1
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Devereux M, Boittier ED, Meuwly M. Systematic improvement of empirical energy functions in the era of machine learning. J Comput Chem 2024; 45:1899-1913. [PMID: 38695412 DOI: 10.1002/jcc.27367] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 02/13/2024] [Accepted: 02/21/2024] [Indexed: 07/05/2024]
Abstract
The impact of targeted replacement of individual terms in empirical force fields is quantitatively assessed for pure water, dichloromethane (CH 2 Cl 2 ), and solvated K + and Cl - ions. For the electrostatic interactions, point charges (PCs) and machine learning (ML)-based minimally distributed charges (MDCM) fitted to the molecular electrostatic potential are evaluated together with electrostatics based on the Coulomb integral. The impact of explicitly including second-order terms is investigated by adding a fragment molecular orbital (FMO)-derived polarization energy to an existing force field, in this case CHARMM. It is demonstrated that anisotropic electrostatics reduce the RMSE for water (by 1.4 kcal/mol), CH 2 Cl 2 (by 0.8 kcal/mol) and for solvated Cl - clusters (by 0.4 kcal/mol). An additional polarization term can be neglected for CH 2 Cl 2 but further improves the models for pure water (by ∼ 1.0 kcal/mol) and hydrated Cl - (by 0.4 kcal/mol), and is key for solvated K + , reducing the RMSE by 2.3 kcal/mol. A 12-6 Lennard-Jones functional form performs satisfactorily with PC and MDCM electrostatics, but is not appropriate for descriptions that account for the electrostatic penetration energy. The importance of many-body contributions is assessed by comparing a strictly 2-body approach with self-consistent reference data. Two-body interactions suffice for CH 2 Cl 2 whereas water and solvated K + and Cl - ions require explicit many-body corrections. Finally, a many-body-corrected dimer potential energy surface exceeds the accuracy attained using a conventional empirical force field, potentially reaching that of an FMO calculation. The present work systematically quantifies which terms improve the performance of an existing force field and what reference data to use for parametrizing these terms in a tractable fashion for ML fitting of pure and heterogeneous systems.
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Affiliation(s)
- Mike Devereux
- Department of Chemistry, University of Basel, Basel, Switzerland
| | - Eric D Boittier
- Department of Chemistry, University of Basel, Basel, Switzerland
| | - Markus Meuwly
- Department of Chemistry, University of Basel, Basel, Switzerland
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2
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Aydin S, Salehi SM, Töpfer K, Meuwly M. SCN as a local probe of protein structural dynamics. J Chem Phys 2024; 161:055101. [PMID: 39092954 DOI: 10.1063/5.0216657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Accepted: 07/03/2024] [Indexed: 08/04/2024] Open
Abstract
The dynamics of lysozyme is probed by attaching -SCN to all alanine residues. The one-dimensional infrared spectra exhibit frequency shifts in the position of the maximum absorption of 4 cm-1, which is consistent with experiments in different solvents and indicates moderately strong interactions of the vibrational probe with its environment. Isotopic substitution 12C → 13C leads to a redshift by -47 cm-1, which agrees quantitatively with experiments for CN-substituted copper complexes in solution. The low-frequency, far-infrared part of the protein spectra contains label-specific information in the difference spectra when compared with the wild type protein. Depending on the position of the labels, local structural changes are observed. For example, introducing the -SCN label at Ala129 leads to breaking of the α-helical structure with concomitant change in the far-infrared spectrum. Finally, changes in the local hydration of SCN-labeled alanine residues as a function of time can be related to the reorientation of the label. It is concluded that -SCN is potentially useful for probing protein dynamics, both in the high-frequency part (CN-stretch) and in the far-infrared part of the spectrum.
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Affiliation(s)
- Sena Aydin
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
| | - Seyedeh Maryam Salehi
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
| | - Kai Töpfer
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
| | - Markus Meuwly
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
- Department of Chemistry, Brown University, Providence, Rhode Island 02912, USA
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3
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Unke OT, Stöhr M, Ganscha S, Unterthiner T, Maennel H, Kashubin S, Ahlin D, Gastegger M, Medrano Sandonas L, Berryman JT, Tkatchenko A, Müller KR. Biomolecular dynamics with machine-learned quantum-mechanical force fields trained on diverse chemical fragments. SCIENCE ADVANCES 2024; 10:eadn4397. [PMID: 38579003 DOI: 10.1126/sciadv.adn4397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 02/29/2024] [Indexed: 04/07/2024]
Abstract
The GEMS method enables molecular dynamics simulations of large heterogeneous systems at ab initio quality.
