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Solov’yov AV, Verkhovtsev AV, Mason NJ, Amos RA, Bald I, Baldacchino G, Dromey B, Falk M, Fedor J, Gerhards L, Hausmann M, Hildenbrand G, Hrabovský M, Kadlec S, Kočišek J, Lépine F, Ming S, Nisbet A, Ricketts K, Sala L, Schlathölter T, Wheatley AEH, Solov’yov IA. Condensed Matter Systems Exposed to Radiation: Multiscale Theory, Simulations, and Experiment. Chem Rev 2024; 124:8014-8129. [PMID: 38842266 PMCID: PMC11240271 DOI: 10.1021/acs.chemrev.3c00902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 05/02/2024] [Accepted: 05/10/2024] [Indexed: 06/07/2024]
Abstract
This roadmap reviews the new, highly interdisciplinary research field studying the behavior of condensed matter systems exposed to radiation. The Review highlights several recent advances in the field and provides a roadmap for the development of the field over the next decade. Condensed matter systems exposed to radiation can be inorganic, organic, or biological, finite or infinite, composed of different molecular species or materials, exist in different phases, and operate under different thermodynamic conditions. Many of the key phenomena related to the behavior of irradiated systems are very similar and can be understood based on the same fundamental theoretical principles and computational approaches. The multiscale nature of such phenomena requires the quantitative description of the radiation-induced effects occurring at different spatial and temporal scales, ranging from the atomic to the macroscopic, and the interlinks between such descriptions. The multiscale nature of the effects and the similarity of their manifestation in systems of different origins necessarily bring together different disciplines, such as physics, chemistry, biology, materials science, nanoscience, and biomedical research, demonstrating the numerous interlinks and commonalities between them. This research field is highly relevant to many novel and emerging technologies and medical applications.
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Affiliation(s)
| | | | - Nigel J. Mason
- School
of Physics and Astronomy, University of
Kent, Canterbury CT2 7NH, United
Kingdom
| | - Richard A. Amos
- Department
of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, U.K.
| | - Ilko Bald
- Institute
of Chemistry, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany
| | - Gérard Baldacchino
- Université
Paris-Saclay, CEA, LIDYL, 91191 Gif-sur-Yvette, France
- CY Cergy Paris Université,
CEA, LIDYL, 91191 Gif-sur-Yvette, France
| | - Brendan Dromey
- Centre
for Light Matter Interactions, School of Mathematics and Physics, Queen’s University Belfast, Belfast BT7 1NN, United Kingdom
| | - Martin Falk
- Institute
of Biophysics of the Czech Academy of Sciences, Královopolská 135, 61200 Brno, Czech Republic
- Kirchhoff-Institute
for Physics, Heidelberg University, Im Neuenheimer Feld 227, 69120 Heidelberg, Germany
| | - Juraj Fedor
- J.
Heyrovský Institute of Physical Chemistry, Czech Academy of Sciences, Dolejškova 3, 18223 Prague, Czech Republic
| | - Luca Gerhards
- Institute
of Physics, Carl von Ossietzky University, Carl-von-Ossietzky-Str. 9-11, 26129 Oldenburg, Germany
| | - Michael Hausmann
- Kirchhoff-Institute
for Physics, Heidelberg University, Im Neuenheimer Feld 227, 69120 Heidelberg, Germany
| | - Georg Hildenbrand
- Kirchhoff-Institute
for Physics, Heidelberg University, Im Neuenheimer Feld 227, 69120 Heidelberg, Germany
- Faculty
of Engineering, University of Applied Sciences
Aschaffenburg, Würzburger
Str. 45, 63743 Aschaffenburg, Germany
| | | | - Stanislav Kadlec
- Eaton European
Innovation Center, Bořivojova
2380, 25263 Roztoky, Czech Republic
| | - Jaroslav Kočišek
- J.
Heyrovský Institute of Physical Chemistry, Czech Academy of Sciences, Dolejškova 3, 18223 Prague, Czech Republic
| | - Franck Lépine
- Université
Claude Bernard Lyon 1, CNRS, Institut Lumière
Matière, F-69622, Villeurbanne, France
| | - Siyi Ming
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Lensfield
Road, Cambridge CB2 1EW, United Kingdom
| | - Andrew Nisbet
- Department
of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, U.K.
| | - Kate Ricketts
- Department
of Targeted Intervention, University College
London, Gower Street, London WC1E 6BT, United Kingdom
| | - Leo Sala
- J.
Heyrovský Institute of Physical Chemistry, Czech Academy of Sciences, Dolejškova 3, 18223 Prague, Czech Republic
| | - Thomas Schlathölter
- Zernike
Institute for Advanced Materials, University
of Groningen, Nijenborgh
4, 9747 AG Groningen, The Netherlands
- University
College Groningen, University of Groningen, Hoendiepskade 23/24, 9718 BG Groningen, The Netherlands
| | - Andrew E. H. Wheatley
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Lensfield
Road, Cambridge CB2 1EW, United Kingdom
| | - Ilia A. Solov’yov
- Institute
of Physics, Carl von Ossietzky University, Carl-von-Ossietzky-Str. 9-11, 26129 Oldenburg, Germany
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2
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Tao Y, Giese TJ, Ekesan Ş, Zeng J, Aradi B, Hourahine B, Aktulga HM, Götz AW, Merz KM, York DM. Amber free energy tools: Interoperable software for free energy simulations using generalized quantum mechanical/molecular mechanical and machine learning potentials. J Chem Phys 2024; 160:224104. [PMID: 38856060 DOI: 10.1063/5.0211276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Accepted: 05/15/2024] [Indexed: 06/11/2024] Open
Abstract
We report the development and testing of new integrated cyberinfrastructure for performing free energy simulations with generalized hybrid quantum mechanical/molecular mechanical (QM/MM) and machine learning potentials (MLPs) in Amber. The Sander molecular dynamics program has been extended to leverage fast, density-functional tight-binding models implemented in the DFTB+ and xTB packages, and an interface to the DeePMD-kit software enables the use of MLPs. The software is integrated through application program interfaces that circumvent the need to perform "system calls" and enable the incorporation of long-range Ewald electrostatics into the external software's self-consistent field procedure. The infrastructure provides access to QM/MM models that may serve as the foundation for QM/MM-ΔMLP potentials, which supplement the semiempirical QM/MM model with a MLP correction trained to reproduce ab initio QM/MM energies and forces. Efficient optimization of minimum free energy pathways is enabled through a new surface-accelerated finite-temperature string method implemented in the FE-ToolKit package. Furthermore, we interfaced Sander with the i-PI software by implementing the socket communication protocol used in the i-PI client-server model. The new interface with i-PI allows for the treatment of nuclear quantum effects with semiempirical QM/MM-ΔMLP models. The modular interoperable software is demonstrated on proton transfer reactions in guanine-thymine mispairs in a B-form deoxyribonucleic acid helix. The current work represents a considerable advance in the development of modular software for performing free energy simulations of chemical reactions that are important in a wide range of applications.
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Affiliation(s)
- Yujun Tao
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, USA
| | - Timothy J Giese
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, USA
| | - Şölen Ekesan
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, USA
| | - Jinzhe Zeng
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, USA
| | - Bálint Aradi
- Bremen Center for Computational Materials Science, University of Bremen, D-28334 Bremen, Germany
| | - Ben Hourahine
- SUPA, Department of Physics, University of Strathclyde, Glasgow G4 0NG, United Kingdom
| | - Hasan Metin Aktulga
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, USA
| | - Andreas W Götz
- San Diego Supercomputer Center, University of California San Diego, La Jolla, California 92093, USA
| | - Kenneth M Merz
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, USA
| | - Darrin M York
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, USA
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Tao Y, Giese TJ, York DM. Electronic and Nuclear Quantum Effects on Proton Transfer Reactions of Guanine-Thymine (G-T) Mispairs Using Combined Quantum Mechanical/Molecular Mechanical and Machine Learning Potentials. Molecules 2024; 29:2703. [PMID: 38893576 PMCID: PMC11173453 DOI: 10.3390/molecules29112703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 05/30/2024] [Accepted: 06/04/2024] [Indexed: 06/21/2024] Open
Abstract
Rare tautomeric forms of nucleobases can lead to Watson-Crick-like (WC-like) mispairs in DNA, but the process of proton transfer is fast and difficult to detect experimentally. NMR studies show evidence for the existence of short-time WC-like guanine-thymine (G-T) mispairs; however, the mechanism of proton transfer and the degree to which nuclear quantum effects play a role are unclear. We use a B-DNA helix exhibiting a wGT mispair as a model system to study tautomerization reactions. We perform ab initio (PBE0/6-31G*) quantum mechanical/molecular mechanical (QM/MM) simulations to examine the free energy surface for tautomerization. We demonstrate that while the ab initio QM/MM simulations are accurate, considerable sampling is required to achieve high precision in the free energy barriers. To address this problem, we develop a QM/MM machine learning potential correction (QM/MM-ΔMLP) that is able to improve the computational efficiency, greatly extend the accessible time scales of the simulations, and enable practical application of path integral molecular dynamics to examine nuclear quantum effects. We find that the inclusion of nuclear quantum effects has only a modest effect on the mechanistic pathway but leads to a considerable lowering of the free energy barrier for the GT*⇌G*T equilibrium. Our results enable a rationalization of observed experimental data and the prediction of populations of rare tautomeric forms of nucleobases and rates of their interconversion in B-DNA.
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Giese TJ, Ekesan Ş, McCarthy E, Tao Y, York DM. Surface-Accelerated String Method for Locating Minimum Free Energy Paths. J Chem Theory Comput 2024; 20:2058-2073. [PMID: 38367218 PMCID: PMC11059188 DOI: 10.1021/acs.jctc.3c01401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/19/2024]
Abstract
We present a surface-accelerated string method (SASM) to efficiently optimize low-dimensional reaction pathways from the sampling performed with expensive quantum mechanical/molecular mechanical (QM/MM) Hamiltonians. The SASM accelerates the convergence of the path using the aggregate sampling obtained from the current and previous string iterations, whereas approaches like the string method in collective variables (SMCV) or the modified string method in collective variables (MSMCV) update the path only from the sampling obtained from the current iteration. Furthermore, the SASM decouples the number of images used to perform sampling from the number of synthetic images used to represent the path. The path is optimized on the current best estimate of the free energy surface obtained from all available sampling, and the proposed set of new simulations is not restricted to being located along the optimized path. Instead, the umbrella potential placement is chosen to extend the range of the free energy surface and improve the quality of the free energy estimates near the path. In this manner, the SASM is shown to improve the exploration for a minimum free energy pathway in regions where the free energy surface is relatively flat. Furthermore, it improves the quality of the free energy profile when the string is discretized with too few images. We compare the SASM, SMCV, and MSMCV using 3 QM/MM applications: a ribozyme methyltransferase reaction using 2 reaction coordinates, the 2'-O-transphosphorylation reaction of Hammerhead ribozyme using 3 reaction coordinates, and a tautomeric reaction in B-DNA using 5 reaction coordinates. We show that SASM converges the paths using roughly 3 times less sampling than the SMCV and MSMCV methods. All three algorithms have been implemented in the FE-ToolKit package made freely available.
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Affiliation(s)
- Timothy J. Giese
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Şölen Ekesan
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Erika McCarthy
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Yujun Tao
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Darrin M. York
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
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Ignatov SK, Masunov AE. Unexpected polarization properties of sub-nanosized magnesium clusters. RSC Adv 2023; 13:4065-4076. [PMID: 36756583 PMCID: PMC9890678 DOI: 10.1039/d2ra08086a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 01/20/2023] [Indexed: 01/29/2023] Open
Abstract
The isotropic electrostatic polarizability (IEP) of sub-nanosized magnesium clusters Mg2-Mg32 was studied in an extensive set comprising 1237 structurally unique isomers. These isomers were found in the course of the global search for the potential energy surface minima of the magnesium clusters at the BP86/6-31G(d) level. The calculation of the polarizability at the same DFT level reveals an unexpected property of the IEP: the linear correlation between the polarizability of the most favorable isomers (and only them) and the cluster nuclearity n. Moreover, for each n, the most stable cluster isomer demonstrates nearly minimal IEP value among all found isomers of a given nuclearity. Surprisingly, these observed features are independent of the cluster structures which are quite different. We hypothesize that the energetic favorability of a cluster structure is related to their low polarizability. Apparently, the atoms forming the cluster tend to arrange themselves in such a way as to provide the most compact distribution of the cluster electron density. A possible explanation of the observed trends, their significance for cluster structure prediction, and the practical applications are discussed.
