1
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Chung MKJ, Ponder JW. Beyond isotropic repulsion: Classical anisotropic repulsion by inclusion of p orbitals. J Chem Phys 2024; 160:174118. [PMID: 38748037 PMCID: PMC11078554 DOI: 10.1063/5.0203678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 04/15/2024] [Indexed: 05/19/2024] Open
Abstract
Accurate modeling of intermolecular repulsion is an integral component in force field development. Although repulsion can be explicitly calculated by applying the Pauli exclusion principle, this approach is computationally viable only for systems of limited sizes. Instead, it has previously been shown that repulsion can be reformulated in a "classical" picture: the Pauli exclusion principle prohibits electrons from occupying the same state, leading to a depletion of electronic charge between atoms, giving rise to an enhanced nuclear-nuclear electrostatic repulsion. This classical picture is called the isotropic S2/R approximation, where S is the overlap and R is the interatomic distance. This approximation accurately captures the repulsion of isotropic atoms such as noble gas dimers; however, a key deficiency is that it fails to capture the angular dependence of the repulsion of anisotropic molecules. To include directionality, the wave function must at least be a linear combination of s and p orbitals. We derive a new anisotropic S2/R repulsion model through the inclusion of the anisotropic p orbital term in the total wave function. Because repulsion is pairwise and decays rapidly, it can be truncated at a short range, making it amenable for efficient calculation of energy and forces in complex biomolecular systems. We present a parameterization of the S101 dimer database against the ab initio benchmark symmetry-adapted perturbation theory, which yields an rms error of only 0.9 kcal/mol. The importance of the anisotropic term is demonstrated through angular scans of water-water dimers and dimers involving halobenzene. Simulation of liquid water shows that the model can be computed efficiently for realistic system sizes.
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Affiliation(s)
| | - Jay W. Ponder
- Author to whom correspondence should be addressed: . Tel.: 314-935-4275
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2
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Fan ZX, Chao SD. A Machine Learning Force Field for Bio-Macromolecular Modeling Based on Quantum Chemistry-Calculated Interaction Energy Datasets. Bioengineering (Basel) 2024; 11:51. [PMID: 38247928 PMCID: PMC11154266 DOI: 10.3390/bioengineering11010051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 12/23/2023] [Accepted: 12/25/2023] [Indexed: 01/23/2024] Open
Abstract
Accurate energy data from noncovalent interactions are essential for constructing force fields for molecular dynamics simulations of bio-macromolecular systems. There are two important practical issues in the construction of a reliable force field with the hope of balancing the desired chemical accuracy and working efficiency. One is to determine a suitable quantum chemistry level of theory for calculating interaction energies. The other is to use a suitable continuous energy function to model the quantum chemical energy data. For the first issue, we have recently calculated the intermolecular interaction energies using the SAPT0 level of theory, and we have systematically organized these energies into the ab initio SOFG-31 (homodimer) and SOFG-31-heterodimer datasets. In this work, we re-calculate these interaction energies by using the more advanced SAPT2 level of theory with a wider series of basis sets. Our purpose is to determine the SAPT level of theory proper for interaction energies with respect to the CCSD(T)/CBS benchmark chemical accuracy. Next, to utilize these energy datasets, we employ one of the well-developed machine learning techniques, called the CLIFF scheme, to construct a general-purpose force field for biomolecular dynamics simulations. Here we use the SOFG-31 dataset and the SOFG-31-heterodimer dataset as the training and test sets, respectively. Our results demonstrate that using the CLIFF scheme can reproduce a diverse range of dimeric interaction energy patterns with only a small training set. The overall errors for each SAPT energy component, as well as the SAPT total energy, are all well below the desired chemical accuracy of ~1 kcal/mol.
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Affiliation(s)
- Zhen-Xuan Fan
- Institute of Applied Mechanics, National Taiwan University, Taipei 106, Taiwan;
| | - Sheng D. Chao
- Institute of Applied Mechanics, National Taiwan University, Taipei 106, Taiwan;
- Center for Quantum Science and Engineering, National Taiwan University, Taipei 106, Taiwan
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3
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Chen JA, Chao SD. Intermolecular Non-Bonded Interactions from Machine Learning Datasets. Molecules 2023; 28:7900. [PMID: 38067629 PMCID: PMC10707888 DOI: 10.3390/molecules28237900] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 11/22/2023] [Accepted: 11/29/2023] [Indexed: 04/04/2024] Open
Abstract
Accurate determination of intermolecular non-covalent-bonded or non-bonded interactions is the key to potentially useful molecular dynamics simulations of polymer systems. However, it is challenging to balance both the accuracy and computational cost in force field modelling. One of the main difficulties is properly representing the calculated energy data as a continuous force function. In this paper, we employ well-developed machine learning techniques to construct a general purpose intermolecular non-bonded interaction force field for organic polymers. The original ab initio dataset SOFG-31 was calculated by us and has been well documented, and here we use it as our training set. The CLIFF kernel type machine learning scheme is used for predicting the interaction energies of heterodimers selected from the SOFG-31 dataset. Our test results show that the overall errors are well below the chemical accuracy of about 1 kcal/mol, thus demonstrating the promising feasibility of machine learning techniques in force field modelling.