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Affiliation(s)
- Oliver T Unke
- Google DeepMind, Tucholskystraße 2, 10117 Berlin, Germany and Brandschenkestrasse 110, 8002 Zürich, Switzerland
- Machine Learning Group, Technische Universität Berlin, 10587 Berlin, Germany
- DFG Cluster of Excellence "Unifying Systems in Catalysis" (UniSysCat), Technische Universität Berlin, 10623 Berlin, Germany
| | - Martin Stöhr
- Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg City, Luxembourg
| | - Stefan Ganscha
- Google DeepMind, Tucholskystraße 2, 10117 Berlin, Germany and Brandschenkestrasse 110, 8002 Zürich, Switzerland
| | - Thomas Unterthiner
- Google DeepMind, Tucholskystraße 2, 10117 Berlin, Germany and Brandschenkestrasse 110, 8002 Zürich, Switzerland
| | - Hartmut Maennel
- Google DeepMind, Tucholskystraße 2, 10117 Berlin, Germany and Brandschenkestrasse 110, 8002 Zürich, Switzerland
| | - Sergii Kashubin
- Google DeepMind, Tucholskystraße 2, 10117 Berlin, Germany and Brandschenkestrasse 110, 8002 Zürich, Switzerland
| | - Daniel Ahlin
- Google DeepMind, Tucholskystraße 2, 10117 Berlin, Germany and Brandschenkestrasse 110, 8002 Zürich, Switzerland
| | - Michael Gastegger
- Machine Learning Group, Technische Universität Berlin, 10587 Berlin, Germany
- DFG Cluster of Excellence "Unifying Systems in Catalysis" (UniSysCat), Technische Universität Berlin, 10623 Berlin, Germany
- BASLEARN - TU Berlin/BASF Joint Lab for Machine Learning, Technische Universität Berlin, 10587 Berlin, Germany
| | - Leonardo Medrano Sandonas
- Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg City, Luxembourg
| | - Joshua T Berryman
- Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg City, Luxembourg
| | - Alexandre Tkatchenko
- Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg City, Luxembourg
| | - Klaus-Robert Müller
- Google DeepMind, Tucholskystraße 2, 10117 Berlin, Germany and Brandschenkestrasse 110, 8002 Zürich, Switzerland
- Machine Learning Group, Technische Universität Berlin, 10587 Berlin, Germany
- Department of Artificial Intelligence, Korea University, Anam-dong, Seongbuk-gu, Seoul 02841, Korea
- Max Planck Institute for Informatics, Stuhlsatzenhausweg, 66123 Saarbrücken, Germany
- BIFOLD - Berlin Institute for the Foundations of Learning and Data, Berlin, Germany
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4
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Zhu Q, Wu Y, Zhao S, Cieplak P, Duan Y, Luo R. Streamlining and Optimizing Strategies of Electrostatic Parameterization. J Chem Theory Comput 2023; 19:6353-6365. [PMID: 37676646 PMCID: PMC10530599 DOI: 10.1021/acs.jctc.3c00659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Abstract
Accurate characterization of electrostatic interactions is crucial in molecular simulation. Various methods and programs have been developed to obtain electrostatic parameters for additive or polarizable models to replicate electrostatic properties obtained from experimental measurements or theoretical calculations. Electrostatic potentials (ESPs), a set of physically well-defined observables from quantum mechanical (QM) calculations, are well suited for optimization efforts due to the ease of collecting a large amount of conformation-dependent data. However, a reliable set of QM ESP computed at an appropriate level of theory and atomic basis set is necessary. In addition, despite the recent development of the PyRESP program for electrostatic parameterizations of induced dipole-polarizable models, the time-consuming and error-prone input file preparation process has limited the widespread use of these protocols. This work aims to comprehensively evaluate the quality of QM ESPs derived by eight methods, including wave function methods such as Hartree-Fock (HF), second-order Møller-Plesset (MP2), and coupled cluster-singles and doubles (CCSD), as well as five hybrid density functional theory (DFT) methods, used in conjunction with 13 different basis sets. The highest theory levels CCSD/aug-cc-pV5Z (a5z) and MP2/aug-cc-pV5Z (a5z) were selected as benchmark data over two homemade data sets. The results show that the hybrid DFT method, ωB97X-D, combined with the aug-cc-pVTZ (a3z) basis set, performs well in reproducing ESPs while taking both accuracy and efficiency into consideration. Moreover, a flexible and user-friendly program called PyRESP_GEN was developed to streamline input file preparation. The restraining strengths, along with strategies for polarizable Gaussian multipole (pGM) model parameterizations, were also optimized. These findings and the program presented in this work facilitate the development and application of induced dipole-polarizable models, such as pGM models, for molecular simulations of both chemical and biological significance.
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Affiliation(s)
- Qiang Zhu
- Department 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
| | - Yongxian Wu
- Department 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
| | - Shiji Zhao
- Nurix Therapeutics, Inc., 1700 Owens St, Suite 205, San Francisco, California 94158, United States
| | - Piotr Cieplak
- SBP Medical Discovery Institute, La Jolla, California 92037, United States
| | - Yong Duan
- UC Davis Genome Center and Department of Biomedical Engineering, University of California, Davis, Davis, California 95616, United States
| | - Ray Luo
- Department 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
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5
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Csizi K, Reiher M. Universal
QM
/
MM
approaches for general nanoscale applications. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2023. [DOI: 10.1002/wcms.1656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Affiliation(s)
| | - Markus Reiher
- Laboratorium für Physikalische Chemie ETH Zürich Zürich Switzerland
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6
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Zhu Q, Ge Y, Li W, Ma J. Treating Polarization Effects in Charged and Polar Bio-Molecules Through Variable Electrostatic Parameters. J Chem Theory Comput 2023; 19:396-411. [PMID: 36592097 DOI: 10.1021/acs.jctc.2c01130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Polarization plays important roles in charged and hydrogen bonding containing systems. Much effort ranging from the construction of physics-based models to quantum mechanism (QM)-based and machine learning (ML)-assisted models have been devoted to incorporating the polarization effect into the conventional force fields at different levels, such as atomic and coarse grained (CG). The application of polarizable force fields or polarization models was limited by two aspects, namely, computational cost and transferability. Different from physics-based models, no predetermining parameters were required in the QM-based approaches. Taking advantage of both the accuracy of QM calculations and efficiency of molecular mechanism (MM) and ML, polarization effects could be treated more efficiently while maintaining the QM accuracy. The computational cost could be reduced with variable electrostatic parameters, such as the charge, dipole, and electronic dielectric constant with the help of linear scaling fragmentation-based QM calculations and ML models. Polarization and entropy effects on the prediction of partition coefficient of druglike molecules are demonstrated by using both explicit or implicit all-atom molecular dynamics simulations and machine learning-assisted models. Directions and challenges for future development are also envisioned.