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Affiliation(s)
| | - Artëm E. Masunov
- NanoScience Technology Center, University of Central FloridaOrlandoFlorida 32826USA,School of Modeling, Simulations and Training, University of Central FloridaOrlandoFlorida 32826USA,South Ural State University (National Research University)ChelyabinskRussia
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Shaimardanov AR, Shulga DA, Palyulin VA. Is an Inductive Effect Explicit Account Required for Atomic Charges Aimed at Use within the Force Fields? J Phys Chem A 2022; 126:6278-6294. [PMID: 36054931 DOI: 10.1021/acs.jpca.2c02722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Polarization and inductive effects are the concepts that have been widely used in qualitative and even quantitative descriptions of experimentally observed properties in chemistry. The polarization effect has proven to be important in cases of biomolecular modeling though still the vast majority of molecular simulations use the classical non-polarizable force fields. In the last few decades, a lot of effort has been put into promoting the polarization effect and incorporating it into modern force fields and charge calculation methods. In contrast, the inductive effect has not attracted such attention and is effectively absent in both classic and modern force fields. Thus, a question is whether this difference corresponds to the difference in the physical significance of the effects and their explicit account, or is an artifact that should be corrected in the next generation of force fields. The significance of the electronic effects is studied in this paper through the prism of performance of specific models for atomic charge calculation that take into explicit account a nested set of effects: the formal charge, the nearest neighbors, the inductive effect, and finally the model, which takes into account all effects, which are possible to account for using atomic charges. The specific choice for the methods is the following: formal charges, MMFF94 bond charge increments, Dynamic Electronegativity Relaxation (DENR), and RESP. We propose a special scheme for the separate estimation of each particular effect contribution. By pairwise comparing the residual molecular electrostatic potential (MEP) errors of those charge models (aimed at best reproducing the quantum chemical reference MEP), we sequentially revealed how the account of each effect contributes to the better-quality MEP reproduction. The following relative importance of effects was estimated; thus, the natural hierarchy of the effects was established. First, the account of formal charges is of primordial importance. Second, the nearest neighbors account is the next in significance. Third, the explicit account of inductive effect in empirical charge calculation schemes was shown to significantly─both qualitatively and quantitatively─improve the quality of MEP reproduction. Fourth, the contribution of polarization is indirectly assessed. Surprisingly, it is of the order of magnitude of the inductive effect even for the molecular systems, for which it is anticipated to be more significant. Finally, the relative importance of anisotropic effects in neutral molecules was additionally reviewed.
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Affiliation(s)
- Arslan R Shaimardanov
- Department of Chemistry, Lomonosov Moscow State University, Moscow 119991, Russian Federation
| | - Dmitry A Shulga
- Department of Chemistry, Lomonosov Moscow State University, Moscow 119991, Russian Federation
| | - Vladimir A Palyulin
- Department of Chemistry, Lomonosov Moscow State University, Moscow 119991, Russian Federation
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Dawson W, Degomme A, Stella M, Nakajima T, Ratcliff LE, Genovese L. Density functional theory calculations of large systems: Interplay between fragments, observables, and computational complexity. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2022. [DOI: 10.1002/wcms.1574] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
| | | | - Martina Stella
- Department of Materials Imperial College London London UK
| | | | | | - Luigi Genovese
- Université Grenoble Alpes, INAC‐MEM, L_Sim Grenoble France
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Gray M, Herbert JM. Comprehensive Basis-Set Testing of Extended Symmetry-Adapted Perturbation Theory and Assessment of Mixed-Basis Combinations to Reduce Cost. J Chem Theory Comput 2022; 18:2308-2330. [PMID: 35289608 DOI: 10.1021/acs.jctc.1c01302] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Hybrid or "extended" symmetry-adapted perturbation theory (XSAPT) replaces traditional SAPT's treatment of dispersion with better performing alternatives while at the same time extending two-body (dimer) SAPT to a many-body treatment of polarization using a self-consistent charge embedding procedure. The present work presents a systematic study of how XSAPT interaction energies and energy components converge with respect to the choice of Gaussian basis set. Errors can be reduced in a systematic way using correlation-consistent basis sets, with aug-cc-pVTZ results converged within <0.1 kcal/mol. Similar (if slightly less systematic) behavior is obtained using Karlsruhe basis sets at much lower cost, and we introduce new versions with limited augmentation that are even more efficient. Pople-style basis sets, which are more efficient still, often afford good results if a large number of polarization functions are included. The dispersion models used in XSAPT afford much faster basis-set convergence as compared to the perturbative description of dispersion in conventional SAPT, meaning that "compromise" basis sets (such as jun-cc-pVDZ) are no longer required and benchmark-quality results can be obtained using triple-ζ basis sets. The use of diffuse functions proves to be essential, especially for the description of hydrogen bonds. The "δ(Hartree-Fock)" correction for high-order induction can be performed in double-ζ basis sets without significant loss of accuracy, leading to a mixed-basis approach that offers 4× speedup over the existing (cubic scaling) XSAPT approach.
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Affiliation(s)
- Montgomery Gray
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - John M Herbert
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
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González-Espinoza CE, Rumble CA, Borgis D, Wesolowski TA. Quantifying Fluctuations of Average Solvent Environments for Embedding Calculations. J Chem Theory Comput 2022; 18:1072-1088. [PMID: 35044168 DOI: 10.1021/acs.jctc.1c01108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The viability and effectiveness of replacing an ensemble of embedded solute calculations by a single calculation using an average description of the solvent environment are evaluated. This work explores the fluctuations of the average description of the system obtained in two ways: from calculations on an ensemble of geometries and from an average environment constructed from the same ensemble. To this end, classical molecular dynamics simulations of a rigid acetone solute in SPCE water are performed in order to generate an ensemble of solvent environments. From this ensemble of solvent configurations, a number of different approaches for constructing an average solvent environment are employed. We perform a thorough numerical analysis of the fluctuations of the electrostatic potential experienced by the solute, as well as the resulting fluctuations of the solute's electronic density, measured through its dipole moment and fitted atomic point charges. At the same time, we inspect the accuracy of the methods used to construct average environments. Finally, the proposed method for generating the embedding potential from an average environment density is applied to estimate the solvatochromic shift of the first excitation of acetone. In order to account for quantum confinement effects, which may be important in certain cases, the fluctuations in the shift due to the interaction with the solvent are evaluated using frozen-density-embedding theory. Our results demonstrate that, for normally distributed environments, the constructed average environment is a reasonably good representation of a fluctuating molecular solvent environment. We then provide guidance for future comparisons between these theoretical treatments of solute/solvent systems to experimental measurements.
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Affiliation(s)
| | - Christopher A Rumble
- Université de Genève, Départment de Chimie Physique 30, Quai Ernest-Ansermet, CH-1211 Genève 4, Switzerland
| | - Daniel Borgis
- Ecole Normale Supérieure, Départment de Chimie, UMR 8640, PSL University, Sorbonne University, CNRS, 75005 Paris, France
| | - Tomasz A Wesolowski
- Université de Genève, Départment de Chimie Physique 30, Quai Ernest-Ansermet, CH-1211 Genève 4, Switzerland
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Carter-Fenk K, Lao KU, Herbert JM. Predicting and Understanding Non-Covalent Interactions Using Novel Forms of Symmetry-Adapted Perturbation Theory. Acc Chem Res 2021; 54:3679-3690. [PMID: 34550669 DOI: 10.1021/acs.accounts.1c00387] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Although sometimes derided as "weak" interactions, non-covalent forces play a critical role in ligand binding and crystal packing and in determining the conformational landscape of flexible molecules. Symmetry-adapted perturbation theory (SAPT) provides a framework for accurate ab initio calculation of intermolecular interactions and furnishes a natural decomposition of the interaction energy into physically meaningful components: semiclassical electrostatics (rigorously obtained from monomer charge densities), Pauli or steric repulsion, induction (including both polarization and charge transfer), and dispersion. This decomposition helps to foster deeper understanding of non-covalent interactions and can be used to construct transferable, physics-based force fields. Separability of the SAPT interaction energy also provides the flexibility to construct composite methods, a feature that we exploit to improve the description of dispersion interactions. These are challenging to describe accurately because they arise from nonlocal electron correlation effects that appear for the first time at second order in perturbation theory but are not quantitatively described at that level.As with all quantum-chemical methods, a major limitation of SAPT is nonlinear scaling of the computational cost with respect to system size. This cost can be significantly mitigated using "SAPT0(KS)", which incorporates monomer electron correlation by means of Kohn-Sham (KS) molecular orbitals from density functional theory (DFT), as well as by an "extended" theory called XSAPT, developed by the authors. XSAPT generalizes traditional dimer SAPT to many-body systems, so that a ligand-protein interaction (for example) can be separated into contributions from individual amino acids, reducing the cost of the calculation below that of even supramolecular DFT while retaining the accuracy of high-level ab initio quantum chemistry.This Account provides an overview of the SAPT0(KS) approach and the XSAPT family of methods. Several low-cost variants are described that provide accuracy approaching that of the best ab initio benchmarks yet are affordable enough to tackle ligand-protein binding and sizable host-guest complexes. These variants include SAPT+aiD, which uses ab initio atom-atom dispersion potentials ("+aiD") in place of second-order SAPT dispersion, and also SAPT+MBD, which incorporates many-body dispersion (MBD) effects that are important in the description of nanoscale materials. Applications to drug binding highlight the size-extensive nature of dispersion, which is not a weak interaction in large systems. Other applications highlight how a physics-based analysis can sometimes upend conventional wisdom regarding intermolecular forces. In particular, careful reconsideration of π-π interactions makes clear that the quadrupolar electrostatics (or "Hunter-Sanders") model of π-π stacking should be replaced by a "van der Waals model" in which conformational preferences arise from a competition between dispersion and Pauli repulsion. Our analysis also suggests that molecular shape, rather than aromaticity per se, is the key factor driving strong stacking interactions. Looking forward, we anticipate that XSAPT-based methods can play a role in screening of drug candidates and in materials design.
