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This paper is dedicated to the quantum chemical package Jaguar, which is commercial software developed and distributed by Schrödinger, Inc. We discuss Jaguar's scientific features that are relevant to chemical research as well as describe those aspects of the program that are pertinent to the user interface, the organization of the computer code, and its maintenance and testing. Among the scientific topics that feature prominently in this paper are the quantum chemical methods grounded in the pseudospectral approach. A number of multistep workflows dependent on Jaguar are covered: prediction of protonation equilibria in aqueous solutions (particularly calculations of tautomeric stability and pKa), reactivity predictions based on automated transition state search, assembly of Boltzmann-averaged spectra such as vibrational and electronic circular dichroism, as well as nuclear magnetic resonance. Discussed also are quantum chemical calculations that are oriented toward materials science applications, in particular, prediction of properties of optoelectronic materials and organic semiconductors, and molecular catalyst design. The topic of treatment of conformations inevitably comes up in real world research projects and is considered as part of all the workflows mentioned above. In addition, we examine the role of machine learning methods in quantum chemical calculations performed by Jaguar, from auxiliary functions that return the approximate calculation runtime in a user interface, to prediction of actual molecular properties. The current work is second in a series of reviews of Jaguar, the first having been published more than ten years ago. Thus, this paper serves as a rare milestone on the path that is being traversed by Jaguar's development in more than thirty years of its existence.
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An important concern related to the performance of Li-ion batteries is the formation of a solid electrolyte interphase on the surface of the anode. This film is formed from the decomposition of electrolytes and can have important effects on the stability and performance. Here, we evaluate the decomposition pathway of ethylene carbonate and related organic electrolyte molecules using a series of density functional approximations and correlated wave function (WF) methods, including the coupled-cluster theory with single, double, and perturbative triple excitations [CCSD(T)] and auxiliary-field quantum Monte Carlo (AFQMC). We find that the transition state barrier associated with ring opening varies widely across different functionals, ranging from 3.01 to 17.15 kcal/mol, which can be compared to the value of 12.84 kcal/mol predicted by CCSD(T). This large variation underscores the importance of benchmarking against accurate WF methods. A performance comparison of all of the density functionals used in this study reveals that the M06-2X-D3 (a meta-hybrid GGA), CAM-B3LYP-D3 (a range-separated hybrid), and B2GP-PLYP-D3 (a double hybrid) perform the best, with average errors of about 1.50-1.60 kcal/mol compared to CCSD(T). We also compared the performance of the WF methods that are more scalable than CCSD(T), finding that DLPNO-CCSD(T) and phaseless AFQMC with a DFT trial wave function exhibit average errors of 1.38 and 1.74 kcal/mol, respectively.
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In contrast to the computational generation of conventional tautomers, the analogous operation that would produce ring-chain tautomers is rarely available in cheminformatics codes. This is partly due to the perceived unimportance of ring-chain tautomerism and partly because specialized algorithms are required to realize the non-local proton transfers that occur during ring-chain rearrangement. Nevertheless, for some types of organic compounds, including sugars, warfarin analogs, fluorescein dyes and some drug-like compounds, ring-chain tautomerism cannot be ignored. In this work, a novel ring-chain tautomer generation algorithm is presented. It differs from previously proposed solutions in that it does not rely on hard-coded patterns of proton migrations and bond rearrangements, and should therefore be more general and maintainable. We deploy this algorithm as part of a workflow which provides an automated solution for tautomer generation and scoring. The workflow identifies protonatable and deprotonatable sites in the molecule using a previously described approach based on rapid micro-pKa prediction. These data are used to distribute the active protons among the protonatable sites exhaustively, at which point alternate resonance structures are considered to obtain pairs of atoms with opposite formal charge. These pairs are connected with a single bond and a 3D undistorted geometry is generated. The scoring of the generated tautomers is performed with a subsequent density functional theory calculation employing an implicit solvent model. We demonstrate the performance of our workflow on several types of organic molecules known to exist in ring-chain tautomeric equilibria in solution. In particular, we show that some ring-chain tautomers not found using previously published algorithms are successfully located by ours.
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Preparações Farmacêuticas/química , Teoria Quântica , Bibliotecas de Moléculas Pequenas/química , Isomerismo , Estrutura MolecularRESUMO
This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange-correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear-electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an "open teamware" model and an increasingly modular design.