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Affiliation(s)
- Qiang Zhu
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education, Institute of Theoretical and Computational Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing210023, P. R. China
| | - Yang Ge
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education, Institute of Theoretical and Computational Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing210023, P. R. China
| | - Wei Li
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education, Institute of Theoretical and Computational Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing210023, P. R. China
| | - Jing Ma
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education, Institute of Theoretical and Computational Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing210023, P. R. China
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7
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Boittier ED, Devereux M, Meuwly M. Molecular Dynamics with Conformationally Dependent, Distributed Charges. J Chem Theory Comput 2022; 18:7544-7554. [PMID: 36346403 DOI: 10.1021/acs.jctc.2c00693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Accounting for geometry-induced changes in the electronic distribution in molecular simulation is important for capturing effects such as charge flow, charge anisotropy, and polarization. Multipolar force fields have demonstrated their ability to correctly represent chemically significant features such as anisotropy and sigma holes. It has also been shown that off-center point charges offer a compact alternative with similar accuracy. Here, it is demonstrated that allowing relocation of charges within a minimally distributed charge model (MDCM) with respect to their reference atoms is a viable route to capture changes in the molecular charge distribution depending on geometry, i.e., intramolecular polarization. The approach, referred to as "flexible MDCM" (fMDCM), is validated on a number of small molecules and provides accuracies in the electrostatic potential (ESP) of 0.5 kcal/mol on average compared with reference data from electronic structure calculations, whereas MDCM and point charges have root mean squared errors of a factor of 2 to 5 higher. In addition, MD simulations in the NVE ensemble using fMDCM for a box of flexible water molecules with periodic boundary conditions show a width of 0.1 kcal/mol for the fluctuation around the mean at 300 K on the 10 ns time scale. For water, the equilibrium valence angle in the gas phase is found to increase by 2° for simulations in the condensed phase which is consistent with experiment. The accuracy in capturing the geometry dependence of the ESP together with the long-time stability in energy conserving simulations makes fMDCM a promising tool to introduce advanced electrostatics into atomistic simulations.
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Affiliation(s)
- Eric D Boittier
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
| | - Mike Devereux
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
| | - Markus Meuwly
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
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8
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Cheng Y, Verstraelen T. A new framework for frequency-dependent polarizable force fields. J Chem Phys 2022; 157:124106. [PMID: 36182425 DOI: 10.1063/5.0115151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
A frequency-dependent extension of the polarizable force field "Atom-Condensed Kohn-Sham density functional theory approximated to the second-order" (ACKS2) [Verstraelen et al., J. Chem. Phys. 141, 194114 (2014)] is proposed, referred to as ACKS2ω. The method enables theoretical predictions of dynamical response properties of finite systems after partitioning of the frequency-dependent molecular response function. Parameters in this model are computed simply as expectation values of an electronic wavefunction, and the hardness matrix is entirely reused from ACKS2 as an adiabatic approximation is used. A numerical validation shows that accurate models can already be obtained with atomic monopoles and dipoles. Absorption spectra of 42 organic and inorganic molecular monomers are evaluated using ACKS2ω, and our results agree well with the time-dependent DFT calculations. Also for the calculation of C6 dispersion coefficients, ACKS2ω closely reproduces its TDDFT reference. When parameters for ACKS2ω are derived from a PBE/aug-cc-pVDZ ground state, it reproduces experimental values for 903 organic and inorganic intermolecular pairs with an MAPE of 3.84%. Our results confirm that ACKS2ω offers a solid connection between the quantum-mechanical description of frequency-dependent response and computationally efficient force-field models.
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Affiliation(s)
- YingXing Cheng
- Center for Molecular Modeling (CMM), Ghent University, Technologiepark-Zwijnaarde 46, B-9052 Gent, Belgium
| | - Toon Verstraelen
- Center for Molecular Modeling (CMM), Ghent University, Technologiepark-Zwijnaarde 46, B-9052 Gent, Belgium
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9
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Sajjan M, Li J, Selvarajan R, Sureshbabu SH, Kale SS, Gupta R, Singh V, Kais S. Quantum machine learning for chemistry and physics. Chem Soc Rev 2022; 51:6475-6573. [PMID: 35849066 DOI: 10.1039/d2cs00203e] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Machine learning (ML) has emerged as a formidable force for identifying hidden but pertinent patterns within a given data set with the objective of subsequent generation of automated predictive behavior. In recent years, it is safe to conclude that ML and its close cousin, deep learning (DL), have ushered in unprecedented developments in all areas of physical sciences, especially chemistry. Not only classical variants of ML, even those trainable on near-term quantum hardwares have been developed with promising outcomes. Such algorithms have revolutionized materials design and performance of photovoltaics, electronic structure calculations of ground and excited states of correlated matter, computation of force-fields and potential energy surfaces informing chemical reaction dynamics, reactivity inspired rational strategies of drug designing and even classification of phases of matter with accurate identification of emergent criticality. In this review we shall explicate a subset of such topics and delineate the contributions made by both classical and quantum computing enhanced machine learning algorithms over the past few years. We shall not only present a brief overview of the well-known techniques but also highlight their learning strategies using statistical physical insight. The objective of the review is not only to foster exposition of the aforesaid techniques but also to empower and promote cross-pollination among future research in all areas of chemistry which can benefit from ML and in turn can potentially accelerate the growth of such algorithms.