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Affiliation(s)
- Kevin Carter-Fenk
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - Ka Un Lao
- Department of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, United States
| | - John M. Herbert
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
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Epifanovsky E, Gilbert ATB, Feng X, Lee J, Mao Y, Mardirossian N, Pokhilko P, White AF, Coons MP, Dempwolff AL, Gan Z, Hait D, Horn PR, Jacobson LD, Kaliman I, Kussmann J, Lange AW, Lao KU, Levine DS, Liu J, McKenzie SC, Morrison AF, Nanda KD, Plasser F, Rehn DR, Vidal ML, You ZQ, Zhu Y, Alam B, Albrecht BJ, Aldossary A, Alguire E, Andersen JH, Athavale V, Barton D, Begam K, Behn A, Bellonzi N, Bernard YA, Berquist EJ, Burton HGA, Carreras A, Carter-Fenk K, Chakraborty R, Chien AD, Closser KD, Cofer-Shabica V, Dasgupta S, de Wergifosse M, Deng J, Diedenhofen M, Do H, Ehlert S, Fang PT, Fatehi S, Feng Q, Friedhoff T, Gayvert J, Ge Q, Gidofalvi G, Goldey M, Gomes J, González-Espinoza CE, Gulania S, Gunina AO, Hanson-Heine MWD, Harbach PHP, Hauser A, Herbst MF, Hernández Vera M, Hodecker M, Holden ZC, Houck S, Huang X, Hui K, Huynh BC, Ivanov M, Jász Á, Ji H, Jiang H, Kaduk B, Kähler S, Khistyaev K, Kim J, Kis G, Klunzinger P, Koczor-Benda Z, Koh JH, Kosenkov D, Koulias L, Kowalczyk T, Krauter CM, Kue K, Kunitsa A, Kus T, Ladjánszki I, Landau A, Lawler KV, Lefrancois D, Lehtola S, Li RR, Li YP, Liang J, Liebenthal M, Lin HH, Lin YS, Liu F, Liu KY, Loipersberger M, Luenser A, Manjanath A, Manohar P, Mansoor E, Manzer SF, Mao SP, Marenich AV, Markovich T, Mason S, Maurer SA, McLaughlin PF, Menger MFSJ, Mewes JM, Mewes SA, Morgante P, Mullinax JW, Oosterbaan KJ, Paran G, Paul AC, Paul SK, Pavošević F, Pei Z, Prager S, Proynov EI, Rák Á, Ramos-Cordoba E, Rana B, Rask AE, Rettig A, Richard RM, Rob F, Rossomme E, Scheele T, Scheurer M, Schneider M, Sergueev N, Sharada SM, Skomorowski W, Small DW, Stein CJ, Su YC, Sundstrom EJ, Tao Z, Thirman J, Tornai GJ, Tsuchimochi T, Tubman NM, Veccham SP, Vydrov O, Wenzel J, Witte J, Yamada A, Yao K, Yeganeh S, Yost SR, Zech A, Zhang IY, Zhang X, Zhang Y, Zuev D, Aspuru-Guzik A, Bell AT, Besley NA, Bravaya KB, Brooks BR, Casanova D, Chai JD, Coriani S, Cramer CJ, Cserey G, DePrince AE, DiStasio RA, Dreuw A, Dunietz BD, Furlani TR, Goddard WA, Hammes-Schiffer S, Head-Gordon T, Hehre WJ, Hsu CP, Jagau TC, Jung Y, Klamt A, Kong J, Lambrecht DS, Liang W, Mayhall NJ, McCurdy CW, Neaton JB, Ochsenfeld C, Parkhill JA, Peverati R, Rassolov VA, Shao Y, Slipchenko LV, Stauch T, Steele RP, Subotnik JE, Thom AJW, Tkatchenko A, Truhlar DG, Van Voorhis T, Wesolowski TA, Whaley KB, Woodcock HL, Zimmerman PM, Faraji S, Gill PMW, Head-Gordon M, Herbert JM, Krylov AI. Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package. J Chem Phys 2021; 155:084801. [PMID: 34470363 PMCID: PMC9984241 DOI: 10.1063/5.0055522] [Citation(s) in RCA: 451] [Impact Index Per Article: 150.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
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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Affiliation(s)
- Evgeny Epifanovsky
- Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, USA
| | | | | | - Joonho Lee
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Yuezhi Mao
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | | | - Pavel Pokhilko
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Alec F. White
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Marc P. Coons
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Adrian L. Dempwolff
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Zhengting Gan
- Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, USA
| | - Diptarka Hait
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Paul R. Horn
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Leif D. Jacobson
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | | | - Jörg Kussmann
- Department of Chemistry, Ludwig Maximilian University, Butenandtstr. 7, D-81377 München, Germany
| | - Adrian W. Lange
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Ka Un Lao
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Daniel S. Levine
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | | | - Simon C. McKenzie
- Research School of Chemistry, Australian National University, Canberra, Australia
| | | | - Kaushik D. Nanda
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | | | - Dirk R. Rehn
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Marta L. Vidal
- Department of Chemistry, Technical University of Denmark, Kemitorvet Bldg. 207, DK-2800 Kgs Lyngby, Denmark
| | | | - Ying Zhu
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Bushra Alam
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Benjamin J. Albrecht
- Department of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | | | - Ethan Alguire
- Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Josefine H. Andersen
- Department of Chemistry, Technical University of Denmark, Kemitorvet Bldg. 207, DK-2800 Kgs Lyngby, Denmark
| | - Vishikh Athavale
- Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Dennis Barton
- Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg, Luxembourg
| | - Khadiza Begam
- Department of Physics, Kent State University, Kent, Ohio 44242, USA
| | - Andrew Behn
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Nicole Bellonzi
- Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Yves A. Bernard
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | | | - Hugh G. A. Burton
- Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
| | - Abel Carreras
- Donostia International Physics Center, 20080 Donostia, Euskadi, Spain
| | - Kevin Carter-Fenk
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | | | - Alan D. Chien
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, USA
| | | | - Vale Cofer-Shabica
- Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Saswata Dasgupta
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Marc de Wergifosse
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Jia Deng
- Research School of Chemistry, Australian National University, Canberra, Australia
| | | | - Hainam Do
- School of Chemistry, University of Nottingham, Nottingham, United Kingdom
| | - Sebastian Ehlert
- Mulliken Center for Theoretical Chemistry, Institut für Physikalische und Theoretische Chemie, Beringstr. 4, 53115 Bonn, Germany
| | - Po-Tung Fang
- Department of Physics, National Taiwan University, Taipei 10617, Taiwan
| | | | - Qingguo Feng
- Department of Chemistry and Biochemistry, Kent State University, Kent, Ohio 44240, USA
| | - Triet Friedhoff
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, USA
| | - James Gayvert
- Department of Chemistry, Boston University, Boston, Massachusetts 02215, USA
| | - Qinghui Ge
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Gergely Gidofalvi
- Department of Chemistry and Biochemistry, Gonzaga University, Spokane, Washington 99258, USA
| | - Matthew Goldey
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Joe Gomes
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | | | - Sahil Gulania
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Anastasia O. Gunina
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | | | - Phillip H. P. Harbach
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Andreas Hauser
- Institute of Experimental Physics, Graz University of Technology, Graz, Austria
| | | | - Mario Hernández Vera
- Department of Chemistry, Ludwig Maximilian University, Butenandtstr. 7, D-81377 München, Germany
| | - Manuel Hodecker
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Zachary C. Holden
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Shannon Houck
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - Xunkun Huang
- Department of Chemistry, Xiamen University, Xiamen 361005, China
| | - Kerwin Hui
- Department of Physics, National Taiwan University, Taipei 10617, Taiwan
| | - Bang C. Huynh
- Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
| | - Maxim Ivanov
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Ádám Jász
- Stream Novation Ltd., Práter utca 50/a, H-1083 Budapest, Hungary
| | - Hyunjun Ji
- Graduate School of Energy, Environment, Water and Sustainability (EEWS), Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Hanjie Jiang
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Benjamin Kaduk
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Sven Kähler
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Kirill Khistyaev
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Jaehoon Kim
- Graduate School of Energy, Environment, Water and Sustainability (EEWS), Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Gergely Kis
- Stream Novation Ltd., Práter utca 50/a, H-1083 Budapest, Hungary
| | | | - Zsuzsanna Koczor-Benda
- Department of Chemistry, Ludwig Maximilian University, Butenandtstr. 7, D-81377 München, Germany
| | - Joong Hoon Koh
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, USA
| | - Dimitri Kosenkov
- Department of Chemistry, Purdue University, West Lafayette, Indiana 47907, USA
| | - Laura Koulias
- Department of Chemistry and Biochemistry, Florida State University, Tallahassee, Florida 32306, USA
| | | | - Caroline M. Krauter
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Karl Kue
- Institute of Chemistry, Academia Sinica, 128, Academia Road Section 2, Nangang District, Taipei 11529, Taiwan
| | - Alexander Kunitsa
- Department of Chemistry, Boston University, Boston, Massachusetts 02215, USA
| | - Thomas Kus
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | | | - Arie Landau
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Keith V. Lawler
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Daniel Lefrancois
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | | | - Run R. Li
- Department of Chemistry and Biochemistry, Florida State University, Tallahassee, Florida 32306, USA
| | - Yi-Pei Li
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Jiashu Liang
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Marcus Liebenthal
- Department of Chemistry and Biochemistry, Florida State University, Tallahassee, Florida 32306, USA
| | - Hung-Hsuan Lin
- Institute of Chemistry, Academia Sinica, 128, Academia Road Section 2, Nangang District, Taipei 11529, Taiwan
| | - You-Sheng Lin
- Department of Physics, National Taiwan University, Taipei 10617, Taiwan
| | - Fenglai Liu
- Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, USA
| | | | | | - Arne Luenser
- Department of Chemistry, Ludwig Maximilian University, Butenandtstr. 7, D-81377 München, Germany
| | - Aaditya Manjanath
- Institute of Chemistry, Academia Sinica, 128, Academia Road Section 2, Nangang District, Taipei 11529, Taiwan
| | - Prashant Manohar
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Erum Mansoor
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Sam F. Manzer
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Shan-Ping Mao
- Department of Physics, National Taiwan University, Taipei 10617, Taiwan
| | | | - Thomas Markovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, USA
| | - Stephen Mason
- School of Chemistry, University of Nottingham, Nottingham, United Kingdom
| | - Simon A. Maurer
- Department of Chemistry, Ludwig Maximilian University, Butenandtstr. 7, D-81377 München, Germany
| | - Peter F. McLaughlin
- Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, USA
| | | | - Jan-Michael Mewes
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Stefanie A. Mewes
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Pierpaolo Morgante
- Department of Chemistry, Florida Institute of Technology, Melbourne, Florida 32901, USA
| | - J. Wayne Mullinax
- Department of Chemistry, Florida Institute of Technology, Melbourne, Florida 32901, USA
| | | | | | - Alexander C. Paul
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Suranjan K. Paul
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Fabijan Pavošević
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, USA
| | - Zheng Pei
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, Oklahoma 73019, USA
| | - Stefan Prager
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Emil I. Proynov
- Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, USA
| | - Ádám Rák
- Stream Novation Ltd., Práter utca 50/a, H-1083 Budapest, Hungary
| | - Eloy Ramos-Cordoba
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Bhaskar Rana
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Alan E. Rask
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Adam Rettig
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Ryan M. Richard
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Fazle Rob
- Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, USA
| | - Elliot Rossomme
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Tarek Scheele
- Institute for Physical and Theoretical Chemistry, University of Bremen, Bremen, Germany
| | - Maximilian Scheurer
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Matthias Schneider
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Nickolai Sergueev
- Department of Chemistry and Biochemistry, Kent State University, Kent, Ohio 44240, USA
| | - Shaama M. Sharada
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Wojciech Skomorowski
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - David W. Small
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Christopher J. Stein
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Yu-Chuan Su
- Department of Physics, National Taiwan University, Taipei 10617, Taiwan
| | - Eric J. Sundstrom
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Zhen Tao
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, USA
| | - Jonathan Thirman
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Gábor J. Tornai
- Stream Novation Ltd., Práter utca 50/a, H-1083 Budapest, Hungary
| | - Takashi Tsuchimochi
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Norm M. Tubman
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | | | - Oleg Vydrov
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Jan Wenzel
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Jon Witte
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Atsushi Yamada
- Department of Chemistry and Biochemistry, Kent State University, Kent, Ohio 44240, USA
| | - Kun Yao
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, USA
| | - Sina Yeganeh
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Shane R. Yost
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Alexander Zech
- Department of Physical Chemistry, University of Geneva, 30, Quai Ernest-Ansermet, CH-1211 Geneva 4, Switzerland
| | - Igor Ying Zhang
- Department of Chemistry, Fudan University, Shanghai 200433, China
| | - Xing Zhang
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Yu Zhang
- Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, USA
| | - Dmitry Zuev
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Alán Aspuru-Guzik
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, USA
| | - Alexis T. Bell
- Department of Chemical Engineering, University of California, Berkeley, California 94720, USA
| | - Nicholas A. Besley
- School of Chemistry, University of Nottingham, Nottingham, United Kingdom
| | - Ksenia B. Bravaya
- Department of Chemistry, Boston University, Boston, Massachusetts 02215, USA
| | - Bernard R. Brooks
- Laboratory of Computational Biophysics, National Institute of Health, Bethesda, Maryland 20892, USA
| | - David Casanova
- Donostia International Physics Center, 20080 Donostia, Euskadi, Spain
| | | | - Sonia Coriani
- Department of Chemistry, Technical University of Denmark, Kemitorvet Bldg. 207, DK-2800 Kgs Lyngby, Denmark
| | | | | | - A. Eugene DePrince
- Department of Chemistry and Biochemistry, Florida State University, Tallahassee, Florida 32306, USA
| | - Robert A. DiStasio
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, USA
| | - Andreas Dreuw
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Barry D. Dunietz
- Department of Chemistry and Biochemistry, Kent State University, Kent, Ohio 44240, USA
| | - Thomas R. Furlani
- Department of Chemistry, University at Buffalo, State University of New York, Buffalo, New York 14260, USA
| | - William A. Goddard
- Materials and Process Simulation Center, California Institute of Technology, Pasadena, California 91125, USA
| | | | - Teresa Head-Gordon
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | | | | | | | - Yousung Jung
- Graduate School of Energy, Environment, Water and Sustainability (EEWS), Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Andreas Klamt
- COSMOlogic GmbH & Co. KG, Imbacher Weg 46, D-51379 Leverkusen, Germany
| | - Jing Kong
- Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, USA
| | - Daniel S. Lambrecht
- Department of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | | | | | - C. William McCurdy
- Department of Chemistry, University of California, Davis, California 95616, USA
| | - Jeffrey B. Neaton
- Department of Physics, University of California, Berkeley, California 94720, USA
| | - Christian Ochsenfeld
- Department of Chemistry, Ludwig Maximilian University, Butenandtstr. 7, D-81377 München, Germany
| | - John A. Parkhill
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, USA
| | - Roberto Peverati
- Department of Chemistry, Florida Institute of Technology, Melbourne, Florida 32901, USA
| | - Vitaly A. Rassolov
- Department of Chemistry and Biochemistry, University of South Carolina, Columbia, South Carolina 29208, USA
| | | | | | | | - Ryan P. Steele
- Department of Chemistry and Henry Eyring Center for Theoretical Chemistry, University of Utah, Salt Lake City, Utah 84112, USA
| | - Joseph E. Subotnik
- Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Alex J. W. Thom
- Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
| | - Alexandre Tkatchenko
- Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg, Luxembourg
| | - Donald G. Truhlar
- Department of Chemistry, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - Troy Van Voorhis
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Tomasz A. Wesolowski
- Department of Physical Chemistry, University of Geneva, 30, Quai Ernest-Ansermet, CH-1211 Geneva 4, Switzerland
| | - K. Birgitta Whaley
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - H. Lee Woodcock
- Department of Chemistry, University of South Florida, Tampa, Florida 33620, USA
| | - Paul M. Zimmerman
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Shirin Faraji
- Zernike Institute for Advanced Materials, University of Groningen, 9774AG Groningen, The Netherlands
| | | | - Martin Head-Gordon
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - John M. Herbert
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Anna I. Krylov
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA,Author to whom correspondence should be addressed:
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Gray M, Herbert JM. Simplified tuning of long-range corrected density functionals for use in symmetry-adapted perturbation theory. J Chem Phys 2021; 155:034103. [PMID: 34293871 DOI: 10.1063/5.0059364] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
Long considered a failure, second-order symmetry-adapted perturbation theory (SAPT) based on Kohn-Sham orbitals, or SAPT0(KS), can be resurrected for semiquantitative purposes using long-range corrected density functionals whose asymptotic behavior is adjusted separately for each monomer. As in other contexts, correct asymptotic behavior can be enforced via "optimal tuning" based on the ionization energy theorem of density functional theory, but the tuning procedure is tedious, expensive for large systems, and comes with a troubling dependence on system size. Here, we show that essentially identical results are obtained using a fast, convenient, and automated tuning procedure based on the size of the exchange hole. In conjunction with "extended" (X)SAPT methods that improve the description of dispersion, this procedure achieves benchmark-quality interaction energies, along with the usual SAPT energy decomposition, without the hassle of system-specific tuning.
