied ideal case of a_e(C-H···O) = 180°-exhibit some degree of freedom that leads to MFC1. Despite the flat PES, we clearly see that the HB properties of MFC1 align with those of the prototypical water dimer O-H···O HB. Each HB property generally becomes less prominent in the higher-energy conformers. Only the MFC1 conformer prominently exhibits (1) elongated C-H donor bonds, (2) attractive C-H···O═C interactions, (3) n(O) → σ*(C-H) hyperconjugation, (4) critical points in the electron density from Bader's method and from the noncovalent interactions method, (5) positively charged donor hydrogen, and (6) downfield NMR chemical shifts and nonzero ²J(C_M-H_M···O_F) coupling constants. Based on this research, some issues merit further study. The flat PES hinders reliable determinations of the HB-induced shifts of the C-H stretches; a similarly difficult challenge is observed for the experiment. The role of charge transfer in HBs remains an intriguing open question, although our BLW and NBO computations suggest that it is relevant to the C-H···O HB geometries. These issues notwithstanding, the prominence of the HB properties in MFC1 serves as clear evidence that the MFC is predominantly bound by a C-H···O HB.

Psi4 1.1: An Open-Source Electronic Structure Program Emphasizing Automation, Advanced Libraries, and Interoperability

Psi4 is an ab initio electronic structure program providing methods such as Hartree-Fock, density functional theory, configuration interaction, and coupled-cluster theory. The 1.1 release represents a major update meant to automate complex tasks, such as geometry optimization using complete-basis-set extrapolation or focal-point methods. Conversion of the top-level code to a Python module means that Psi4 can now be used in complex workflows alongside other Python tools. Several new features have been added with the aid of libraries providing easy access to techniques such as density fitting, Cholesky decomposition, and Laplace denominators. The build system has been completely rewritten to simplify interoperability with independent, reusable software components for quantum chemistry. Finally, a wide range of new theoretical methods and analyses have been added to the code base, including functional-group and open-shell symmetry adapted perturbation theory, density-fitted coupled cluster with frozen natural orbitals, orbital-optimized perturbation and coupled-cluster methods (e.g., OO-MP2 and OO-LCCD), density-fitted multiconfigurational self-consistent field, density cumulant functional theory, algebraic-diagrammatic construction excited states, improvements to the geometry optimizer, and the "X2C" approach to relativistic corrections, among many other improvements.

Density-fitted open-shell symmetry-adapted perturbation theory and application to π-stacking in benzene dimer cation and ionized DNA base pair steps

Symmetry-Adapted Perturbation Theory (SAPT) is one of the most popular approaches to energy component analysis of non-covalent interactions between closed-shell systems, yielding both accurate interaction energies and meaningful interaction energy components. In recent years, the full open-shell equations for SAPT up to second-order in the intermolecular interaction and zeroth-order in the intramolecular correlation (SAPT0) were published [P. S. Zuchowski et al., J. Chem. Phys. 129, 084101 (2008); M. Hapka et al., ibid. 137, 164104 (2012)]. Here, we utilize density-fitted electron repulsion integrals to produce an efficient computational implementation. This approach is used to examine the effect of ionization on π-π interactions. For the benzene dimer radical cation, comparison against reference values indicates a good performance for open-shell SAPT0, except in cases with substantial charge transfer. For π stacking between hydrogen-bonded pairs of nucleobases, dispersion interactions still dominate binding, in spite of the creation of a positive charge.

Analytic energy gradients for the coupled-cluster singles and doubles method with the density-fitting approximation