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Affiliation(s)
- Manas Sajjan
- Department of Chemistry, Purdue University, West Lafayette, IN-47907, USA. .,Purdue Quantum Science and Engineering Institute, Purdue University, West Lafayette, Indiana 47907, USA
| | - Junxu Li
- Purdue Quantum Science and Engineering Institute, Purdue University, West Lafayette, Indiana 47907, USA.,Department of Physics and Astronomy, Purdue University, West Lafayette, IN-47907, USA
| | - Raja Selvarajan
- Purdue Quantum Science and Engineering Institute, Purdue University, West Lafayette, Indiana 47907, USA.,Department of Physics and Astronomy, Purdue University, West Lafayette, IN-47907, USA
| | - Shree Hari Sureshbabu
- Purdue Quantum Science and Engineering Institute, Purdue University, West Lafayette, Indiana 47907, USA.,Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN-47907, USA
| | - Sumit Suresh Kale
- Department of Chemistry, Purdue University, West Lafayette, IN-47907, USA. .,Purdue Quantum Science and Engineering Institute, Purdue University, West Lafayette, Indiana 47907, USA
| | - Rishabh Gupta
- Department of Chemistry, Purdue University, West Lafayette, IN-47907, USA. .,Purdue Quantum Science and Engineering Institute, Purdue University, West Lafayette, Indiana 47907, USA
| | - Vinit Singh
- Department of Chemistry, Purdue University, West Lafayette, IN-47907, USA. .,Purdue Quantum Science and Engineering Institute, Purdue University, West Lafayette, Indiana 47907, USA
| | - Sabre Kais
- Department of Chemistry, Purdue University, West Lafayette, IN-47907, USA. .,Purdue Quantum Science and Engineering Institute, Purdue University, West Lafayette, Indiana 47907, USA.,Department of Physics and Astronomy, Purdue University, West Lafayette, IN-47907, USA.,Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN-47907, USA
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10
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Töpfer K, Upadhyay M, Meuwly M. Quantitative molecular simulations. Phys Chem Chem Phys 2022; 24:12767-12786. [PMID: 35593769 PMCID: PMC9158373 DOI: 10.1039/d2cp01211a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Accepted: 04/30/2022] [Indexed: 11/21/2022]
Abstract
All-atom simulations can provide molecular-level insights into the dynamics of gas-phase, condensed-phase and surface processes. One important requirement is a sufficiently realistic and detailed description of the underlying intermolecular interactions. The present perspective provides an overview of the present status of quantitative atomistic simulations from colleagues' and our own efforts for gas- and solution-phase processes and for the dynamics on surfaces. Particular attention is paid to direct comparison with experiment. An outlook discusses present challenges and future extensions to bring such dynamics simulations even closer to reality.
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Affiliation(s)
- Kai Töpfer
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland.
| | - Meenu Upadhyay
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland.
| | - Markus Meuwly
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland.
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11
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Abstract
We review different models for introducing electric polarization in force fields, with special focus on methods where polarization is modelled at the atomic charge level. While electric polarization has been included in several force fields, the common approach has been to focus on atomic dipole polarizability. Several approaches allow modelling electric polarization by using charge-flow between charge sites instead, but this has been less exploited, despite that atomic charges and charge-flow is expected to be more important than atomic dipoles and dipole polarizability. A number of challenges are required to be solved for charge-flow models to be incorporated into polarizable force fields, for example how to parameterize the models and how to make them computational efficient.
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Affiliation(s)
- Frank Jensen
- Department of Chemistry, Aarhus University, Denmark.
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12
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Salehi SM, Käser S, Töpfer K, Diamantis P, Pfister R, Hamm P, Rothlisberger U, Meuwly M. Hydration dynamics and IR spectroscopy of 4-fluorophenol. Phys Chem Chem Phys 2022; 24:26046-26060. [PMID: 36268728 PMCID: PMC9627945 DOI: 10.1039/d2cp02857c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Halogenated groups are relevant in pharmaceutical applications and potentially useful spectroscopic probes for infrared spectroscopy. In this work, the structural dynamics and infrared spectroscopy of para-fluorophenol (F-PhOH) and phenol (PhOH) is investigated in the gas phase and in water using a combination of experiment and molecular dynamics (MD) simulations. The gas phase and solvent dynamics around F-PhOH and PhOH is characterized from atomistic simulations using empirical energy functions with point charges or multipoles for the electrostatics, Machine Learning (ML) based parametrizations and with full ab initio (QM) and mixed Quantum Mechanical/Molecular Mechanics (QM/MM) simulations with a particular focus on the CF- and OH-stretch region. The CF-stretch band is heavily mixed with other modes whereas the OH-stretch in solution displays a characteristic high-frequency peak around 3600 cm−1 most likely associated with the –OH group of PhOH and F-PhOH together with a characteristic progression below 3000 cm−1 due to coupling with water modes which is also reproduced by several of the simulations. Solvent and radial distribution functions indicate that the CF-site is largely hydrophobic except for simulations using point charges which renders them unsuited for correctly describing hydration and dynamics around fluorinated sites. The hydrophobic character of the CF-group is particularly relevant for applications in pharmaceutical chemistry with a focus on local hydration and interaction with the surrounding protein. Halogenated groups are relevant in pharmaceutical applications and potentially useful spectroscopic probes for infrared spectroscopy.![]()