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Affiliation(s)
- Montgomery Gray
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - John M Herbert
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
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Loco D, Lagardère L, Adjoua O, Piquemal JP. Atomistic Polarizable Embeddings: Energy, Dynamics, Spectroscopy, and Reactivity. Acc Chem Res 2021; 54:2812-2822. [PMID: 33961401 PMCID: PMC8264944 DOI: 10.1021/acs.accounts.0c00662] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Indexed: 12/20/2022]
Abstract
The computational modeling of realistic extended systems, relevant in, e.g., Chemistry and Biophysics, is a fundamental problem of paramount importance in contemporary research. Enzymatic catalysis and photoinduced processes in pigment-protein complexes are typical problems targeted by computer-aided approaches, to complement experiments as interpretative tools at a molecular scale. The daunting complexity of this task lies in between the opposite stringent requirements of results' reliability for structural/dynamical properties and related intermolecular interactions, and a mandatory principle of realism in the modeling strategy. Therefore, in practice, a truly realistic computational model of a biologically relevant system can easily fail to meet the accuracy requirement, in order to balance the excessive computational cost necessary to reach the desired precision.To address such an "accuracy vs reality" dualistic requirement, mixed quantum mechanics/classical mechanics approaches within Atomistic (i.e., preserving the discrete particle configuration) Polarizable Embeddings (QM/APEs) methods have been proposed over the years. In this Account, we review recent developments in the design and application of general QM/APE methods, targeting situations where a local intrinsically quantum behavior is coupled to a large molecular system (i.e., an environment), often involving processes with different dynamical time scales, in order to avoid brute-force, unpractical quantum chemistry calculations on the complete system.In the first place, our interest is devoted to the available APEs models presently implemented in computational software, highlighting the quantum chemistry methods that can be used to treat the QM subsystem. We review the coupling strategy between the QM subsystem and the APE, which requires to examine the way the QM/MM mutual interactions are accounted for and how the polarization of the classical environment is considered with respect to (wrt) the quantum variables. Because of the need of reliable molecular and macromolecular structures, a pivotal aspect to address here is the handling of the system dynamics (i.e., gradients wrt nuclear positions are required), especially for large molecular assemblies composed by an overwhelming number of atoms, exploring many conformations on a complex energy landscape.Alongside, we highlight our views on the necessary steps to take toward more accurate general-purposes and transferable explicit embeddings. The main objective to achieve here is to design a more physically grounded multiscale approach. To do so, one should apply advanced new generation classical models to account for refined induction effects that are able to (i) improve the quality of QM/MM interaction energies; (ii) enhance transferability by avoiding the compulsory partial (or total) reparameterization of the classical model. Moreover, the extension of recent developments originating from the field of advanced classical molecular dynamics (MD) to the realm of QM/APE methods is a key direction to improve both speed and efficiency for the phase space exploration of systems of growing size and complexity.Lastly, we point out specific research topics where an advanced QM/APE dynamics can certainly shed some light. For example, we discuss chemical reactions in "harsh" environments and the case of spectroscopic theoretical modeling where the inclusion of refined environment effects is often mandatory.
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Affiliation(s)
- Daniele Loco
- Laboratoire
de Chimie Théorique, Sorbonne Université,
UMR 7616 CNRS, 75005 Paris, France
| | - Louis Lagardère
- Laboratoire
de Chimie Théorique, Sorbonne Université,
UMR 7616 CNRS, 75005 Paris, France
- Intitut
Parisien de Chimie Physique et Théorique, Sorbonne Université, FR 2622 CNRS, 75005 Paris, France
| | - Olivier Adjoua
- Laboratoire
de Chimie Théorique, Sorbonne Université,
UMR 7616 CNRS, 75005 Paris, France
| | - Jean-Philip Piquemal
- Laboratoire
de Chimie Théorique, Sorbonne Université,
UMR 7616 CNRS, 75005 Paris, France
- Institut
Universitaire de France, F-75005 Paris, France
- Department
of Biomedical Engineering, The University
of Texas at Austin, Austin, Texas 78712, United States
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14
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Yan Z, Li X, Chung LW. Multiscale Quantum Refinement Approaches for Metalloproteins. J Chem Theory Comput 2021; 17:3783-3796. [PMID: 34032440 DOI: 10.1021/acs.jctc.1c00148] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Biomolecules with metal ion(s) (e.g., metalloproteins) play many important biological roles. However, accurate structural determination of metalloproteins, particularly those containing transition metal ion(s), is challenging due to their complicated electronic structure, complex bonding of metal ions, and high number of conformations in biomolecules. Quantum refinement, which was proposed to combine crystallographic data with computational chemistry methods by several groups, can improve the local structures of some proteins. In this study, a quantum refinement method combining several multiscale computational schemes with experimental (X-ray diffraction) information was developed for metalloproteins. Various quantum refinement approaches using different ONIOM (our own N-layered integrated molecular orbital and molecular mechanics) combinations of quantum mechanics (QM), semiempirical (SE), and molecular mechanics (MM) methods were conducted to assess the performance and reliability on the refined local structure in two metalloproteins. The structures for two (Cu- or Zn-containing) metalloproteins were refined by combining two-layer ONIOM2(QM1/QM2) and ONIOM2(QM/MM) and three-layer ONIOM3(QM1/QM2/MM) schemes with experimental data. The accuracy of the quantum-refined metal binding sites was also examined and compared in these multiscale quantum refinement calculations. ONIOM3(QM/SE/MM) schemes were found to give good results with lower computational costs and were proposed to be a good choice for the multiscale computational scheme for quantum refinement calculations of metal binding site(s) in metalloproteins with high efficiency. Additionally, a two-center ONIOM approach was employed to speed up the quantum refinement calculations for the Zn metalloprotein with two remote active sites/ligands. Moreover, a recent quantum-embedding wavefunction-in-density functional theory (WF-in-DFT) method was also adopted as the high-level method in unprecedented ONIOM2(CCSD-in-B3LYP/MM) and ONIOM3(CCSD-in-B3LYP/SE/MM) calculations, which can be regarded as novel pseudo-three- and pseudo-four-layer ONIOM methods, respectively, to refine the key Zn binding site at the coupled-cluster singles and doubles (CCSD) level. These refined results indicate that multiscale quantum refinement schemes can be used to improve the structural accuracy obtained for local metal binding site(s) in metalloproteins with high efficiency.
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Affiliation(s)
- Zeyin Yan
- Shenzhen Grubbs Institute, Department of Chemistry and Guangdong Provincial Key Laboratory of Catalysis, Southern University of Science and Technology, Shenzhen 518055, China
| | - Xin Li
- Shenzhen Grubbs Institute, Department of Chemistry and Guangdong Provincial Key Laboratory of Catalysis, Southern University of Science and Technology, Shenzhen 518055, China
| | - Lung Wa Chung
- Shenzhen Grubbs Institute, Department of Chemistry and Guangdong Provincial Key Laboratory of Catalysis, Southern University of Science and Technology, Shenzhen 518055, China
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15
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Wei H, Qi R, Wang J, Cieplak P, Duan Y, Luo R. Efficient formulation of polarizable Gaussian multipole electrostatics for biomolecular simulations. J Chem Phys 2021; 153:114116. [PMID: 32962395 DOI: 10.1063/5.0019560] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Molecular dynamics simulations of biomolecules have been widely adopted in biomedical studies. As classical point-charge models continue to be used in routine biomolecular applications, there have been growing demands on developing polarizable force fields for handling more complicated biomolecular processes. Here, we focus on a recently proposed polarizable Gaussian Multipole (pGM) model for biomolecular simulations. A key benefit of pGM is its screening of all short-range electrostatic interactions in a physically consistent manner, which is critical for stable charge-fitting and is needed to reproduce molecular anisotropy. Another advantage of pGM is that each atom's multipoles are represented by a single Gaussian function or its derivatives, allowing for more efficient electrostatics than other Gaussian-based models. In this study, we present an efficient formulation for the pGM model defined with respect to a local frame formed with a set of covalent basis vectors. The covalent basis vectors are chosen to be along each atom's covalent bonding directions. The new local frame can better accommodate the fact that permanent dipoles are primarily aligned along covalent bonds due to the differences in electronegativity of bonded atoms. It also allows molecular flexibility during molecular simulations and facilitates an efficient formulation of analytical electrostatic forces without explicit torque computation. Subsequent numerical tests show that analytical atomic forces agree excellently with numerical finite-difference forces for the tested system. Finally, the new pGM electrostatics algorithm is interfaced with the particle mesh Ewald (PME) implementation in Amber for molecular simulations under the periodic boundary conditions. To validate the overall pGM/PME electrostatics, we conducted an NVE simulation for a small water box of 512 water molecules. Our results show that to achieve energy conservation in the polarizable model, it is important to ensure enough accuracy on both PME and induction iteration. It is hoped that the reformulated pGM model will facilitate the development of future force fields based on the pGM electrostatics for applications in biomolecular systems and processes where polarization plays crucial roles.