An efficient implementation is presented for analytic gradients of the coupled-cluster singles and doubles (CCSD) method with the density-fitting approximation, denoted DF-CCSD. Frozen core terms are also included. When applied to a set of alkanes, the DF-CCSD analytic gradients are significantly accelerated compared to conventional CCSD for larger molecules. The efficiency of our DF-CCSD algorithm arises from the acceleration of several different terms, which are designated as the "gradient terms": computation of particle density matrices (PDMs), generalized Fock-matrix (GFM), solution of the Z-vector equation, formation of the relaxed PDMs and GFM, back-transformation of PDMs and GFM to the atomic orbital (AO) basis, and evaluation of gradients in the AO basis. For the largest member of the alkane set (C10H22), the computational times for the gradient terms (with the cc-pVTZ basis set) are 2582.6 (CCSD) and 310.7 (DF-CCSD) min, respectively, a speed up of more than 8-folds. For gradient related terms, the DF approach avoids the usage of four-index electron repulsion integrals. Based on our previous study [U. Bozkaya, J. Chem. Phys. 141, 124108 (2014)], our formalism completely avoids construction or storage of the 4-index two-particle density matrix (TPDM), using instead 2- and 3-index TPDMs. The DF approach introduces negligible errors for equilibrium bond lengths and harmonic vibrational frequencies.

Revised Damping Parameters for the D3 Dispersion Correction to Density Functional Theory

Since the original fitting of Grimme's DFT-D3 damping parameters, the number and quality of benchmark interaction energies has increased significantly. Here, conventional benchmark sets, which focus on minimum-orientation radial curves at the expense of angular diversity, are augmented by new databases such as side chain-side chain interactions (SSI), which are composed of interactions gleaned from crystal data and contain no such minima-focused bias. Moreover, some existing databases such as S22×5 are extended to shorter intermolecular separations. This improved DFT-D3 training set provides a balanced description of distances, covers the entire range of interaction types, and at 1526 data points is far larger than the original training set of 130. The results are validated against a new collection of 6773 data points and demonstrate that the effect of refitting the damping parameters ranges from no change in accuracy (LC-ωPBE-D3) to an almost 2-fold decrease in average error (PBE-D3).

Analysis of transition state stabilization by non-covalent interactions in the Houk-List model of organocatalyzed intermolecular Aldol additions using functional-group symmetry-adapted perturbation theory

Rational design of catalysts would be aided by a better understanding of how non-covalent interactions stabilize transition states. Here, we apply the newly-developed Functional-Group Symmetry-Adapted Perturbation Theory (F-SAPT) to quantify non-covalent interactions in transition states of the proline-catalyzed intermolecular aldol reaction between benzaldehyde and cyclohexanone, according to the Houk-List mechanism [Bahmanyar et al., J. Am. Chem. Soc., 2003, 125, 2475]. A recent re-examination of this organocatalytic reaction by Rzepa and co-workers [Armstrong et al., Chem. Sci., 2014, 5, 2057] used electron density analysis to identify three key non-covalent interactions thought to influence stereoselectivity: (1) a favorable electrostatic interaction (originally identified by Houk and List) between the NCH(δ+) group of the enamine intermediate and the (δ-)O[double bond, length as m-dash]C of benzaldehyde; (2) a C-H/π interaction between the cyclohexene group of the enamine intermediate and the benzaldehyde phenyl ring; (3) a stabilizing contact between an ortho-hydrogen of the phenyl and an oxygen of the carboxylic acid group of the enamine. These three interactions have been directly computed using F-SAPT, which confirms the stabilizing interaction between an ortho-hydrogen and the carboxylic acid in the (S,S) and (R,S) transition state stereoisomers. F-SAPT analysis also finds stabilizing dispersion and electrostatic interactions due to a C-H/π interaction between the cyclohexene and phenyl groups in the (S,S) and (R,R) transition states. However, unfavorable exchange-repulsion cancels the attractive terms that favor these stereoisomers. Surprisingly, the interaction thought to be most important for stereoselectivity, the NCH(δ+)(δ-)O[double bond, length as m-dash]C interaction, is actually found to be repulsive due to the negative charge on the nitrogen. Hence, our results indicate that geometric analysis and/or density-based analysis does not necessarily produce a reliable picture of non-covalent stabilization. As confirmed by high-level coupled-cluster computations, intermolecular interaction energies are strongest for the (R,R) transition states, which are not the experimentally favored products. This suggests that at least for this reaction, stereoselectivity is also strongly dependent on the energy required to distort the reacting molecules into the transition state geometry.