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Affiliation(s)
- Seyedeh Maryam Salehi
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
| | - Silvan Käser
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
| | - Kai Töpfer
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
| | - Polydefkis Diamantis
- Laboratory of Computational Chemistry and Biochemistry, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Rolf Pfister
- Department of Chemistry, University of Zurich, Switzerland
| | - Peter Hamm
- Department of Chemistry, University of Zurich, Switzerland
| | - Ursula Rothlisberger
- Laboratory of Computational Chemistry and Biochemistry, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Markus Meuwly
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
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13
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Mondal P, Cazade PA, Das AK, Bereau T, Meuwly M. Multipolar Force Fields for Amide-I Spectroscopy from Conformational Dynamics of the Alanine Trimer. J Phys Chem B 2021; 125:10928-10938. [PMID: 34559531 DOI: 10.1021/acs.jpcb.1c05423] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The dynamics and spectroscopy of N-methyl-acetamide (NMA) and trialanine in solution are characterized from molecular dynamics simulations using different energy functions, including a conventional point charge (PC)-based force field, one based on a multipolar (MTP) representation of the electrostatics, and a semiempirical DFT method. For the 1D infrared spectra, the frequency splitting between the two amide-I groups is 10 cm-1 from the PC, 13 cm-1 from the MTP, and 47 cm-1 from self-consistent charge density functional tight-binding (SCC-DFTB) simulations, compared with 25 cm-1 from experiment. The frequency trajectory required for the frequency fluctuation correlation function (FFCF) is determined from individual normal mode (INM) and full normal mode (FNM) analyses of the amide-I vibrations. The spectroscopy, time-zero magnitude of the FFCF C(t = 0), and the static component Δ02 from simulations using MTP and analysis based on FNM are all consistent with experiments for (Ala)3. Contrary to this, for the analysis excluding mode-mode coupling (INM), the FFCF decays to zero too rapidly and for simulations with a PC-based force field, the Δ02 is too small by a factor of two compared with experiments. Simulations with SCC-DFTB agree better with experiment for these observables than those from PC-based simulations. The conformational ensemble sampled from simulations using PCs is consistent with the literature (including PII, β, αR, and αL), whereas that covered by the MTP-based simulations is dominated by PII with some contributions from β and αR. This agrees with and confirms recently reported Bayesian-refined populations based on 1D infrared experiments. FNM analysis together with a MTP representation provides a meaningful model to correctly describe the dynamics of hydrated trialanine.
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Affiliation(s)
- Padmabati Mondal
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, Basel 4056, Switzerland
| | - Pierre-André Cazade
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, Basel 4056, Switzerland
| | - Akshaya K Das
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, Basel 4056, Switzerland
| | - Tristan Bereau
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, Basel 4056, Switzerland
| | - Markus Meuwly
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, Basel 4056, Switzerland.,Department of Chemistry, Brown University, Providence/RI 02912, United States
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14
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Unke O, Chmiela S, Sauceda HE, Gastegger M, Poltavsky I, Schütt KT, Tkatchenko A, Müller KR. Machine Learning Force Fields. Chem Rev 2021; 121:10142-10186. [PMID: 33705118 PMCID: PMC8391964 DOI: 10.1021/acs.chemrev.0c01111] [Citation(s) in RCA: 371] [Impact Index Per Article: 123.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Indexed: 12/27/2022]
Abstract
In recent years, the use of machine learning (ML) in computational chemistry has enabled numerous advances previously out of reach due to the computational complexity of traditional electronic-structure methods. One of the most promising applications is the construction of ML-based force fields (FFs), with the aim to narrow the gap between the accuracy of ab initio methods and the efficiency of classical FFs. The key idea is to learn the statistical relation between chemical structure and potential energy without relying on a preconceived notion of fixed chemical bonds or knowledge about the relevant interactions. Such universal ML approximations are in principle only limited by the quality and quantity of the reference data used to train them. This review gives an overview of applications of ML-FFs and the chemical insights that can be obtained from them. The core concepts underlying ML-FFs are described in detail, and a step-by-step guide for constructing and testing them from scratch is given. The text concludes with a discussion of the challenges that remain to be overcome by the next generation of ML-FFs.