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Aldehyde oxidase (AOX) and other related molybdenum-containing enzymes are known to oxidize the C-H bonds of aromatic rings. This process contributes to the metabolism of pharmaceutical compounds and, therefore, is of vital importance to drug pharmacokinetics. The present work describes an automated computational workflow and its use for the prediction of intrinsic reactivity of small aromatic molecules toward a minimal model of the active site of AOX. The workflow is based on quantum chemical transition state searches for the underlying single-step oxidation reaction, where the automated protocol includes identification of unique aromatic C-H bonds, creation of three-dimensional reactant and product complex geometries via a templating approach, search for a transition state, and validation of reaction end points. Conformational search on the reactants, products, and the transition states is performed. The automated procedure has been validated on previously reported transition state barriers and was used to evaluate the intrinsic reactivity of nearly three hundred heterocycles commonly found in approved drug molecules. The intrinsic reactivity of more than 1000 individual aromatic carbon sites is reported. Stereochemical and conformational aspects of the oxidation reaction, which have not been discussed in previous studies, are shown to play important roles in accurate modeling of the oxidation reaction. Observations on structural trends that determine the reactivity are provided and rationalized.
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Aldeído Oxidase , Aldeído Oxidase/química , Aldeído Oxidase/metabolismo , Domínio Catalítico , OxirreduçãoRESUMO
A method that we have recently introduced for rapid computation of intermolecular interaction energies is reformulated and subjected to further tests. The method employs monomer-based self-consistent field calculations with an electrostatic embedding designed to capture many-body polarization (the "XPol" procedure), augmented by pairwise symmetry-adapted perturbation theory (SAPT) to capture dispersion and exchange interactions along with any remaining induction effects. A rigorous derivation of the XPol+SAPT methodology is presented here, which demonstrates that the method is systematically improvable, and moreover introduces some additional intermolecular interactions as compared to the more heuristic derivation that was presented previously. Applications to various non-covalent complexes and clusters are presented, including geometry optimizations and one-dimensional potential energy scans. The performance of the XPol+SAPT methodology in its present form (based on second-order intermolecular perturbation theory and neglecting intramolecular electron correlation) is qualitatively acceptable across a wide variety of systems-and quantitatively quite good in certain cases-but the quality of the results is rather sensitive to the choice of one-particle basis set. Basis sets that work well for dispersion-bound systems offer less-than-optimal performance for clusters dominated by induction and electrostatic interactions, and vice versa. A compromise basis set is identified that affords good results for both induction and dispersion interactions, although this favorable performance ultimately relies on error cancellation, as in traditional low-order SAPT. Suggestions for future improvements to the methodology are discussed.
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Transferable high dimensional neural network potentials (HDNNPs) have shown great promise as an avenue to increase the accuracy and domain of applicability of existing atomistic force fields for organic systems relevant to life science. We have previously reported such a potential (Schrödinger-ANI) that has broad coverage of druglike molecules. We extend that work here to cover ionic and zwitterionic druglike molecules expected to be relevant to drug discovery research activities. We report a novel HDNNP architecture, which we call QRNN, that predicts atomic charges and uses these charges as descriptors in an energy model that delivers conformational energies within chemical accuracy when measured against the reference theory it is trained to. Further, we find that delta learning based on a semiempirical level of theory approximately halves the errors. We test the models on torsion energy profiles, relative conformational energies, geometric parameters, and relative tautomer errors.
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Redes Neurais de Computação , Íons , Conformação MolecularRESUMO
Liquid electrolytes are one of the most important components of Li-ion batteries, which are a critical technology of the modern world. However, we still lack the computational tools required to accurately calculate key properties of these materials (viscosity and ionic diffusivity) from first principles necessary to support improved designs. In this work, we report a machine learning-based force field for liquid electrolyte simulations, which bridges the gap between the accuracy of range-separated hybrid density functional theory and the efficiency of classical force fields. Predictions of material properties made with this force field are quantitatively accurate compared to experimental data. Our model uses the QRNN deep neural network architecture, which includes both long-range interactions and global charge equilibration. The training data set is composed solely of non-periodic density functional theory (DFT), allowing the practical use of an accurate theory (here, ωB97X-D3BJ/def2-TZVPD), which would be prohibitively expensive for generating large data sets with periodic DFT. In this report, we focus on seven common carbonates and LiPF6, but this methodology has very few assumptions and can be readily applied to any liquid electrolyte system. This provides a promising path forward for large-scale atomistic modeling of many important battery chemistries.