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Affiliation(s)
- Jia-An Chen
- Institute of Applied Mechanics, National Taiwan University, Taipei 106, Taiwan;
| | - Sheng D. Chao
- Institute of Applied Mechanics, National Taiwan University, Taipei 106, Taiwan;
- Center for Quantum Science and Engineering, National Taiwan University, Taipei 106, Taiwan
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4
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Ji ML, Li Z, Hu XY, Zhang WT, Zhang HX, Lu J. Dynamic chromatin accessibility tuning by the long noncoding RNA ELDR accelerates chondrocyte senescence and osteoarthritis. Am J Hum Genet 2023; 110:606-624. [PMID: 36868238 PMCID: PMC10119164 DOI: 10.1016/j.ajhg.2023.02.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 02/10/2023] [Indexed: 03/05/2023] Open
Abstract
Epigenetic reprogramming plays a critical role in chondrocyte senescence during osteoarthritis (OA) pathology, but the underlying molecular mechanisms remain to be elucidated. Here, using large-scale individual datasets and genetically engineered (Col2a1-CreERT2;Eldrflox/flox and Col2a1-CreERT2;ROSA26-LSL-Eldr+/+ knockin) mouse models, we show that a novel transcript of long noncoding RNA ELDR is essential for the development of chondrocyte senescence. ELDR is highly expressed in chondrocytes and cartilage tissues of OA. Mechanistically, exon 4 of ELDR physically mediates a complex consisting of hnRNPL and KAT6A to regulate histone modifications of the promoter region of IHH, thereby activating hedgehog signaling and promoting chondrocyte senescence. Therapeutically, GapmeR-mediated silencing of ELDR in the OA model substantially attenuates chondrocyte senescence and cartilage degradation. Clinically, ELDR knockdown in cartilage explants from OA-affected individuals decreased the expression of senescence markers and catabolic mediators. Taken together, these findings uncover an lncRNA-dependent epigenetic driver in chondrocyte senescence, highlighting that ELDR could be a promising therapeutic avenue for OA.
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Affiliation(s)
- Ming-Liang Ji
- The Center of Joint and Sports Medicine, Orthopedics Department, Zhongda Hospital, Southeast University, Nanjing, China.
| | - Zhuang Li
- The Center of Joint and Sports Medicine, Orthopedics Department, Zhongda Hospital, Southeast University, Nanjing, China
| | - Xin Yue Hu
- The Center of Joint and Sports Medicine, Orthopedics Department, Zhongda Hospital, Southeast University, Nanjing, China
| | - Wei Tuo Zhang
- The Center of Joint and Sports Medicine, Orthopedics Department, Zhongda Hospital, Southeast University, Nanjing, China
| | - Hai Xiang Zhang
- The Center of Joint and Sports Medicine, Orthopedics Department, Zhongda Hospital, Southeast University, Nanjing, China
| | - Jun Lu
- The Center of Joint and Sports Medicine, Orthopedics Department, Zhongda Hospital, Southeast University, Nanjing, China.
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5
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Chung MKJ, Wang Z, Rackers JA, Ponder JW. Classical Exchange Polarization: An Anisotropic Variable Polarizability Model. J Phys Chem B 2022; 126:7579-7594. [PMID: 36166814 PMCID: PMC10868659 DOI: 10.1021/acs.jpcb.2c04237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Polarizability, or the tendency of the electron distribution to distort under an electric field, often depends on the local chemical environment. For example, the polarizability of a chloride ion is larger in gas phase compared to a chloride ion solvated in water. This effect is due to the restriction the Pauli exclusion principle places on the allowed electron states. Because no two electrons can occupy the same state, when a highly polarizable atom comes in close contact with other atoms or molecules, the space of allowed states can dramatically decrease. This constraint suggests that an accurate molecular mechanics polarizability model should depend on the radial distance between neighboring atoms. This paper introduces a variable polarizability model within the framework of the HIPPO (Hydrogen-like Intermolecular Polarizable Potential) force field, by damping the polarizability as a function of the orbital overlap of two atoms. This effectively captures the quantum mechanical exchange polarization effects, without explicit utilization of antisymmetrized wave functions. We show that the variable polarizability model remarkably improves the two-body polarization energies and three-body energies of ion-ion and ion-water systems. Under this model, no manual tuning of atomic polarizabilities for monatomic ions is required; the gas-phase polarizability can be used because an appropriate damping function is able to correct the polarizability at short range.