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Affiliation(s)
- Haixin Wei
- Departments of Molecular Biology and Biochemistry, Chemical and Biomolecular Engineering, Materials Science and Engineering, and Biomedical Engineering, Graduate Program in Chemical and Materials Physics, University of California, Irvine, Irvine, California 92697, USA
| | - Ruxi Qi
- Departments of Molecular Biology and Biochemistry, Chemical and Biomolecular Engineering, Materials Science and Engineering, and Biomedical Engineering, Graduate Program in Chemical and Materials Physics, University of California, Irvine, Irvine, California 92697, USA
| | - Junmei Wang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, USA
| | - Piotr Cieplak
- SBP Medical Discovery Institute, 10901 North Torrey Pines Road, La Jolla, California 92037, USA
| | - Yong Duan
- UC Davis Genome Center and Department of Biomedical Engineering, University of California, Davis, One Shields Avenue, Davis, California 95616, USA
| | - Ray Luo
- Departments of Molecular Biology and Biochemistry, Chemical and Biomolecular Engineering, Materials Science and Engineering, and Biomedical Engineering, Graduate Program in Chemical and Materials Physics, University of California, Irvine, Irvine, California 92697, USA
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16
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Watanabe HC, Yamada M, Suzuki Y. Proton transfer in bulk water using the full adaptive QM/MM method: integration of solute- and solvent-adaptive approaches. Phys Chem Chem Phys 2021; 23:8344-8360. [PMID: 33875999 DOI: 10.1039/d1cp00116g] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The quantum mechanical/molecular mechanical (QM/MM) method is a hybrid molecular simulation technique that increases the accessibility of local electronic structures of large systems. The technique combines the benefit of accuracy found in the QM method and that of cost efficiency found in the MM method. However, it is difficult to directly apply the QM/MM method to the dynamics of solution systems, particularly for proton transfer. As explained in the Grotthuss mechanism, proton transfer is a structural interconversion between hydronium ions and solvent water molecules. Hence, when the QM/MM method is applied, an adaptive treatment, namely on-the-fly revisions on molecular definitions, is required for both the solute and solvent. Although several solvent-adaptive methods have been proposed, a full adaptive framework, which is an approach that also considers adaptation for solutes, remains untapped. In this paper, we propose a new numerical expression for the coordinates of the excess proton and its control algorithm. Furthermore, we confirm that this method can stably and accurately simulate proton transfer dynamics in bulk water.
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Affiliation(s)
- Hiroshi C Watanabe
- Quantum Computing Center, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan.
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17
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Zhou S, Wang Y, Gao J. Solvation Induction of Free Energy Barriers of Decarboxylation Reactions in Aqueous Solution from Dual-Level QM/MM Simulations. JACS AU 2021; 1:233-244. [PMID: 34467287 PMCID: PMC8395672 DOI: 10.1021/jacsau.0c00110] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Indexed: 06/13/2023]
Abstract
Carbon dioxide capture, corresponding to the recombination process of decarboxylation reactions of organic acids, is typically barrierless in the gas phase and has a relatively low barrier in aprotic solvents. However, these processes often encounter significant solvent-reorganization-induced barriers in aqueous solution if the decarboxylation product is not immediately protonated. Both the intrinsic stereoelectronic effects and solute-solvent interactions play critical roles in determining the overall decarboxylation equilibrium and free energy barrier. An understanding of the interplay of these factors is important for designing novel materials applied to greenhouse gas capture and storage as well as for unraveling the catalytic mechanisms of a range of carboxy lyases in biological CO2 production. A range of decarboxylation reactions of organic acids with rates spanning nearly 30 orders of magnitude have been examined through dual-level combined quantum mechanical and molecular mechanical simulations to help elucidate the origin of solvation-induced free energy barriers for decarboxylation and the reverse carboxylation reactions in water.
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Affiliation(s)
- Shaoyuan Zhou
- Institute
of Theoretical Chemistry, Jilin University, Changchun 130023, China
- Institute
of Systems and Physical Biology, Shenzhen
Bay Laboratory, Shenzhen 518055, China
| | - Yingjie Wang
- Institute
of Systems and Physical Biology, Shenzhen
Bay Laboratory, Shenzhen 518055, China
| | - Jiali Gao
- Institute
of Systems and Physical Biology, Shenzhen
Bay Laboratory, Shenzhen 518055, China
- Beijing
University Shenzhen Graduate School, Shenzhen 518055, China
- Department
of Chemistry and Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455, United States
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18
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Qi Y, Ren H, Li H, Zhang DL, Cui HQ, Weng JB, Li GH, Wang GY, Li Y. Interaction energy prediction of organic molecules using deep tensor neural network. CHINESE J CHEM PHYS 2021. [DOI: 10.1063/1674-0068/cjcp2009163] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Yuan Qi
- Dalian Institute of Chemical Physics, State Key Laboratory of Molecular Reaction Dynamics, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hong Ren
- Aerospace Center Hospital, Department of Ophthalmology, Beijing 100049, China
| | - Hong Li
- Dalian Naval Academy, Department of Basic Sciences, Dalian 116018, China
| | - Ding-lin Zhang
- Dalian Institute of Chemical Physics, State Key Laboratory of Molecular Reaction Dynamics, Dalian 116023, China
| | - Hong-qiang Cui
- Dalian Institute of Chemical Physics, State Key Laboratory of Molecular Reaction Dynamics, Dalian 116023, China
| | - Jun-ben Weng
- Dalian Institute of Chemical Physics, State Key Laboratory of Molecular Reaction Dynamics, Dalian 116023, China
| | - Guo-hui Li
- Dalian Institute of Chemical Physics, State Key Laboratory of Molecular Reaction Dynamics, Dalian 116023, China
| | - Gui-yan Wang
- Harbin Engineering University, College of Intelligent Systems Science and Engineering, Harbin 150001, China
| | - Yan Li
- Dalian Institute of Chemical Physics, State Key Laboratory of Molecular Reaction Dynamics, Dalian 116023, China
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19
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Lambros E, Lipparini F, Cisneros GA, Paesani F. A Many-Body, Fully Polarizable Approach to QM/MM Simulations. J Chem Theory Comput 2020; 16:7462-7472. [PMID: 33213149 PMCID: PMC8131112 DOI: 10.1021/acs.jctc.0c00932] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
We present a new development in quantum mechanics/molecular mechanics (QM/MM) methods by replacing conventional MM models with data-driven many-body (MB) representations rigorously derived from high-level QM calculations. The new QM/MM approach builds on top of mutually polarizable QM/MM schemes developed for polarizable force fields with inducible dipoles and uses permutationally invariant polynomials to effectively account for quantum-mechanical contributions (e.g., exchange-repulsion and charge transfer and penetration) that are difficult to describe by classical expressions adopted by conventional MM models. Using the many-body MB-pol and MB-DFT potential energy functions for water, which include explicit two-body and three-body terms fitted to reproduce the corresponding CCSD(T) and PBE0 two-body and three-body energies for water, we demonstrate a smooth energetic transition as molecules are transferred between QM and MM regions, without the need of a transition layer. By effectively elevating the accuracy of both the MM region and the QM/MM interface to that of the QM region, the new QM/MB-MM approach achieves an accuracy comparable to that obtained with a fully QM treatment of the entire system.
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Affiliation(s)
- Eleftherios Lambros
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Filippo Lipparini
- Dipartimento di Chimica e Chimica Industriale, University of Pisa, via G. Moruzzi 13, 56124 Pisa, Italy
| | | | - Francesco Paesani
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
- Materials Science and Engineering, University of California San Diego, La Jolla, California 92093, United States
- San Diego Supercomputer Center, University of California San Diego, La Jolla, California 92093, United States
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20
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Abstract
High-order charge transfer is incorporated into the fragment molecular orbital (FMO) method using a charge transfer state with fractional charges. This state is used for a partition analysis of properties based on segments that may be different from fragments in FMO. The partition analysis is also formulated for calculations without fragmentation. All development in this work is limited to density-functional tight-binding. The analysis is applied to a water cluster, crambin (PDB: 1CBN), and two complexes of Trp-cage (1L2Y) with ligands. The contributions of functional groups in ligands are obtained, providing useful information for drug discovery.
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Affiliation(s)
- Dmitri G Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba 305-8568, Japan
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21
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Nottoli M, Mennucci B, Lipparini F. Excited state Born-Oppenheimer molecular dynamics through coupling between time dependent DFT and AMOEBA. Phys Chem Chem Phys 2020; 22:19532-19541. [PMID: 32844823 DOI: 10.1039/d0cp03688a] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
We present the implementation of excited state Born-Oppenheimer molecular dynamics (BOMD) using a polarizable QM/MM approach based on a time-dependent density functional theory (TDDFT) formulation and the AMOEBA force field. The implementation relies on an interface between Tinker and Gaussian software and it uses an algorithm for the calculation of QM/MM energy and forces which scales linearly with the number of MM atoms. The resulting code can perform TDDFT/AMOEBA BOMD simulations on real-life systems with standard computational resources. As a test case, the method is applied to the study of the mechanism of locally-excited to charge-transfer conversion in dimethylaminobenzonitrile in a polar solvent. Our simulations confirm that such a conversion is governed by the twisting of the dimethylamino group which is accompanied by an important reorientation of solvent molecules.
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Affiliation(s)
- Michele Nottoli
- Dipartimento di Chimica e Chimica Industriale, Università di Pisa, Via G. Moruzzi 13, 56124 Pisa, Italy.
| | - Benedetta Mennucci
- Dipartimento di Chimica e Chimica Industriale, Università di Pisa, Via G. Moruzzi 13, 56124 Pisa, Italy.
| | - Filippo Lipparini
- Dipartimento di Chimica e Chimica Industriale, Università di Pisa, Via G. Moruzzi 13, 56124 Pisa, Italy.
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22
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Chen X, Qu Z, Suo B, Gao J. A self-consistent coulomb bath model using density fitting. J Comput Chem 2020; 41:1698-1708. [PMID: 32369627 DOI: 10.1002/jcc.26211] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 03/02/2020] [Accepted: 04/05/2020] [Indexed: 12/24/2022]
Abstract
A self-consistent Coulomb bath model is presented to provide an accurate and efficient way of performing calculations for interfragment electrostatic and polarization interactions. In this method, a condensed-phase system is partitioned into molecular fragment blocks. Each fragment is embedded in the Coulomb bath due to other fragments. Importantly, the present Coulomb bath is represented using a density fitting method in which the electron densities of molecular fragments are fitted using an atom-centered auxiliary basis set of Gaussian type. The Coulomb bath is incorporated into an effective Hamiltonian for each fragment, with which the electron density is optimized through an iterative double self-consistent field (DSCF) procedure to realize the mutual many-body polarization effects. In this work, the accuracy of interfragment interaction energies enumerated using the Coulomb bath is tested, showing a good agreement with the exact results from an energy decomposition analysis. The qualitative features of many-body polarization effects are visualized by electron density difference plots. It is also shown that the present DSCF method can yield fast and robust convergence with near-linear scaling in performance with increase in system size.