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Affiliation(s)
- Oliver
T. Unke
- Machine
Learning Group, Technische Universität
Berlin, 10587 Berlin, Germany
- DFG
Cluster of Excellence “Unifying Systems in Catalysis”
(UniSysCat), Technische Universität Berlin, 10623 Berlin, Germany
| | - Stefan Chmiela
- Machine
Learning Group, Technische Universität
Berlin, 10587 Berlin, Germany
| | - Huziel E. Sauceda
- Machine
Learning Group, Technische Universität
Berlin, 10587 Berlin, Germany
- BASLEARN,
BASF-TU Joint Lab, Technische Universität
Berlin, 10587 Berlin, Germany
| | - Michael Gastegger
- Machine
Learning Group, Technische Universität
Berlin, 10587 Berlin, Germany
- DFG
Cluster of Excellence “Unifying Systems in Catalysis”
(UniSysCat), Technische Universität Berlin, 10623 Berlin, Germany
- BASLEARN,
BASF-TU Joint Lab, Technische Universität
Berlin, 10587 Berlin, Germany
| | - Igor Poltavsky
- Department
of Physics and Materials Science, University
of Luxembourg, L-1511 Luxembourg City, Luxembourg
| | - Kristof T. Schütt
- Machine
Learning Group, Technische Universität
Berlin, 10587 Berlin, Germany
| | - Alexandre Tkatchenko
- Department
of Physics and Materials Science, University
of Luxembourg, L-1511 Luxembourg City, Luxembourg
| | - Klaus-Robert Müller
- Machine
Learning Group, Technische Universität
Berlin, 10587 Berlin, Germany
- BIFOLD−Berlin
Institute for the Foundations of Learning and Data, Berlin, Germany
- Department
of Artificial Intelligence, Korea University, Anam-dong, Seongbuk-gu, Seoul 02841, Korea
- Max Planck
Institute for Informatics, Stuhlsatzenhausweg, 66123 Saarbrücken, Germany
- Google
Research, Brain Team, Berlin, Germany
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15
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Devereux M, Pezzella M, Raghunathan S, Meuwly M. Polarizable Multipolar Molecular Dynamics Using Distributed Point Charges. J Chem Theory Comput 2020; 16:7267-7280. [PMID: 33245239 DOI: 10.1021/acs.jctc.0c00883] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Distributed point charge models (DCM) and their minimal variants (MDCM) have been integrated with tools widely used for condensed-phase simulations, including a virial-based barostat and a slow-growth algorithm for thermodynamic integration. Minimal DCM is further developed in a systematic fashion to reduce fitting errors in the electrostatic interaction energy, and a new fragment-based approach offers considerable speedup of the MDCM fitting process for larger molecules with increased numbers of off-centered charged sites. Finally, polarizable (M)DCM is also introduced in the present work. The developments are used in condensed-phase simulations of popular force fields with commonly applied simulation conditions. (M)DCM equivalents for a range of widely used water force fields and for fluorobenzene (PhF) are developed and applied along with the original models to evaluate the impact of reformulating the electrostatic term. Comparisons of the molecular electrostatic potential (MEP), electrostatic interaction energies, and bulk properties from molecular dynamics simulations for a range of models from simple TIPnP (n = 3-5) to the polarizable, multipolar iAMOEBA models for water and an existing quadrupolar model for PhF confirm that DCMs retain the accuracy of the original models, providing a homogeneous, efficient, and generic point charge alternative to a multipolar electrostatic model for force field development and multilevel simulations.
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Affiliation(s)
- Mike Devereux
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
| | - Marco Pezzella
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
| | - Shampa Raghunathan
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
| | - Markus Meuwly
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland.,Department of Chemistry, Brown University, Providence, Rhode Island 02912, United States
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16
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Spinn A, Handle PH, Kraml J, Hofer TS, Liedl KR. Charge Anisotropy of Nitrogen: Where Chemical Intuition Fails. J Chem Theory Comput 2020; 16:4443-4453. [PMID: 32427474 PMCID: PMC7365557 DOI: 10.1021/acs.jctc.0c00204] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Indexed: 01/03/2023]
Abstract
For more than half a century computer simulations were developed and employed to study ensemble properties of a wide variety of atomic and molecular systems with tremendous success. Nowadays, a selection of force-fields is available that describe the interactions in such systems. A key feature of force-fields is an adequate description of the electrostatic potential (ESP). Several force-fields model the ESP via point charges positioned at the atom centers. A major shortcoming of this approach, its inability to model anisotropies in the ESP, can be mitigated using additional charge sites. It has been shown that nitrogen is the most problematic element abundant in many polymers as well as large molecules of biological origin. To tackle this issue, small organic molecules containing a single nitrogen atom were studied. In performing rigorous scans of the surroundings of these nitrogen atoms, positions where a single extra charge can enhance the ESP description the most were identified. Significant improvements are found for ammonia, amines, and amides. Interestingly, the optimal location for the extra charge does not correlate with the chemically intuitive position of the nitrogen lone pair. In fact, the placement of an extra charge in the lone-pair location does not lead to significant improvements in most cases.
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Affiliation(s)
| | | | - Johannes Kraml
- Institute of General, Inorganic
and Theoretical Chemistry, University of
Innsbruck, Innrain 80-82, A-6020 Innsbruck, Austria
| | - Thomas S. Hofer
- Institute of General, Inorganic
and Theoretical Chemistry, University of
Innsbruck, Innrain 80-82, A-6020 Innsbruck, Austria
| | - Klaus R. Liedl
- Institute of General, Inorganic
and Theoretical Chemistry, University of
Innsbruck, Innrain 80-82, A-6020 Innsbruck, Austria
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17
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Koner D, Salehi SM, Mondal P, Meuwly M. Non-conventional force fields for applications in spectroscopy and chemical
reaction dynamics. J Chem Phys 2020; 153:010901. [DOI: 10.1063/5.0009628] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Affiliation(s)
- Debasish Koner
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, 4056 Basel,
Switzerland
| | - Seyedeh Maryam Salehi
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, 4056 Basel,
Switzerland
| | - Padmabati Mondal
- Indian Institute of Science Education and Research (IISER) Tirupati, Karakambadi Road, Mangalam, Tirupati 517507, Andhra
Pradesh, India
| | - Markus Meuwly
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel,
Switzerland and Department of Chemistry, Brown University, Providence, Rhode Island, USA
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18
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Yu Y, Shi L. Vibrational solvatochromism of the ester carbonyl vibration of PCBM in organic solutions. J Chem Phys 2019. [DOI: 10.1063/1.5111046] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Affiliation(s)
- Yue Yu
- School of Natural Sciences, University of California, Merced, California 95343, USA
| | - Liang Shi
- School of Natural Sciences, University of California, Merced, California 95343, USA
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19
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Poier PP, Jensen F. Describing Molecular Polarizability by a Bond Capacity Model. J Chem Theory Comput 2019; 15:3093-3107. [PMID: 30920212 DOI: 10.1021/acs.jctc.8b01215] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
We propose a bond capacity model for describing molecular polarization in force field energy functions at the charge-only level. Atomic charges are calculated by allowing charge to flow between atom pairs according to a bond capacity and a difference in electrostatic potential. The bond capacity is closely related to the bond order and decays to zero as the bond distance is increased. The electrostatic potential is composed of an intrinsic potential, identified as the electronegativity, and a screened Coulomb potential from all other charges. The bond capacity model leads to integer fragment charges upon bond dissociation and displays linear scaling of the polarizability with system size. Bond capacity parameters can be derived from reference molecular polarizabilities, while electronegativity parameters can be derived from reference atomic charges or a reference molecular electrostatic potential. Out-of-plane polarization for planar systems is modeled by off-nuclei charge sites. The model is shown to be able to reproduce anisotropic reference molecular polarizabilities with an accuracy of ∼10% using a limited set of bond capacity parameters and can describe both inter- and intramolecular polarization.