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Affiliation(s)
- Moses K. J. Chung
- Medical Scientist Training Program, Washington University School of Medicine, Saint Louis, MO 63110, USA
- Department of Physics, Washington University in St. Louis, Saint Louis, MO 63130, USA
| | - Zhi Wang
- Department of Chemistry, Washington University in St. Louis, Saint Louis, MO 63130, USA
| | - Joshua A. Rackers
- Center for Computing Research, Sandia National Laboratories, Albuquerque, NM 87185, USA
| | - Jay W. Ponder
- Department of Chemistry, Washington University in St. Louis, Saint Louis, MO 63130, USA
- Department of Biochemistry & Molecular Biophysics, Washington University School of Medicine, Saint Louis, MO 63110, USA
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6
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Oliveira MP, Gonçalves YMH, Ol Gheta SK, Rieder SR, Horta BAC, Hünenberger PH. Comparison of the United- and All-Atom Representations of (Halo)alkanes Based on Two Condensed-Phase Force Fields Optimized against the Same Experimental Data Set. J Chem Theory Comput 2022; 18:6757-6778. [PMID: 36190354 DOI: 10.1021/acs.jctc.2c00524] [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 level of accuracy that can be achieved by a force field is influenced by choices made in the interaction-function representation and in the relevant simulation parameters. These choices, referred to here as functional-form variants (FFVs), include for example the model resolution, the charge-derivation procedure, the van der Waals combination rules, the cutoff distance, and the treatment of the long-range interactions. Ideally, assessing the effect of a given FFV on the intrinsic accuracy of the force-field representation requires that only the specific FFV is changed and that this change is performed at an optimal level of parametrization, a requirement that may prove extremely challenging to achieve in practice. Here, we present a first attempt at such a comparison for one specific FFV, namely the choice of a united-atom (UA) versus an all-atom (AA) resolution in a force field for saturated acyclic (halo)alkanes. Two force-field versions (UA vs AA) are optimized in an automated way using the CombiFF approach against 961 experimental values for the pure-liquid densities ρliq and vaporization enthalpies ΔHvap of 591 compounds. For the AA force field, the torsional and third-neighbor Lennard-Jones parameters are also refined based on quantum-mechanical rotational-energy profiles. The comparison between the UA and AA resolutions is also extended to properties that have not been included as parameterization targets, namely the surface-tension coefficient γ, the isothermal compressibility κT, the isobaric thermal-expansion coefficient αP, the isobaric heat capacity cP, the static relative dielectric permittivity ϵ, the self-diffusion coefficient D, the shear viscosity η, the hydration free energy ΔGwat, and the free energy of solvation ΔGche in cyclohexane. For the target properties ρliq and ΔHvap, the UA and AA resolutions reach very similar levels of accuracy after optimization. For the nine other properties, the AA representation leads to more accurate results in terms of η; comparably accurate results in terms of γ, κT, αP, ϵ, D, and ΔGche; and less accurate results in terms of cP and ΔGwat. This work also represents a first step toward the calibration of a GROMOS-compatible force field at the AA resolution.
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Affiliation(s)
- Marina P Oliveira
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Yan M H Gonçalves
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCI, CH-8093 Zürich, Switzerland
| | - S Kashef Ol Gheta
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Salomé R Rieder
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Bruno A C Horta
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Philippe H Hünenberger
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCI, CH-8093 Zürich, Switzerland
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7
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Huang HH, Wang YS, Chao SD. A Minimum Quantum Chemistry CCSD(T)/CBS Data Set of Dimeric Interaction Energies for Small Organic Functional Groups: Heterodimers. ACS OMEGA 2022; 7:20059-20080. [PMID: 35722020 PMCID: PMC9201891 DOI: 10.1021/acsomega.2c01888] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 05/04/2022] [Indexed: 06/15/2023]
Abstract
We extend our previous quantum chemistry calculations of interaction energies for 31 homodimers of small organic functional groups (the SOFG-31 data set) by including 239 heterodimers with monomers selected within the SOFG-31 data set, thus resulting in the SOFG-31+239 data set. The minimum-level theoretical scheme contains (1) the basis set superposition error corrected supermolecule (BSSE-SM) approach for intermolecular interactions; (2) the second-order Møller-Plesset perturbation theory (MP2) with the Dunning's aug-cc-pVXZ (X = D, T, Q) basis sets for the geometry optimization and correlation energy calculations; and (3) the single-point energy calculations with the coupled cluster with single, double, and perturbative triple excitations method at the complete basis set limit [CCSD(T)/CBS] using the well-tested extrapolation methods for the MP2 energy calibrations. In addition, we have performed a parallel series of energy decomposition calculations based on the symmetry adapted perturbation theory (SAPT) in order to gain chemical insights. That the above procedure cannot be further reduced has been proven to be very crucial for constructing reliable data sets of interaction energies. The calculated CCSD(T)/CBS interaction energy data can serve as a benchmark for testing or training less accurate but more efficient calculation methods, such as the electronic density functional theory. As an application, we employ a segmental SAPT model previously developed for the SOFG-31 data set to predict binding energies of large heterodimer complexes. These model energy "quanta" can be used in coarse-grained molecular dynamics simulations by avoiding large-scale calculations.