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Affiliation(s)
- Xin Chen
- Laboratory of Theoretical and Computational Chemistry, Institute of Theoretical Chemistry, Jilin University, Changchun, China.,Shenzhen Bay Laboratory, Shenzhen, China
| | - Zexing Qu
- Laboratory of Theoretical and Computational Chemistry, Institute of Theoretical Chemistry, Jilin University, Changchun, China
| | - Bingbing Suo
- Shaanxi Key Laboratory for Theoretical Physics Frontiers, Institute of Modern Physics, Northwest University, Xi'an, Shaanxi, China
| | - Jiali Gao
- Shenzhen Bay Laboratory, Shenzhen, China.,Laboratory of Computational Chemistry and Drug Design, Peking University Shenzhen Graduate School, Shenzhen, China.,Department of Chemistry and Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota, USA
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23
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Walton JR, Rivera-Rivera LA. Force Based Canonical Approximation of Molecular Potentials: Average Force versus Pointwise Force. J Phys Chem A 2020; 124:1648-1658. [PMID: 32065524 DOI: 10.1021/acs.jpca.9b10685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
This work presents a new force-based canonical approach that utilizes the average force rather than the pointwise force, on which previously developed canonical approaches were based. Advantageously, the average force based method only requires the evaluation of the potential function and not its derivative. The average force and the pointwise force based methods are applied to a variety of diatomic molecules, and their accuracy is compared. It is demonstrated that the average force based method gives an improved accuracy compared to the pointwise force based method. This improved accuracy is attributed to the fact that the average force based method eliminates the need to use the numerical approximation of the derivative of the potential function that, in practice, is only known at discrete points. In addition, an algorithm is developed to apply the average force based method as a practical tool for generating potential curves for pairwise interatomic interactions utilizing the classical Lennard-Jones potential as reference. Moreover, application of the average force based method leads to a new canonical approximation paradigm. In this new paradigm, only the coordinates of the equilibrium configuration (the bottom of the potential well) of a molecule are required for accurate generation of the potential function. Moreover, theoretical results are presented, demonstrating the effectiveness of the canonical transformation procedure in producing highly accurate potential approximations. In particular, it is proved that a certain general set of qualitative conditions on potential-like functions are sufficient for a given potential function to be in the same canonical transformation class as a (dimensionless) Lennard-Jones potential. For functions satisfying these assumptions, it is shown that they have canonical approximations with arbitrarily small approximation errors.
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Affiliation(s)
- Jay R Walton
- Department of Mathematics , Texas A&M University , College Station , Texas 77843-3368 , United States
| | - Luis A Rivera-Rivera
- Department of Physical Sciences , Ferris State University , Big Rapids , Michigan 49307 , United States
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24
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Abstract
Basic concepts in the analysis of binding using the fragment molecular orbital method are discussed at length: polarization, desolvation, and interaction. The components in the pair interaction energy decomposition analysis are introduced, and the analysis is illustrated for a water dimer and a protein-ligand complex.
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Affiliation(s)
- Dmitri G Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan.
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25
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Bondanza M, Nottoli M, Cupellini L, Lipparini F, Mennucci B. Polarizable embedding QM/MM: the future gold standard for complex (bio)systems? Phys Chem Chem Phys 2020; 22:14433-14448. [DOI: 10.1039/d0cp02119a] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
We provide a perspective of the induced dipole formulation of polarizable QM/MM, showing how efficient implementations will enable their application to the modeling of dynamics, spectroscopy, and reactivity in complex biosystems.
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Affiliation(s)
- Mattia Bondanza
- Dipartimento di Chimica e Chimica Industriale
- Università di Pisa
- I-56124 Pisa
- Italy
| | - Michele Nottoli
- Dipartimento di Chimica e Chimica Industriale
- Università di Pisa
- I-56124 Pisa
- Italy
| | - Lorenzo Cupellini
- Dipartimento di Chimica e Chimica Industriale
- Università di Pisa
- I-56124 Pisa
- Italy
| | - Filippo Lipparini
- Dipartimento di Chimica e Chimica Industriale
- Università di Pisa
- I-56124 Pisa
- Italy
| | - Benedetta Mennucci
- Dipartimento di Chimica e Chimica Industriale
- Università di Pisa
- I-56124 Pisa
- Italy
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26
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Abstract
Since the introduction of the fragment molecular orbital method 20 years ago, fragment-based approaches have occupied a small but growing niche in quantum chemistry. These methods decompose a large molecular system into subsystems small enough to be amenable to electronic structure calculations, following which the subsystem information is reassembled in order to approximate an otherwise intractable supersystem calculation. Fragmentation sidesteps the steep rise (with respect to system size) in the cost of ab initio calculations, replacing it with a distributed cost across numerous computer processors. Such methods are attractive, in part, because they are easily parallelizable and therefore readily amenable to exascale computing. As such, there has been hope that distributed computing might offer the proverbial "free lunch" in quantum chemistry, with the entrée being high-level calculations on very large systems. While fragment-based quantum chemistry can count many success stories, there also exists a seedy underbelly of rarely acknowledged problems. As these methods begin to mature, it is time to have a serious conversation about what they can and cannot be expected to accomplish in the near future. Both successes and challenges are highlighted in this Perspective.
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Affiliation(s)
- John M Herbert
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
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27
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Kaliakin DS, Fedorov DG, Alexeev Y, Varganov SA. Locating Minimum Energy Crossings of Different Spin States Using the Fragment Molecular Orbital Method. J Chem Theory Comput 2019; 15:6074-6084. [DOI: 10.1021/acs.jctc.9b00641] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Affiliation(s)
- Danil S. Kaliakin
- Department of Chemistry, University of Nevada, Reno, 1664 N. Virginia Street, Reno, Nevada 89557-0216, United States
| | - Dmitri G. Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba 305-8568, Japan
| | - Yuri Alexeev
- Computational Science Division and Argonne Leadership Computing Facility, Argonne National Laboratory, Argonne, Illinois 60439, United States
| | - Sergey A. Varganov
- Department of Chemistry, University of Nevada, Reno, 1664 N. Virginia Street, Reno, Nevada 89557-0216, United States
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28
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Fedorov DG. Solvent Screening in Zwitterions Analyzed with the Fragment Molecular Orbital Method. J Chem Theory Comput 2019; 15:5404-5416. [PMID: 31461277 DOI: 10.1021/acs.jctc.9b00715] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Based on induced solvent charges, a new model of solvent screening is developed in the framework of the fragment molecular orbital combined with the polarizable continuum model. The developed model is applied to analyze interactions in a prototypical zwitterionic system, sodium chloride in water, and it is shown that the large underestimation of the interaction in the original solvent screening based on local charges is successfully corrected. The model is also applied to a complex of the Trp-cage (PDB: 1L2Y ) miniprotein with an anionic ligand, and the physical factors determined protein-ligand binding in solution are unraveled.
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Affiliation(s)
- Dmitri G Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat) , National Institute of Advanced Industrial Science and Technology (AIST) , Central 2, Umezono 1-1-1 , Tsukuba 305-8568 , Japan
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29
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Conrad JA, Kim S, Gordon MS. Ionic liquids from a fragmented perspective. Phys Chem Chem Phys 2019; 21:16878-16888. [PMID: 31359024 DOI: 10.1039/c9cp02836f] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
The efficacy of using fragmentation methods, such as the effective fragment potential, the fragment molecular orbital and the effective fragment molecular orbital methods is discussed. The advantages and current limitations of these methods are considered, potential improvements are suggested, and a prognosis for the future is provided.
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Affiliation(s)
- Justin A Conrad
- Department of Chemistry, Iowa State University, Ames, IA 50014, USA.
| | - Shinae Kim
- Department of Chemistry, Iowa State University, Ames, IA 50014, USA.
| | - Mark S Gordon
- Department of Chemistry, Iowa State University, Ames, IA 50014, USA.
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30
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Liu J, Rana B, Liu KY, Herbert JM. Variational Formulation of the Generalized Many-Body Expansion with Self-Consistent Charge Embedding: Simple and Correct Analytic Energy Gradient for Fragment-Based ab Initio Molecular Dynamics. J Phys Chem Lett 2019; 10:3877-3886. [PMID: 31251619 DOI: 10.1021/acs.jpclett.9b01214] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
The many-body expansion (MBE) and its extension to overlapping fragments, the generalized (G)MBE, constitute the theoretical basis for most fragment-based approaches for large-scale quantum chemistry. We reformulate the GMBE for use with embedding charges determined self-consistently from the fragment wave functions, in a manner that preserves the variational nature of the underlying self-consistent field method. As a result, the analytic gradient retains the simple "sum of fragment gradients" form that is often assumed in practice, sometimes incorrectly. This obviates (without approximation) the need to solve coupled-perturbed equations, and we demonstrate stable, fragment-based ab initio molecular dynamics simulations using this technique. Energy conservation fails when charge-response contributions to the Fock matrix are neglected, even while geometry optimizations and vibrational frequency calculations may yet be accurate. Stable simulations can be recovered by means of straightforward modifications introduced here, providing a general paradigm for fragment-based ab initio molecular dynamics.
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Affiliation(s)
- Jie Liu
- Department of Chemistry and Biochemistry , The Ohio State University , Columbus , Ohio 43210 , United States
| | - Bhaskar Rana
- Department of Chemistry and Biochemistry , The Ohio State University , Columbus , Ohio 43210 , United States
| | - Kuan-Yu Liu
- Department of Chemistry and Biochemistry , The Ohio State University , Columbus , Ohio 43210 , United States
| | - John M Herbert
- Department of Chemistry and Biochemistry , The Ohio State University , Columbus , Ohio 43210 , United States
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31
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Ren S, Lipparini F, Mennucci B, Caricato M. Coupled Cluster Theory with Induced Dipole Polarizable Embedding for Ground and Excited States. J Chem Theory Comput 2019; 15:4485-4496. [PMID: 31265278 DOI: 10.1021/acs.jctc.9b00468] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
In this work, we present the theory and implementation of the coupled cluster single and double excitations (CCSD) method combined with a classical polarizable molecular mechanics force field (MMPol) based on the induced dipole model. The method is developed to compute electronic excitation energies within the state specific (SS) and linear response (LR) formalisms for the interaction of the quantum mechanical and classical regions. Furthermore, we consider an approximate expression of the correlation energy, originally developed for CCSD with implicit solvation models, where the interaction term is linear in the coupled cluster density. This approximation allows us to include the explicit contribution of the environment to the CC equations without increasing the computational effort. The test calculations on microsolvated systems, where the CCSD/MMPol method is compared to full CCSD calculations, demonstrates the reliability of this computational protocol for all interaction schemes (errors < 2%). We also show that it is important to include induced dipoles on all atom centers of the classical region and that too diffuse functions in the basis set may be problematic due to too strong interaction with the environment.
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Affiliation(s)
- Sijin Ren
- Department of Chemistry , University of Kansas , 1567 Irving Hill Road , Lawrence , Kansas 66044 , United States
| | - Filippo Lipparini
- Department of Chemistry , Università di Pisa , Via Giuseppe Moruzzi , 13 56124 Pisa , Italy
| | - Benedetta Mennucci
- Department of Chemistry , Università di Pisa , Via Giuseppe Moruzzi , 13 56124 Pisa , Italy
| | - Marco Caricato
- Department of Chemistry , University of Kansas , 1567 Irving Hill Road , Lawrence , Kansas 66044 , United States
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32
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Fedorov DG, Brekhov A, Mironov V, Alexeev Y. Molecular Electrostatic Potential and Electron Density of Large Systems in Solution Computed with the Fragment Molecular Orbital Method. J Phys Chem A 2019; 123:6281-6290. [DOI: 10.1021/acs.jpca.9b04936] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Dmitri G. Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba, 305-8568, Japan
| | - Anton Brekhov
- Department of Chemistry, Lomonosov Moscow State University, Moscow, 119991, Russian Federation
| | - Vladimir Mironov
- Department of Chemistry, Lomonosov Moscow State University, Moscow, 119991, Russian Federation
| | - Yuri Alexeev
- Argonne Leadership Computing Facility and Computational Science Division, Argonne National Laboratory, Argonne, Illinois, 60439, United States
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33
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Liu J, Sun H, Glover WJ, He X. Prediction of Excited-State Properties of Oligoacene Crystals Using Fragment-Based Quantum Mechanical Method. J Phys Chem A 2019; 123:5407-5417. [PMID: 31187994 DOI: 10.1021/acs.jpca.8b12552] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
A fundamental understanding of the excited-state properties of molecular crystals is of central importance for their optoelectronics applications. In this study, we developed the electrostatically embedded generalized molecular fractionation (EE-GMF) method for the quantitative characterization of the excited-state properties of locally excited molecular clusters. The accuracy of the EE-GMF method is systematically assessed for oligoacene crystals. Our result demonstrates that the EE-GMF method is capable of providing the lowest vertical singlet (S1) and triplet excitation energies (T1), in excellent agreement with the full-system quantum mechanical calculations. Using this method, we also investigated the performance of different density functionals in predicting the excited-state properties of the oligoacene crystals. Among the 13 tested functionals, B3LYP and MN15 give the two lowest overall mean unsigned errors with reference to the experimental S1 and T1 excitation energies. The EE-GMF approach can be readily utilized for studying the excited-state properties of large-scale organic solids at diverse ab initio levels.