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Affiliation(s)
- Pier Paolo Poier
- Department of Chemistry , Aarhus University , Langelandsgade 140 , DK-8000 Aarhus , Denmark
| | - Frank Jensen
- Department of Chemistry , Aarhus University , Langelandsgade 140 , DK-8000 Aarhus , Denmark
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20
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Doyle CC, Shi Y, Beck TL. The Importance of the Water Molecular Quadrupole for Estimating Interfacial Potential Shifts Acting on Ions Near the Liquid–Vapor Interface. J Phys Chem B 2019; 123:3348-3358. [DOI: 10.1021/acs.jpcb.9b01289] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Carrie C. Doyle
- Department of Chemistry, University of Cincinnati, Cincinnati, Ohio 45221, United States
| | - Yu Shi
- Department of Chemistry, University of Cincinnati, Cincinnati, Ohio 45221, United States
| | - Thomas L. Beck
- Department of Chemistry, University of Cincinnati, Cincinnati, Ohio 45221, United States
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21
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Jing Z, Liu C, Cheng SY, Qi R, Walker BD, Piquemal JP, Ren P. Polarizable Force Fields for Biomolecular Simulations: Recent Advances and Applications. Annu Rev Biophys 2019; 48:371-394. [PMID: 30916997 DOI: 10.1146/annurev-biophys-070317-033349] [Citation(s) in RCA: 217] [Impact Index Per Article: 43.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Realistic modeling of biomolecular systems requires an accurate treatment of electrostatics, including electronic polarization. Due to recent advances in physical models, simulation algorithms, and computing hardware, biomolecular simulations with advanced force fields at biologically relevant timescales are becoming increasingly promising. These advancements have not only led to new biophysical insights but also afforded opportunities to advance our understanding of fundamental intermolecular forces. This article describes the recent advances and applications, as well as future directions, of polarizable force fields in biomolecular simulations.
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Affiliation(s)
- Zhifeng Jing
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA;
| | - Chengwen Liu
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA;
| | - Sara Y Cheng
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA;
| | - Rui Qi
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA;
| | - Brandon D Walker
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA;
| | - Jean-Philip Piquemal
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA; .,Sorbonne Université, CNRS, Laboratoire de Chimie Theórique, 75252 Paris CEDEX 05, France.,Institut Universitaire de France, 75005 Paris, France
| | - Pengyu Ren
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA;
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22
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Horton JT, Allen AEA, Dodda LS, Cole DJ. QUBEKit: Automating the Derivation of Force Field Parameters from Quantum Mechanics. J Chem Inf Model 2019; 59:1366-1381. [DOI: 10.1021/acs.jcim.8b00767] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Joshua T. Horton
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, United Kingdom
| | - Alice E. A. Allen
- TCM Group, Cavendish Laboratory, 19 JJ Thomson Avenue, Cambridge CB3 0HE, United Kingdom
| | - Leela S. Dodda
- Department of Chemistry, Yale University, New Haven, Connecticut 06520-8107, United States
| | - Daniel J. Cole
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, United Kingdom
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23
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Titov OI, Shulga DA, Palyulin VA. Quadrupole Correction: From Molecular Electrostatic Potential to Free Energies of Halogen Bonding. J Chem Theory Comput 2018; 15:1159-1167. [DOI: 10.1021/acs.jctc.8b00739] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Oleg I. Titov
- Department of Chemistry, Lomonosov Moscow State University, Moscow 119991, Russia
| | - Dmitry A. Shulga
- Department of Chemistry, Lomonosov Moscow State University, Moscow 119991, Russia
| | - Vladimir A. Palyulin
- Department of Chemistry, Lomonosov Moscow State University, Moscow 119991, Russia
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24
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Piquemal JP, Jordan KD. Preface: Special Topic: From Quantum Mechanics to Force Fields. J Chem Phys 2018; 147:161401. [PMID: 29096449 DOI: 10.1063/1.5008887] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
This Special Topic issue entitled "From Quantum Mechanics to Force Fields" is dedicated to the ongoing efforts of the theoretical chemistry community to develop a new generation of accurate force fields based on data from high-level electronic structure calculations and to develop faster electronic structure methods for testing and designing force fields as well as for carrying out simulations. This issue includes a collection of 35 original research articles that illustrate recent theoretical advances in the field. It provides a timely snapshot of recent developments in the generation of approaches to enable more accurate molecular simulations of processes important in chemistry, physics, biophysics, and materials science.