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Affiliation(s)
- Hsing-Hsiang Huang
- Institute
of Applied Mechanics, National Taiwan University, Taipei 10617, Taiwan R.O.C.
| | - Yi-Siang Wang
- School
of Chemistry & Biochemistry, Georgia
Institute of Technology, Atlanta, Georgia 30332, United States
| | - Sheng D. Chao
- Institute
of Applied Mechanics, National Taiwan University, Taipei 10617, Taiwan R.O.C.
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8
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Rackers JA, Silva RR, Wang Z, Ponder JW. Polarizable Water Potential Derived from a Model Electron Density. J Chem Theory Comput 2021; 17:7056-7084. [PMID: 34699197 DOI: 10.1021/acs.jctc.1c00628] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
A new empirical potential for efficient, large scale molecular dynamics simulation of water is presented. The HIPPO (Hydrogen-like Intermolecular Polarizable POtential) force field is based upon the model electron density of a hydrogen-like atom. This framework is used to derive and parametrize individual terms describing charge penetration damped permanent electrostatics, damped polarization, charge transfer, anisotropic Pauli repulsion, and damped dispersion interactions. Initial parameter values were fit to Symmetry Adapted Perturbation Theory (SAPT) energy components for ten water dimer configurations, as well as the radial and angular dependence of the canonical dimer. The SAPT-based parameters were then systematically refined to extend the treatment to water bulk phases. The final HIPPO water model provides a balanced representation of a wide variety of properties of gas phase clusters, liquid water, and ice polymorphs, across a range of temperatures and pressures. This water potential yields a rationalization of water structure, dynamics, and thermodynamics explicitly correlated with an ab initio energy decomposition, while providing a level of accuracy comparable or superior to previous polarizable atomic multipole force fields. The HIPPO water model serves as a cornerstone around which similarly detailed physics-based models can be developed for additional molecular species.
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Affiliation(s)
- Joshua A Rackers
- Program in Computational & Molecular Biophysics, Washington University School of Medicine, Saint Louis, Missouri 63110, United States.,Center for Computing Research, Sandia National Laboratories, Albuquerque, New Mexico 87123, United States
| | - Roseane R Silva
- Program in Computational & Molecular Biophysics, Washington University School of Medicine, Saint Louis, Missouri 63110, United States
| | - Zhi Wang
- Department of Chemistry, Washington University in Saint Louis, Saint Louis, Missouri 63130, United States
| | - Jay W Ponder
- Department of Chemistry, Washington University in Saint Louis, Saint Louis, Missouri 63130, United States.,Department of Biochemistry & Molecular Biophysics, Washington University School of Medicine, Saint Louis, Missouri 63110, United States
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9
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Chang YM, Wang YS, Chao SD. A minimum quantum chemistry CCSD(T)/CBS dataset of dimeric interaction energies for small organic functional groups. J Chem Phys 2020; 153:154301. [PMID: 33092384 DOI: 10.1063/5.0019392] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
We have performed a quantum chemistry study on the bonding patterns and interaction energies for 31 dimers of small organic functional groups (dubbed the SOFG-31 dataset), including the alkane-alkene-alkyne (6 + 4 + 4 = 14, AAA) groups, alcohol-aldehyde-ketone (4 + 4 + 3 = 11, AAK) groups, and carboxylic acid-amide (3 + 3 = 6, CAA) groups. The basis set superposition error corrected super-molecule approach using the second order Møller-Plesset perturbation theory (MP2) with the Dunning's aug-cc-pVXZ (X = D, T, Q) basis sets has been employed in the geometry optimization and energy calculations. To calibrate the MP2 calculated interaction energies for these dimeric complexes, we perform single-point calculations with the coupled cluster with single, double, and perturbative triple excitations method at the complete basis set limit [CCSD(T)/CBS] using the well-tested extrapolation methods. In order to gain more physical insights, we also perform a parallel series of energy decomposition calculations based on the symmetry adapted perturbation theory (SAPT). The collection of these CCSD(T)/CBS interaction energy values can serve as a minimum quantum chemistry dataset for testing or training less accurate but more efficient calculation methods. As an application, we further propose a segmental SAPT model based on chemically recognizable segments in a specific functional group. These model interactions can be used to construct coarse-grained force fields for larger molecular systems.