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Affiliation(s)
- Jinfeng Liu
- Department of Basic Medicine and Clinical Pharmacy , China Pharmaceutical University , Nanjing 210009 , China
| | | | - William J Glover
- NYU Shanghai , Shanghai 200122 , China.,NYU-ECNU Center for Computational Chemistry at NYU Shanghai , Shanghai 200062 , China.,Department of Chemistry , New York University , New York , New York 10003 , United States
| | - Xiao He
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai , Shanghai 200062 , China
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34
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Carter-Fenk K, Lao KU, Liu KY, Herbert JM. Accurate and Efficient ab Initio Calculations for Supramolecular Complexes: Symmetry-Adapted Perturbation Theory with Many-Body Dispersion. J Phys Chem Lett 2019; 10:2706-2714. [PMID: 31063380 DOI: 10.1021/acs.jpclett.9b01156] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Symmetry-adapted perturbation theory (SAPT) provides a chemically meaningful energy decomposition scheme for nonbonded interactions that is useful for interpretive purposes. Although formally a dimer theory, we have previously introduced an "extended" version (XSAPT) that incorporates many-body polarization via self-consistent charge embedding. Here, we extend the XSAPT methodology to include nonadditive dispersion, using a modified form of the many-body dispersion (MBD) method of Tkatchenko and co-workers. Dispersion interactions beyond the pairwise atom-atom approximation improve total interaction energies even in small systems, and for large π-stacked complexes these corrections can amount to several kilocalories per mole. The XSAPT+MBD method introduced here achieves errors of ≲1 kcal/mol (as compared to high-level ab initio benchmarks) for the L7 data set of large dispersion-bound complexes and ≲4 kcal/mol (as compared to experiment) for the S30L data set of host-guest complexes. This is superior to the best contemporary density functional methods for noncovalent interactions, at comparable or lower cost. XSAPT+MBD represents a promising method for application to supramolecular assemblies, including protein-ligand binding.
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Affiliation(s)
- Kevin Carter-Fenk
- Department of Chemistry and Biochemistry , The Ohio State University , Columbus , Ohio 43210 , United States
| | - Ka Un Lao
- Department of Chemistry and Chemical Biology , Cornell University , Ithaca , New York 14853 , United States
| | - Kuan-Yu Liu
- Department of Chemistry and Biochemistry , The Ohio State University , Columbus , Ohio 43210 , United States
| | - John M Herbert
- Department of Chemistry and Biochemistry , The Ohio State University , Columbus , Ohio 43210 , United States
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35
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Holden ZC, Rana B, Herbert JM. Analytic gradient for the QM/MM-Ewald method using charges derived from the electrostatic potential: Theory, implementation, and application to ab initio molecular dynamics simulation of the aqueous electron. J Chem Phys 2019; 150:144115. [DOI: 10.1063/1.5089673] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
Affiliation(s)
- Zachary C. Holden
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Bhaskar Rana
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - John M. Herbert
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
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36
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37
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Wang J, Cieplak P, Luo R, Duan Y. Development of Polarizable Gaussian Model for Molecular Mechanical Calculations I: Atomic Polarizability Parameterization To Reproduce ab Initio Anisotropy. J Chem Theory Comput 2019; 15:1146-1158. [PMID: 30645118 PMCID: PMC7197406 DOI: 10.1021/acs.jctc.8b00603] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
A set of atomic polarizability parameters for a new polarizable Gaussian model (pGM) has been developed with the goal to accurately reproduce the polarizability anisotropy, taking advantage of its ability to attenuate all short-range electrostatic interactions, by fitting the ab initio molecular polarizability tensors ( A pq) calculated at the B3LYP/aug-cc-pVTZ level. For comparison, we also rederived the parameters for three Thole models in which the 1-2 (bonded), 1-3 (separated by two bonds), and 1-4 (separated by three bonds) interactions are fully included. The average percent errors (APEs) of molecular polarizability tensors for 4842 molecules or dimers are 2.98, 3.76, 3.28, and 3.82% for the pGM, Thole linear, Thole exponential, and Thole Amoeba models, respectively, with atom-type independent, universal screening factors (USF). The APEs are reduced further to 2.30, 2.69, 2.25, and 2.48% for the four corresponding polarizable models with atom-type dependent, variable screening factors (VSF). It is encouraging that the pGM with variable screening factors achieved APEs of 1.83 for 1155 amino acid analogs, dipeptides, and tetrapeptides, 1.39 for 28 nucleic acid bases, 0.708 for 1464 water clusters, and 1.99 for 85 dimers of water and biological building blocks. Compared to the new set of models, the APEs of the old Thole models that were fitted to isotropic molecular polarizabilities are 8.7% for set A (without the 1-2 and 1-3 interactions) and 6.3% for set D (with the 1-2 and 1-3 interactions) models, respectively. MPAD, a metric of molecular polarization anisotropy difference based on the diagonal terms of molecular polarizability tensors was defined and applied to assess the polarizable models in reproducing the ab initio molecular polarization anisotropy. The MPADs are 3.71, 4.70, 4.11, and 4.77% for the pGM, Thole linear, Thole exponential, and Thole Amoeba USF models, respectively. The APEs are reduced further to 2.85, 3.58, 2.90, and 3.15% for the four corresponding VSF models. Thus, the new pGM and Thole models notably improve molecular polarization anisotropy. Since pGM attenuates all short-range electrostatic interactions, its application is expected to improve stability in charge fitting, energy, and force calculations and the accuracy of multibody polarization.
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Affiliation(s)
- Junmei Wang
- Department of Pharmaceutical Sciences , University of Pittsburgh , 3501 Terrace Street , Pittsburgh , Pennsylvania 15261 , United States
| | - Piotr Cieplak
- SBP Medical Discovery Institute , 10901 North Torrey Pines Road , La Jolla , California 92037 , United States
| | - Ray Luo
- Departments of Molecular Biology and Biochemistry, Chemical and Biomolecular Engineering, Materials Science and Engineering, and Biomedical Engineering , University of California, Irvine , Irvine , California 92697 , United States
| | - Yong Duan
- UC Davis Genome Center and Department of Biomedical Engineering , University of California, Davis , One Shields Avenue , Davis , California 95616 , United States
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38
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Wildman A, Donati G, Lipparini F, Mennucci B, Li X. Nonequilibrium Environment Dynamics in a Frequency-Dependent Polarizable Embedding Model. J Chem Theory Comput 2018; 15:43-51. [PMID: 30512961 DOI: 10.1021/acs.jctc.8b00836] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Hybrid quantum mechanical/molecular mechanical (QM/MM) models are some of the most powerful and computationally feasible approaches to account for solvent effects or more general environmental perturbations on quantum chemical systems. In their more recent formulations (known as polarizable embedding) they can account for electrostatic and mutual polarization effects between the QM and the MM subsystems. In this paper, a polarizable embedding scheme based on induced dipoles that is able both to describe electron evolution of the embedded QM system in an efficient manner as well as to capture the frequency dependent behavior of the solvent is proposed, namely, ωMMPol. The effects of this frequency-dependent solvent on a time-dependent model system-the Rabi oscillations of H2+ in a resonant field-are considered. The solvent is shown to introduce only mild perturbations when the excitation frequencies of the solvent and the solute are off-resonant. However, the dynamics of the H2+ are fundamentally changed in the presence of a near-resonant excitation solvent. The effectiveness of ωMMPol to simulating realistic chemical systems is demonstrated by capturing charge transfer dynamics within a solvated system.
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Affiliation(s)
- Andrew Wildman
- Department of Chemistry , University of Washington , Seattle , Washington 98195 , United States
| | - Greta Donati
- Department of Chemistry , University of Washington , Seattle , Washington 98195 , United States
| | - Filippo Lipparini
- Dipartimento di Chimica e Chimica Industriale , Universitá di Pisa , Via Risorgimento 35 , 56126 Pisa , Italy
| | - Benedetta Mennucci
- Dipartimento di Chimica e Chimica Industriale , Universitá di Pisa , Via Risorgimento 35 , 56126 Pisa , Italy
| | - Xiaosong Li
- Department of Chemistry , University of Washington , Seattle , Washington 98195 , United States
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39
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Lao KU, Herbert JM. A Simple Correction for Nonadditive Dispersion within Extended Symmetry-Adapted Perturbation Theory (XSAPT). J Chem Theory Comput 2018; 14:5128-5142. [DOI: 10.1021/acs.jctc.8b00527] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Ka Un Lao
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - John M. Herbert
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
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40
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Christensen AS, Kromann JC, Jensen JH, Cui Q. Intermolecular interactions in the condensed phase: Evaluation of semi-empirical quantum mechanical methods. J Chem Phys 2018; 147:161704. [PMID: 29096452 DOI: 10.1063/1.4985605] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
To facilitate further development of approximate quantum mechanical methods for condensed phase applications, we present a new benchmark dataset of intermolecular interaction energies in the solution phase for a set of 15 dimers, each containing one charged monomer. The reference interaction energy in solution is computed via a thermodynamic cycle that integrates dimer binding energy in the gas phase at the coupled cluster level and solute-solvent interaction with density functional theory; the estimated uncertainty of such calculated interaction energy is ±1.5 kcal/mol. The dataset is used to benchmark the performance of a set of semi-empirical quantum mechanical (SQM) methods that include DFTB3-D3, DFTB3/CPE-D3, OM2-D3, PM6-D3, PM6-D3H+, and PM7 as well as the HF-3c method. We find that while all tested SQM methods tend to underestimate binding energies in the gas phase with a root-mean-squared error (RMSE) of 2-5 kcal/mol, they overestimate binding energies in the solution phase with an RMSE of 3-4 kcal/mol, with the exception of DFTB3/CPE-D3 and OM2-D3, for which the systematic deviation is less pronounced. In addition, we find that HF-3c systematically overestimates binding energies in both gas and solution phases. As most approximate QM methods are parametrized and evaluated using data measured or calculated in the gas phase, the dataset represents an important first step toward calibrating QM based methods for application in the condensed phase where polarization and exchange repulsion need to be treated in a balanced fashion.
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Affiliation(s)
- Anders S Christensen
- Department of Chemistry and Theoretical Chemistry Institute, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, USA
| | - Jimmy C Kromann
- Department of Chemistry, University of Copenhagen, Copenhagen, Denmark
| | - Jan H Jensen
- Department of Chemistry, University of Copenhagen, Copenhagen, Denmark
| | - Qiang Cui
- Department of Chemistry and Theoretical Chemistry Institute, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, USA
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41
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Xu M, Zhu T, Zhang JZH. A Force Balanced Fragmentation Method for ab Initio Molecular Dynamic Simulation of Protein. Front Chem 2018; 6:189. [PMID: 29900167 PMCID: PMC5989690 DOI: 10.3389/fchem.2018.00189] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Accepted: 05/09/2018] [Indexed: 12/28/2022] Open
Abstract
A force balanced generalized molecular fractionation with conjugate caps (FB-GMFCC) method is proposed for ab initio molecular dynamic simulation of proteins. In this approach, the energy of the protein is computed by a linear combination of the QM energies of individual residues and molecular fragments that account for the two-body interaction of hydrogen bond between backbone peptides. The atomic forces on the caped H atoms were corrected to conserve the total force of the protein. Using this approach, ab initio molecular dynamic simulation of an Ace-(ALA)9-NME linear peptide showed the conservation of the total energy of the system throughout the simulation. Further a more robust 110 ps ab initio molecular dynamic simulation was performed for a protein with 56 residues and 862 atoms in explicit water. Compared with the classical force field, the ab initio molecular dynamic simulations gave better description of the geometry of peptide bonds. Although further development is still needed, the current approach is highly efficient, trivially parallel, and can be applied to ab initio molecular dynamic simulation study of large proteins.