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Lítio , Simulação de Dinâmica Molecular , Fontes de Energia Elétrica , Eletrólitos , Redes Neurais de ComputaçãoRESUMO
Water cluster anions, (H(2)O)(N)(-), are examined using mixed quantum/classical molecular dynamics based on a one-electron pseudopotential model that incorporates many-body polarization and predicts vertical electron detachment energies (VDEs) with an accuracy of ~0.1 eV. By varying the initial conditions under which the clusters are formed, we are able to identify four distinct isomer types that exhibit different size-dependent VDEs. On the basis of a strong correlation between the electron's radius of gyration and its optical absorption maximum, and extrapolating to the bulk limit (N â ∞), our analysis supports the assignment of the "isomer Ib" data series, observed in photoelectron spectra of very cold clusters, as arising from cavity-bound (H(2)O)(N)(-) cluster isomers. The "isomer I" data reported in warmer experiments are assigned to surface-bound isomers in smaller clusters, transitioning to partially embedded isomers in larger clusters. The partially embedded isomers are characterized by a partially formed solvent cavity at the cluster surface, and they are spectroscopically quite similar to internalized cavity isomers. These assignments are consistent with various experimental data, and our theoretical characterization of these isomers sheds new light on a long-standing assignment problem.
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The prevailing structural paradigm for the aqueous electron is that of an s-like ground-state wave function that inhabits a quasi-spherical solvent cavity, a viewpoint that is supported by numerous atomistic simulations using various one-electron pseudopotential models. This conceptual picture has recently been challenged, however, on the basis of results obtained from a new electron-water pseudopotential model that predicts a more delocalized wave function and no well-defined solvent cavity. Here, we examine this new model in comparison to two alternative, cavity-forming pseudopotential models. We find that the cavity-forming models are far more consistent with the experimental data for the electron's radius of gyration, optical absorption spectrum, and vertical electron binding energy. Calculations of the absorption spectrum using time-dependent density functional theory are in quantitative or semiquantitative agreement with experiment when the solvent geometries are obtained from the cavity-forming pseudopotential models, but differ markedly from experiment when geometries that do not form a cavity are used.
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We report a fragment-based electronic structure method, intended for the study of clusters and molecular liquids, that incorporates electronic polarization (induction) in a self-consistent fashion but treats intermolecular exchange and dispersion interactions perturbatively, as post-self-consistent field corrections, using a form of pairwise symmetry-adapted perturbation theory. The computational cost of the method scales quadratically as a function of the number of fragments (monomers), but could be made to scale linearly by exploiting distance-dependent thresholds. Extensive benchmark calculations are reported using the S22 database of high-level ab initio binding energies for dimers, and we find that average errors can be reduced to <1 kcal/mol with a suitable choice of basis set. Comparison to ab initio benchmarks for water clusters as large as (H(2)O)(20) demonstrates that the method recovers â³90% of the binding energy in these systems, at a tiny fraction of the computational cost. As such, this approach represents a promising path toward accurate, systematically improvable, and parameter-free simulation of molecular liquids.
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The electronic absorption spectrum of the aqueous electron in bulk water has been simulated using long-range-corrected time-dependent density functional theory as well as mixed quantum/classical molecular dynamics based on a one-electron model in which electron-water polarization is treated self-consistently. Both methodologies suggest that the high-energy Lorentzian tail that is observed experimentally arises mostly from delocalized bound-state excitations of the electron rather than bound-to-continuum excitations, as is usually assumed. Excited states in the blue tail are bound only by polarization of the solvent electron density. These findings have potentially important ramifications for understanding electron localization in polar condensed media as well as biological radiation damage arising from dissociative electron attachment.
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Previously, we reported an electron-water pseudopotential designed to be used in conjunction with a polarizable water model, in order to describe the hydrated electron [L. D. Jacobson et al., J. Chem. Phys. 130, 124115 (2009)]. Subsequently, we found this model to be inadequate for the aqueous electron in bulk water, and here we report a reparametrization of the model. Unlike the previous model, the current version is not fit directly to any observables; rather, we use an ab initio exchange-correlation potential, along with a repulsive potential that is fit to reproduce the density maximum of the excess electron's wave function within the static-exchange approximation. The new parametrization performs at least as well as the previous model, as compared to ab initio benchmarks for (H(2)O)(n) (-) clusters, and also predicts reasonable values for the diffusion coefficient, radius of gyration, and absorption maximum of the bulk species. The new model predicts a vertical electron binding energy of 3.7 eV in bulk water, which is 1.4 eV smaller than the value obtained using nonpolarizable models; the difference represents the solvent's electronic reorganization energy following electron detachment. We find that the electron's first solvation shell is quite loose, which may be responsible for the electron's large, positive entropy of hydration. Many-body polarization alters the electronic absorption line shape in a qualitative way, giving rise to a high-energy tail that is observed experimentally but is absent in previous simulations. In our model, this feature arises from spatially diffuse excited states that are bound only by electronic reorganization (i.e., solvent polarization) following electronic excitation.