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Affiliation(s)
- Yu-Ming Chang
- Institute of Applied Mechanics, National Taiwan University, Taipei 10617, Taiwan
| | - Yi-Siang Wang
- Institute of Applied Mechanics, National Taiwan University, Taipei 10617, Taiwan
| | - Sheng D Chao
- Institute of Applied Mechanics, National Taiwan University, Taipei 10617, Taiwan
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10
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Glick ZL, Metcalf DP, Koutsoukas A, Spronk SA, Cheney DL, Sherrill CD. AP-Net: An atomic-pairwise neural network for smooth and transferable interaction potentials. J Chem Phys 2020; 153:044112. [DOI: 10.1063/5.0011521] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Affiliation(s)
- Zachary L. Glick
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, and School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, USA
| | - Derek P. Metcalf
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, and School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, USA
| | - Alexios Koutsoukas
- Molecular Structure and Design, Bristol Myers Squibb Company, P.O. Box 5400, Princeton, New Jersey 08543, USA
| | - Steven A. Spronk
- Molecular Structure and Design, Bristol Myers Squibb Company, P.O. Box 5400, Princeton, New Jersey 08543, USA
| | - Daniel L. Cheney
- Molecular Structure and Design, Bristol Myers Squibb Company, P.O. Box 5400, Princeton, New Jersey 08543, USA
| | - C. David Sherrill
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, and School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, USA
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11
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Garcia J, Podeszwa R, Szalewicz K. SAPT codes for calculations of intermolecular interaction energies. J Chem Phys 2020; 152:184109. [PMID: 32414261 DOI: 10.1063/5.0005093] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Symmetry-adapted perturbation theory (SAPT) is a method for calculations of intermolecular (noncovalent) interaction energies. The set of SAPT codes that is described here, the current version named SAPT2020, includes virtually all variants of SAPT developed so far, among them two-body SAPT based on perturbative, coupled cluster, and density functional theory descriptions of monomers, three-body SAPT, and two-body SAPT for some classes of open-shell monomers. The properties of systems governed by noncovalent interactions can be predicted only if potential energy surfaces (force fields) are available. SAPT is the preferred approach for generating such surfaces since it is seamlessly connected to the asymptotic expansion of interaction energy. SAPT2020 includes codes for automatic development of such surfaces, enabling generation of complete dimer surfaces with a rigid monomer approximation for dimers containing about one hundred atoms. These codes can also be used to obtain surfaces including internal degrees of freedom of monomers.
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Affiliation(s)
- Javier Garcia
- Department of Physics and Astronomy, University of Delaware, Newark, Delaware 19716, USA
| | - Rafał Podeszwa
- Institute of Chemistry, University of Silesia at Katowice, Szkolna 9, Katowice, Poland
| | - Krzysztof Szalewicz
- Department of Physics and Astronomy, University of Delaware, Newark, Delaware 19716, USA
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12
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Smith DGA, Burns LA, Simmonett AC, Parrish RM, Schieber MC, Galvelis R, Kraus P, Kruse H, Di Remigio R, Alenaizan A, James AM, Lehtola S, Misiewicz JP, Scheurer M, Shaw RA, Schriber JB, Xie Y, Glick ZL, Sirianni DA, O’Brien JS, Waldrop JM, Kumar A, Hohenstein EG, Pritchard BP, Brooks BR, Schaefer HF, Sokolov AY, Patkowski K, DePrince AE, Bozkaya U, King RA, Evangelista FA, Turney JM, Crawford TD, Sherrill CD. Psi4 1.4: Open-source software for high-throughput quantum chemistry. J Chem Phys 2020; 152:184108. [PMID: 32414239 PMCID: PMC7228781 DOI: 10.1063/5.0006002] [Citation(s) in RCA: 330] [Impact Index Per Article: 82.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 04/12/2020] [Indexed: 12/13/2022] Open
Abstract
PSI4 is a free and open-source ab initio electronic structure program providing implementations of Hartree-Fock, density functional theory, many-body perturbation theory, configuration interaction, density cumulant theory, symmetry-adapted perturbation theory, and coupled-cluster theory. Most of the methods are quite efficient, thanks to density fitting and multi-core parallelism. The program is a hybrid of C++ and Python, and calculations may be run with very simple text files or using the Python API, facilitating post-processing and complex workflows; method developers also have access to most of PSI4's core functionalities via Python. Job specification may be passed using The Molecular Sciences Software Institute (MolSSI) QCSCHEMA data format, facilitating interoperability. A rewrite of our top-level computation driver, and concomitant adoption of the MolSSI QCARCHIVE INFRASTRUCTURE project, makes the latest version of PSI4 well suited to distributed computation of large numbers of independent tasks. The project has fostered the development of independent software components that may be reused in other quantum chemistry programs.