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Affiliation(s)
- Jean-Philip Piquemal
- Laboratoire de Chimie Théorique, UMR 7616 CNRS, UPMC, Sorbonne Universités, 75252 Paris Cedex 05, France
| | - Kenneth D Jordan
- Department of Chemistry, The University of Pittsburgh, 219 Parkman Avenue, Pittsburgh, Pennsylvania 15260, USA
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25
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Schmid MH, Das AK, Landis CR, Meuwly M. Multi-State VALBOND for Atomistic Simulations of Hypervalent Molecules, Metal Complexes, and Reactions. J Chem Theory Comput 2018; 14:3565-3578. [DOI: 10.1021/acs.jctc.7b01210] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Affiliation(s)
- Maurus H. Schmid
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, 4056 Basel, Switzerland
| | - Akshaya Kumar Das
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, 4056 Basel, Switzerland
| | - Clark R. Landis
- Department of Chemistry, University of Wisconsin—Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Markus Meuwly
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, 4056 Basel, Switzerland
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26
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El Hage K, Bemish RJ, Meuwly M. From in silica to in silico: retention thermodynamics at solid–liquid interfaces. Phys Chem Chem Phys 2018; 20:18610-18622. [DOI: 10.1039/c8cp02899k] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The dynamics of solvated molecules at the solid/liquid interface is essential for a molecular-level understanding for the solution thermodynamics in reversed phase liquid chromatography (RPLC).
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Affiliation(s)
- Krystel El Hage
- Department of Chemistry
- University of Basel
- CH-4056 Basel
- Switzerland
| | - Raymond J. Bemish
- Air Force Research Laboratory
- Space Vehicles Directorate
- Kirtland AFB
- USA
| | - Markus Meuwly
- Department of Chemistry
- University of Basel
- CH-4056 Basel
- Switzerland
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27
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Fracchia F, Del Frate G, Mancini G, Rocchia W, Barone V. Force Field Parametrization of Metal Ions from Statistical Learning Techniques. J Chem Theory Comput 2017; 14:255-273. [PMID: 29112432 PMCID: PMC5763284 DOI: 10.1021/acs.jctc.7b00779] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
![]()
A novel
statistical procedure has been developed to optimize the parameters
of nonbonded force fields of metal ions in soft matter. The criterion
for the optimization is the minimization of the deviations from ab initio forces and energies calculated for model systems.
The method exploits the combination of the linear ridge regression
and the cross-validation techniques with the differential evolution
algorithm. Wide freedom in the choice of the functional form of the
force fields is allowed since both linear and nonlinear parameters
can be optimized. In order to maximize the information content of
the data employed in the fitting procedure, the composition of the
training set is entrusted to a combinatorial optimization algorithm
which maximizes the dissimilarity of the included instances. The methodology
has been validated using the force field parametrization of five metal
ions (Zn2+, Ni2+, Mg2+, Ca2+, and Na+) in water as test cases.
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Affiliation(s)
| | | | - Giordano Mancini
- Scuola Normale Superiore, Piazza dei Cavalieri 7, I-56126 Pisa, Italy.,Istituto Nazionale di Fisica Nucleare (INFN) sezione di Pisa , Largo Bruno Pontecorvo 3, I-56127 Pisa, Italy
| | - Walter Rocchia
- Department of Drug Discovery and Development, Istituto Italiano di Tecnologia , 16163 Genova, Italy
| | - Vincenzo Barone
- Scuola Normale Superiore, Piazza dei Cavalieri 7, I-56126 Pisa, Italy.,Istituto Nazionale di Fisica Nucleare (INFN) sezione di Pisa , Largo Bruno Pontecorvo 3, I-56127 Pisa, Italy
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28
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Antipov SV, Bhattacharyya S, El Hage K, Xu ZH, Meuwly M, Rothlisberger U, Vaníček J. Ultrafast dynamics induced by the interaction of molecules with electromagnetic fields: Several quantum, semiclassical, and classical approaches. STRUCTURAL DYNAMICS (MELVILLE, N.Y.) 2017; 4:061509. [PMID: 29376107 PMCID: PMC5758379 DOI: 10.1063/1.4996559] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/17/2017] [Accepted: 10/11/2017] [Indexed: 06/07/2023]
Abstract
Several strategies for simulating the ultrafast dynamics of molecules induced by interactions with electromagnetic fields are presented. After a brief overview of the theory of molecule-field interaction, we present several representative examples of quantum, semiclassical, and classical approaches to describe the ultrafast molecular dynamics, including the multiconfiguration time-dependent Hartree method, Bohmian dynamics, local control theory, semiclassical thawed Gaussian approximation, phase averaging, dephasing representation, molecular mechanics with proton transfer, and multipolar force fields. In addition to the general overview, some focus is given to the description of nuclear quantum effects and to the direct dynamics, in which the ab initio energies and forces acting on the nuclei are evaluated on the fly. Several practical applications, performed within the framework of the Swiss National Center of Competence in Research "Molecular Ultrafast Science and Technology," are presented: These include Bohmian dynamics description of the collision of H with H2, local control theory applied to the photoinduced ultrafast intramolecular proton transfer, semiclassical evaluation of vibrationally resolved electronic absorption, emission, photoelectron, and time-resolved stimulated emission spectra, infrared spectroscopy of H-bonding systems, and multipolar force fields applications in the condensed phase.
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Affiliation(s)
- Sergey V Antipov
- Laboratory of Theoretical Physical Chemistry, Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Swarnendu Bhattacharyya
- Laboratory of Computational Chemistry and Biochemistry, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Krystel El Hage
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
| | - Zhen-Hao Xu
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
| | - Markus Meuwly
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
| | - Ursula Rothlisberger
- Laboratory of Computational Chemistry and Biochemistry, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Jiří Vaníček
- Laboratory of Theoretical Physical Chemistry, Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
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