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Previously, Turi and Borgis [J. Chem. Phys. 117, 6186 (2002)] parametrized an electron-water interaction potential, intended for use in simulations of hydrated electrons, by considering H(2)O(-) in the "static exchange" (essentially, frozen-core Hartree-Fock) approximation, then applying an approximate Phillips-Kleinman procedure to construct a one-electron pseudopotential representing the electron-water interaction. To date, this pseudopotential has been used exclusively in conjunction with a simple point charge water model that is parametrized for bulk water and yields poor results for small, neutral water clusters. Here, we extend upon the work of Turi and Borgis by reparametrizing the electron-water pseudopotential for use with the AMOEBA water model, which performs well for neutral clusters. The result is a one-electron model Hamiltonian for (H(2)O)(n)(-), in which the one-electron wave function polarizes the water molecules, and vice versa, in a fully self-consistent fashion. The new model is fully variational and analytic energy gradients are available. We have implemented the new model using a modified Davidson algorithm to compute eigenstates, with the unpaired electron represented on a real-space grid. Comparison to ab initio electronic structure calculations for (H(2)O)(n)(-) cluster isomers ranging from n=2 to n=35 reveals that the new model is significantly more accurate than the Turi-Borgis model, for both relative isomer energies and for vertical electron detachment energies. Electron-water polarization interactions are found to be much more significant for cavity states of the unpaired electron than for surface states.
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Transition state search is at the center of multiple types of computational chemical predictions related to mechanistic investigations, reactivity and regioselectivity predictions, and catalyst design. The process of finding transition states in practice is, however, a laborious multistep operation that requires significant user involvement. Here, we report a highly automated workflow designed to locate transition states for a given elementary reaction with minimal setup overhead. The only essential inputs required from the user are the structures of the separated reactants and products. The seamless workflow combining computational technologies from the fields of cheminformatics, molecular mechanics, and quantum chemistry automatically finds the most probable correspondence between the atoms in the reactants and the products, generates a transition state guess, launches a transition state search through a combined approach involving the relaxing string method and the quadratic synchronous transit, and finally validates the transition state via the analysis of the reactive chemical bonds and imaginary vibrational frequencies as well as by the intrinsic reaction coordinate method. Our approach does not target any specific reaction type, nor does it depend on training data; instead, it is meant to be of general applicability for a wide variety of reaction types. The workflow is highly flexible, permitting modifications such as a choice of accuracy, level of theory, basis set, or solvation treatment. Successfully located transition states can be used for setting up transition state guesses in related reactions, saving computational time and increasing the probability of success. The utility and performance of the method are demonstrated in applications to transition state searches in reactions typical for organic chemistry, medicinal chemistry, and homogeneous catalysis research. In particular, applications of our code to Michael additions, hydrogen abstractions, Diels-Alder cycloadditions, carbene insertions, and an enzyme reaction model involving a molybdenum complex are shown and discussed.
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Larsen et al. (Reports, 2 July 2010, p. 65) suggest that, contrary to the established paradigm, the aqueous electron does not carve out and occupy a cavity in liquid water. Closer examination of their theoretical model, however, reveals that many of its predictions differ substantively from established benchmarks and that its behavior differs qualitatively from Hartree-Fock theory, upon which the model is based.
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We recently introduced a mixed quantum/classical model for the hydrated electron that includes electron/water polarization in a self-consistent fashion, using a polarizable force field for the water molecules [ J. Chem. Phys. 2010 , 133 , 154506 ]. Calculation of the electronic absorption spectrum for this model is not straightforward, owing to the state-specific nature of the Hamiltonian, the high density of electronic states, and the large solvent polarization response upon electronic excitation. Together, these properties make it difficult or impossible to converge the polarizable solvent dipoles self-consistently for each excited-state wave function. Here, we overcome this problem by means of an extended Lagrangian procedure for performing constrained annealing in the space of electronic variables. By construction, this algorithm affords self-consistent, mutually orthogonal solutions for any state-specific Hamiltonian, and we illustrate this approach by computing the optical spectrum of our polarizable model for the aqueous electron. The spectrum thus obtained affords better agreement with experiment than previous, perturbative calculations of solvent dipole relaxation. Strengths, weaknesses, and possible generalizations of this procedure are discussed.