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Affiliation(s)
| | - Lori A. Burns
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | - Andrew C. Simmonett
- National Institutes of Health – National Heart,
Lung and Blood Institute, Laboratory of Computational Biology, Bethesda,
Maryland 20892, USA
| | - Robert M. Parrish
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | - Matthew C. Schieber
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | | | - Peter Kraus
- School of Molecular and Life Sciences, Curtin
University, Kent St., Bentley, Perth, Western Australia 6102,
Australia
| | - Holger Kruse
- Institute of Biophysics of the Czech Academy of
Sciences, Královopolská 135, 612 65 Brno, Czech
Republic
| | - Roberto Di Remigio
- Department of Chemistry, Centre for Theoretical
and Computational Chemistry, UiT, The Arctic University of Norway, N-9037
Tromsø, Norway
| | - Asem Alenaizan
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | - Andrew M. James
- Department of Chemistry, Virginia
Tech, Blacksburg, Virginia 24061, USA
| | - Susi Lehtola
- Department of Chemistry, University of
Helsinki, P.O. Box 55 (A. I. Virtasen aukio 1), FI-00014 Helsinki,
Finland
| | - Jonathon P. Misiewicz
- Center for Computational Quantum Chemistry,
University of Georgia, Athens, Georgia 30602, USA
| | - Maximilian Scheurer
- Interdisciplinary Center for Scientific
Computing, Heidelberg University, D-69120 Heidelberg,
Germany
| | - Robert A. Shaw
- ARC Centre of Excellence in Exciton Science,
School of Science, RMIT University, Melbourne, VIC 3000,
Australia
| | - Jeffrey B. Schriber
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | - Yi Xie
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | - Zachary L. Glick
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | - Dominic A. Sirianni
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | - Joseph Senan O’Brien
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | - Jonathan M. Waldrop
- Department of Chemistry and Biochemistry, Auburn
University, Auburn, Alabama 36849, USA
| | - Ashutosh Kumar
- Department of Chemistry, Virginia
Tech, Blacksburg, Virginia 24061, USA
| | - Edward G. Hohenstein
- SLAC National Accelerator Laboratory, Stanford
PULSE Institute, Menlo Park, California 94025,
USA
| | | | - Bernard R. Brooks
- National Institutes of Health – National Heart,
Lung and Blood Institute, Laboratory of Computational Biology, Bethesda,
Maryland 20892, USA
| | - Henry F. Schaefer
- Center for Computational Quantum Chemistry,
University of Georgia, Athens, Georgia 30602, USA
| | - Alexander Yu. Sokolov
- Department of Chemistry and Biochemistry, The
Ohio State University, Columbus, Ohio 43210, USA
| | - Konrad Patkowski
- Department of Chemistry and Biochemistry, Auburn
University, Auburn, Alabama 36849, USA
| | - A. Eugene DePrince
- Department of Chemistry and Biochemistry,
Florida State University, Tallahassee, Florida 32306-4390,
USA
| | - Uğur Bozkaya
- Department of Chemistry, Hacettepe
University, Ankara 06800, Turkey
| | - Rollin A. King
- Department of Chemistry, Bethel
University, St. Paul, Minnesota 55112, USA
| | | | - Justin M. Turney
- Center for Computational Quantum Chemistry,
University of Georgia, Athens, Georgia 30602, USA
| | | | - C. David Sherrill
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
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13
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Patkowski K. Recent developments in symmetry‐adapted perturbation theory. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2019. [DOI: 10.1002/wcms.1452] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Affiliation(s)
- Konrad Patkowski
- Department of Chemistry and Biochemistry Auburn University Auburn Alabama
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14
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Das AK, Urban L, Leven I, Loipersberger M, Aldossary A, Head-Gordon M, Head-Gordon T. Development of an Advanced Force Field for Water Using Variational Energy Decomposition Analysis. J Chem Theory Comput 2019; 15:5001-5013. [DOI: 10.1021/acs.jctc.9b00478] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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15
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Andrés J, Ayers PW, Boto RA, Carbó-Dorca R, Chermette H, Cioslowski J, Contreras-García J, Cooper DL, Frenking G, Gatti C, Heidar-Zadeh F, Joubert L, Martín Pendás Á, Matito E, Mayer I, Misquitta AJ, Mo Y, Pilmé J, Popelier PLA, Rahm M, Ramos-Cordoba E, Salvador P, Schwarz WHE, Shahbazian S, Silvi B, Solà M, Szalewicz K, Tognetti V, Weinhold F, Zins ÉL. Nine questions on energy decomposition analysis. J Comput Chem 2019; 40:2248-2283. [PMID: 31251411 DOI: 10.1002/jcc.26003] [Citation(s) in RCA: 88] [Impact Index Per Article: 17.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Accepted: 05/16/2019] [Indexed: 01/05/2023]
Abstract
The paper collects the answers of the authors to the following questions: Is the lack of precision in the definition of many chemical concepts one of the reasons for the coexistence of many partition schemes? Does the adoption of a given partition scheme imply a set of more precise definitions of the underlying chemical concepts? How can one use the results of a partition scheme to improve the clarity of definitions of concepts? Are partition schemes subject to scientific Darwinism? If so, what is the influence of a community's sociological pressure in the "natural selection" process? To what extent does/can/should investigated systems influence the choice of a particular partition scheme? Do we need more focused chemical validation of Energy Decomposition Analysis (EDA) methodology and descriptors/terms in general? Is there any interest in developing common benchmarks and test sets for cross-validation of methods? Is it possible to contemplate a unified partition scheme (let us call it the "standard model" of partitioning), that is proper for all applications in chemistry, in the foreseeable future or even in principle? In the end, science is about experiments and the real world. Can one, therefore, use any experiment or experimental data be used to favor one partition scheme over another? © 2019 Wiley Periodicals, Inc.