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Affiliation(s)
- Mingyuan Xu
- State Key Lab of Precision Spectroscopy, Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, Shanghai Key Laboratory of Green Chemistry & Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, China
| | - Tong Zhu
- State Key Lab of Precision Spectroscopy, Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, Shanghai Key Laboratory of Green Chemistry & Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, China.,NYU-ECNU Center for Computational Chemistry at New York University Shanghai, Shanghai, China
| | - John Z H Zhang
- State Key Lab of Precision Spectroscopy, Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, Shanghai Key Laboratory of Green Chemistry & Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, China.,NYU-ECNU Center for Computational Chemistry at New York University Shanghai, Shanghai, China.,Department of Chemistry, New York University, New York, NY, United States.,Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, China
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42
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Lao KU, Herbert JM. Atomic Orbital Implementation of Extended Symmetry-Adapted Perturbation Theory (XSAPT) and Benchmark Calculations for Large Supramolecular Complexes. J Chem Theory Comput 2018; 14:2955-2978. [DOI: 10.1021/acs.jctc.8b00058] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Ka Un Lao
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - John M. Herbert
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
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43
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A quantum mechanical computational method for modeling electrostatic and solvation effects of protein. Sci Rep 2018; 8:5475. [PMID: 29615707 PMCID: PMC5882933 DOI: 10.1038/s41598-018-23783-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2018] [Accepted: 03/19/2018] [Indexed: 12/28/2022] Open
Abstract
An efficient computational approach for modeling protein electrostatic is developed according to static point-charge model distributions based on the linear-scaling EE-GMFCC (electrostatically embedded generalized molecular fractionation with conjugate caps) quantum mechanical (QM) method. In this approach, the Electrostatic-Potential atomic charges are obtained from ab initio calculation of protein, both polarization and charge transfer effect are taken into consideration. This approach shows a significant improvement in the description of electrostatic potential and solvation energy of proteins comparing with current popular molecular mechanics (MM) force fields. Therefore, it has gorgeous prospect in many applications, including accurate calculations of electric field or vibrational Stark spectroscopy in proteins and predicting protein-ligand binding affinity. It can also be applied in QM/MM calculations or electronic embedding method of ONIOM to provide a better electrostatic environment.
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44
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Fedorov DG, Kitaura K. Pair Interaction Energy Decomposition Analysis for Density Functional Theory and Density-Functional Tight-Binding with an Evaluation of Energy Fluctuations in Molecular Dynamics. J Phys Chem A 2018; 122:1781-1795. [DOI: 10.1021/acs.jpca.7b12000] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Dmitri G. Fedorov
- Research
Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba 305-8568, Japan
| | - Kazuo Kitaura
- Advanced
Institute for Computational Science (AICS), RIKEN, 7-1-26 Minatojima-Minami-Machi,
Chuo-ku, Kobe, Hyogo 650-0047, Japan
- Fukui
Institute for Fundamental Chemistry, Kyoto University, Takano-Nishihiraki-cho
34-4, Sakyou-ku, Kyoto 606-8103, Japan
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45
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Cournia Z, Allen B, Sherman W. Relative Binding Free Energy Calculations in Drug Discovery: Recent Advances and Practical Considerations. J Chem Inf Model 2017; 57:2911-2937. [PMID: 29243483 DOI: 10.1021/acs.jcim.7b00564] [Citation(s) in RCA: 383] [Impact Index Per Article: 54.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Accurate in silico prediction of protein-ligand binding affinities has been a primary objective of structure-based drug design for decades due to the putative value it would bring to the drug discovery process. However, computational methods have historically failed to deliver value in real-world drug discovery applications due to a variety of scientific, technical, and practical challenges. Recently, a family of approaches commonly referred to as relative binding free energy (RBFE) calculations, which rely on physics-based molecular simulations and statistical mechanics, have shown promise in reliably generating accurate predictions in the context of drug discovery projects. This advance arises from accumulating developments in the underlying scientific methods (decades of research on force fields and sampling algorithms) coupled with vast increases in computational resources (graphics processing units and cloud infrastructures). Mounting evidence from retrospective validation studies, blind challenge predictions, and prospective applications suggests that RBFE simulations can now predict the affinity differences for congeneric ligands with sufficient accuracy and throughput to deliver considerable value in hit-to-lead and lead optimization efforts. Here, we present an overview of current RBFE implementations, highlighting recent advances and remaining challenges, along with examples that emphasize practical considerations for obtaining reliable RBFE results. We focus specifically on relative binding free energies because the calculations are less computationally intensive than absolute binding free energy (ABFE) calculations and map directly onto the hit-to-lead and lead optimization processes, where the prediction of relative binding energies between a reference molecule and new ideas (virtual molecules) can be used to prioritize molecules for synthesis. We describe the critical aspects of running RBFE calculations, from both theoretical and applied perspectives, using a combination of retrospective literature examples and prospective studies from drug discovery projects. This work is intended to provide a contemporary overview of the scientific, technical, and practical issues associated with running relative binding free energy simulations, with a focus on real-world drug discovery applications. We offer guidelines for improving the accuracy of RBFE simulations, especially for challenging cases, and emphasize unresolved issues that could be improved by further research in the field.
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Affiliation(s)
- Zoe Cournia
- Biomedical Research Foundation, Academy of Athens , 4 Soranou Ephessiou, 11527 Athens, Greece
| | - Bryce Allen
- Silicon Therapeutics , 300 A Street, Boston, Massachusetts 02210, United States
| | - Woody Sherman
- Silicon Therapeutics , 300 A Street, Boston, Massachusetts 02210, United States
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46
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Demerdash O, Wang L, Head‐Gordon T. Advanced models for water simulations. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2017. [DOI: 10.1002/wcms.1355] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Omar Demerdash
- Kenneth S. Pitzer Center for Theoretical Chemistry University of California Berkeley CA USA
- Department of Chemistry University of California Berkeley CA USA
| | - Lee‐Ping Wang
- Department of Chemistry University of California, Davis Davis CA USA
| | - Teresa Head‐Gordon
- Kenneth S. Pitzer Center for Theoretical Chemistry University of California Berkeley CA USA
- Department of Chemistry University of California Berkeley CA USA
- Department of Bioengineering University of California Berkeley CA USA
- Department of Chemical and Biomolecular Engineering University of California Berkeley CA USA
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Grimme S, Bannwarth C, Caldeweyher E, Pisarek J, Hansen A. A general intermolecular force field based on tight-binding quantum chemical calculations. J Chem Phys 2017; 147:161708. [DOI: 10.1063/1.4991798] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Stefan Grimme
- Mulliken Center for Theoretical Chemistry, Institut für Physikalische und Theoretische Chemie der Universität Bonn, Beringstr. 4, D-53115 Bonn,
Germany
| | - Christoph Bannwarth
- Mulliken Center for Theoretical Chemistry, Institut für Physikalische und Theoretische Chemie der Universität Bonn, Beringstr. 4, D-53115 Bonn,
Germany
| | - Eike Caldeweyher
- Mulliken Center for Theoretical Chemistry, Institut für Physikalische und Theoretische Chemie der Universität Bonn, Beringstr. 4, D-53115 Bonn,
Germany
| | - Jana Pisarek
- Mulliken Center for Theoretical Chemistry, Institut für Physikalische und Theoretische Chemie der Universität Bonn, Beringstr. 4, D-53115 Bonn,
Germany
| | - Andreas Hansen
- Mulliken Center for Theoretical Chemistry, Institut für Physikalische und Theoretische Chemie der Universität Bonn, Beringstr. 4, D-53115 Bonn,
Germany
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Giese TJ, York DM. Quantum mechanical force fields for condensed phase molecular simulations. JOURNAL OF PHYSICS. CONDENSED MATTER : AN INSTITUTE OF PHYSICS JOURNAL 2017; 29:383002. [PMID: 28817382 PMCID: PMC5821073 DOI: 10.1088/1361-648x/aa7c5c] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Molecular simulations are powerful tools for providing atomic-level details into complex chemical and physical processes that occur in the condensed phase. For strongly interacting systems where quantum many-body effects are known to play an important role, density-functional methods are often used to provide the model with the potential energy used to drive dynamics. These methods, however, suffer from two major drawbacks. First, they are often too computationally intensive to practically apply to large systems over long time scales, limiting their scope of application. Second, there remain challenges for these models to obtain the necessary level of accuracy for weak non-bonded interactions to obtain quantitative accuracy for a wide range of condensed phase properties. Quantum mechanical force fields (QMFFs) provide a potential solution to both of these limitations. In this review, we address recent advances in the development of QMFFs for condensed phase simulations. In particular, we examine the development of QMFF models using both approximate and ab initio density-functional models, the treatment of short-ranged non-bonded and long-ranged electrostatic interactions, and stability issues in molecular dynamics calculations. Example calculations are provided for crystalline systems, liquid water, and ionic liquids. We conclude with a perspective for emerging challenges and future research directions.
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Henriksen NM, Gilson MK. Evaluating Force Field Performance in Thermodynamic Calculations of Cyclodextrin Host-Guest Binding: Water Models, Partial Charges, and Host Force Field Parameters. J Chem Theory Comput 2017; 13:4253-4269. [PMID: 28696692 PMCID: PMC5606194 DOI: 10.1021/acs.jctc.7b00359] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
Abstract
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Computational
prediction of noncovalent binding free energies with
methods based on molecular mechanical force fields has become increasingly
routine in drug discovery projects, where they promise to speed the
discovery of small molecule ligands to bind targeted proteins with
high affinity. Because the reliability of free energy methods still
has significant room for improvement, new force fields, or modifications
of existing ones, are regularly introduced with the aim of improving
the accuracy of molecular simulations. However, comparatively little
work has been done to systematically assess how well force fields
perform, particularly in relation to the calculation of binding affinities.
Hardware advances have made these calculations feasible, but comprehensive
force field assessments for protein–ligand sized systems still
remain costly. Here, we turn to cyclodextrin host–guest systems,
which feature many hallmarks of protein–ligand binding interactions
but are generally much more tractable due to their small size. We
present absolute binding free energy and enthalpy calculations, using
the attach-pull-release (APR) approach, on a set of 43 cyclodextrin-guest
pairs for which experimental ITC data are available. The test set
comprises both α- and β-cyclodextrin hosts binding a series
of small organic guests, each with one of three functional groups:
ammonium, alcohol, or carboxylate. Four water models are considered
(TIP3P, TIP4Pew, SPC/E, and OPC), along with two partial charge assignment
procedures (RESP and AM1-BCC) and two cyclodextrin host force fields.
The results suggest a complex set of considerations when choosing
a force field for biomolecular simulations. For example, some force
field combinations clearly outperform others at the binding enthalpy
calculations but not for the binding free energy. Additionally, a
force field combination which we expected to be the worst performer
gave the most accurate binding free energies – but the least
accurate binding enthalpies. The results have implications for the
development of improved force fields, and we propose this test set,
and potential future elaborations of it, as a powerful validation
suite to evaluate new force fields and help guide future force field
development.
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Affiliation(s)
- Niel M Henriksen
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego , La Jolla, California 92093-0736, United States
| | - Michael K Gilson
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego , La Jolla, California 92093-0736, United States
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Cui Q. Perspective: Quantum mechanical methods in biochemistry and biophysics. J Chem Phys 2017; 145:140901. [PMID: 27782516 DOI: 10.1063/1.4964410] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
In this perspective article, I discuss several research topics relevant to quantum mechanical (QM) methods in biophysical and biochemical applications. Due to the immense complexity of biological problems, the key is to develop methods that are able to strike the proper balance of computational efficiency and accuracy for the problem of interest. Therefore, in addition to the development of novel ab initio and density functional theory based QM methods for the study of reactive events that involve complex motifs such as transition metal clusters in metalloenzymes, it is equally important to develop inexpensive QM methods and advanced classical or quantal force fields to describe different physicochemical properties of biomolecules and their behaviors in complex environments. Maintaining a solid connection of these more approximate methods with rigorous QM methods is essential to their transferability and robustness. Comparison to diverse experimental observables helps validate computational models and mechanistic hypotheses as well as driving further development of computational methodologies.
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Affiliation(s)
- Qiang Cui
- Department of Chemistry and Theoretical Chemistry Institute, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, USA
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