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Affiliation(s)
- Juan Andrés
- Departament de Ciències Experimentals Universitat Jaume I, 12080, Castelló, Spain
| | - Paul W Ayers
- Department of Chemistry and Chemical Biology, McMaster University, 1280 Main Street West, L8S 4M1, Hamilton, Ontario, Canada
| | | | - Ramon Carbó-Dorca
- Institut de Química Computational i Catàlisi, Universitat de Girona, C/M Aurelia Capmany 69, 17003, Girona, Spain
| | - Henry Chermette
- Université Lyon 1 et UMR CNRS 5280 Institut Sciences Analytiques, Université de Lyon, 69622, Paris, France
| | - Jerzy Cioslowski
- Institute of Physics, University of Szczecin, Wielkopolska, 15, 70-451, Szczecin, Poland
| | | | - David L Cooper
- Department of Chemistry, University of Liverpool, Liverpool, L69 7ZD, United Kingdom
| | - Gernot Frenking
- Fachbereich Chemie, Philipps-Universität Marburg, Hans-Meerweinstr. 4, 35032, Marburg, Germany
| | - Carlo Gatti
- CNR-ISTM Istituto di Scienze e Tecnologie Molecolari, via Golgi 19, 20133, Milan, Italy and Istituto Lombardo Accademia di Scienze e Lettere, via Brera 28, 20121, Milan, Italy
| | - Farnaz Heidar-Zadeh
- Physics and Materials Science Research Unit, University of Luxembourg, L-1511 Luxembourg, Luxembourg and Department of Chemistry, Queen's University, Kingston, Ontario K7L 3N6, Canada
| | - Laurent Joubert
- COBRA UMR 6014 & FR 3038, INSA Rouen, CNRS, Université de Rouen Normandie, Mont-St-Aignan, France
| | - Ángel Martín Pendás
- Departamento de Química Física y Analítica, Universidad de Oviedo, 33006, Oviedo, Spain
| | - Eduard Matito
- Kimika Fakultatea, Euskal Herriko Unibertsitatea (UPV/EHU), and Donostia International Physics Center (DIPC), P.K. 1072, 20080, Donostia, Euskadi, Spain.,IKERBASQUE, Basque Foundation for Science, 48011, Bilbao, Euskadi, Spain
| | - István Mayer
- Institute of Organic Chemistry, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, 1117, Hungary
| | - Alston J Misquitta
- School of Physics and Astronomy, Queen Mary University of London, Mile End Road, London, E1 4NS, United Kingdom
| | - Yirong Mo
- Chemistry Department, Western Michigan University, Kalamazoo, Michigan, 49008
| | - Julien Pilmé
- Sorbonne Université, CNRS, LCT, UMR 7616, 4 place Jussieu, 75005, Paris, France
| | - Paul L A Popelier
- Manchester Institute of Biotechnology (MIB), 131 Princess Street, Manchester, M1 7DN, United Kingdom.,School of Chemistry, University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
| | - Martin Rahm
- Department of Chemistry and Chemical Engineering, Chalmers University of Technology, 412 96, Gothenburg, Sweden
| | - Eloy Ramos-Cordoba
- Kimika Fakultatea, Euskal Herriko Unibertsitatea (UPV/EHU), and Donostia International Physics Center (DIPC), P.K. 1072, 20080, Donostia, Euskadi, Spain
| | - Pedro Salvador
- Institut de Química Computacional i Catàlisi, Universitat de Girona, C/M Aurelia Capmany 69, 17003, Girona, Spain
| | - W H Eugen Schwarz
- Theoretical Chemistry Center at Tsinghua University, Beijing, 100084, China.,Physical and Theoretical Chemistry Laboratory, Faculty of Science and Engineering, University of Siegen, Siegen, 57068, Germany
| | - Shant Shahbazian
- Department of Physics, Shahid Beheshti University, P.O. Box 19395-4716, G. C., Evin, 19839, Tehran, Iran
| | - Bernard Silvi
- Sorbonne Université, CNRS, LCT, UMR 7616, 4 place Jussieu, 75005, Paris, France
| | - Miquel Solà
- Institut de Química Computacional i Catàlisi, Universitat de Girona, C/M Aurelia Capmany 69, 17003, Girona, Spain
| | - Krzysztof Szalewicz
- Department of Physics and Astronomy, University of Delaware, Newark, Delaware
| | - Vincent Tognetti
- COBRA UMR 6014 & FR 3038, INSA Rouen, CNRS, Université de Rouen Normandie, Mont-St-Aignan, France
| | - Frank Weinhold
- Theoretical Chemistry Institute and Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin, 53706
| | - Émilie-Laure Zins
- Sorbonne Université, UPMC Univ. Paris 06, MONARIS, UMR 8233, Université Pierre et Marie Curie, 4 Place Jussieu, Case Courrier 49, 75252, Paris, France
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16
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Liu C, Piquemal JP, Ren P. AMOEBA+ Classical Potential for Modeling Molecular Interactions. J Chem Theory Comput 2019; 15:4122-4139. [PMID: 31136175 DOI: 10.1021/acs.jctc.9b00261] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Classical potentials based on isotropic and additive atomic charges have been widely used to model molecules in computers for the past few decades. The crude approximations in the underlying physics are hindering both their accuracy and transferability across chemical and physical environments. Here we present a new classical potential, AMOEBA+, to capture essential intermolecular forces, including permanent electrostatics, repulsion, dispersion, many-body polarization, short-range charge penetration, and charge transfer, by extending the polarizable multipole-based AMOEBA (Atomic Multipole Optimized Energetics for Biomolecular Applications) model. For a set of common organic molecules, we show that AMOEBA+ with general parameters can reproduce both quantum mechanical interactions and energy decompositions according to Symmetry-Adapted Perturbation Theory (SAPT). Additionally, a new water model based on the AMOEBA+ framework captures various liquid-phase properties in molecular dynamics simulations while remaining consistent with SAPT energy decompositions, utilizing both ab initio data and experimental liquid properties. Our results demonstrate that it is possible to improve the physical basis of classical force fields to advance their accuracy and general applicability.
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Affiliation(s)
- Chengwen Liu
- Department of Biomedical Engineering , The University of Texas at Austin , Austin , Texas 78712 , United States
| | - Jean-Philip Piquemal
- Department of Biomedical Engineering , The University of Texas at Austin , Austin , Texas 78712 , United States.,Laboratoire de Chimie Théorique , Sorbonne Université, UMR7616 CNRS , Paris 75252 , France.,Institut Universitaire de France , Paris Cedex 05, 75005 , France
| | - Pengyu Ren
- Department of Biomedical Engineering , The University of Texas at Austin , Austin , Texas 78712 , United States
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17
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Rackers JA, Ponder JW. Classical Pauli repulsion: An anisotropic, atomic multipole model. J Chem Phys 2019; 150:084104. [PMID: 30823770 DOI: 10.1063/1.5081060] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Pauli repulsion is a key component of any theory of intermolecular interactions. Although Pauli or exchange repulsion has its origin in the quantum mechanical nature of electrons, it is possible to describe the resulting energetic effects via a classical model in terms of the overlap of electron densities. In fact, closed shell intermolecular repulsion can be explained as a diminution of election density in the internuclear region resulting in decreased screening of nuclear charges and increased nuclear-nuclear repulsion. We provide a concise anisotropic repulsion formulation using the atomic multipoles from the Atomic Multipole Optimized Energetics for Biomolecular Applications force field to describe the electron density at each atom in a larger system. Mathematically, the proposed model consists of damped pairwise exponential multipolar repulsion interactions truncated at short range, which are suitable for use in compute-intensive biomolecular force fields and molecular dynamics simulations. Parameters for 26 atom classes encompassing most organic molecules are derived from a fit to Symmetry Adapted Perturbation Theory exchange repulsion energies for the S101 dimer database. Several applications of the multipolar Pauli repulsion model are discussed, including noble gas interactions, analysis of stationary points on the water dimer potential surface, and the directionality of several halogen bonding interactions.
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Affiliation(s)
- Joshua A Rackers
- Program in Computational and Molecular Biophysics, Washington University, School of Medicine, Saint Louis, Missouri 63110, USA
| | - Jay W Ponder
- Department of Chemistry, Washington University in Saint Louis, Saint Louis, Missouri 63130, USA
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