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Myers CA, Lu SY, Shedge S, Pyuskulyan A, Donahoe K, Khanna A, Shi L, Isborn CM. Axial H-Bonding Solvent Controls Inhomogeneous Spectral Broadening, While Peripheral H-Bonding Solvent Controls Vibronic Broadening: Cresyl Violet in Methanol. J Phys Chem B 2024; 128:5685-5699. [PMID: 38832562 DOI: 10.1021/acs.jpcb.4c01401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
Abstract
The dynamics of the nuclei of both a chromophore and its condensed-phase environment control many spectral features, including the vibronic and inhomogeneous broadening present in spectral line shapes. For the cresyl violet chromophore in methanol, we here analyze and isolate the effect of specific chromophore-solvent interactions on simulated spectral densities, reorganization energies, and linear absorption spectra. Employing both chromophore and its condensed-phase environment control many spectral features, including the vibronic and inhomogeneous broadening present in spectral line shapes. For the cresyl violet chromophore in methanol, we here analyze and isolate the effect of specific chromophore-solvent interactions on simulated spectral densities, reorganization energies, and linear absorption spectra. Employing both force field and ab initio molecular dynamics trajectories along with the inclusion of only certain solvent molecules in the excited-state calculations, we determine that the methanol molecules axial to the chromophore are responsible for the majority of inhomogeneous broadening, with a single methanol molecule that forms an axial hydrogen bond dominating the response. The strong peripheral hydrogen bonds do not contribute to spectral broadening, as they are very stable throughout the dynamics and do not lead to increased energy-gap fluctuations. We also find that treating the strong peripheral hydrogen bonds as molecular mechanical point charges during the molecular dynamics simulation underestimates the vibronic coupling. Including these peripheral hydrogen bonding methanol molecules in the quantum-mechanical region in a geometry optimization increases the vibronic coupling, suggesting that a more advanced treatment of these strongly interacting solvent molecules during the molecular dynamics trajectory may be necessary to capture the full vibronic spectral broadening.
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Affiliation(s)
- Christopher A Myers
- Department of Chemistry and Biochemistry, University of California Merced, Merced, California 95343, United States
| | - Shao-Yu Lu
- Department of Chemistry and Biochemistry, University of California Merced, Merced, California 95343, United States
| | - Sapana Shedge
- Department of Chemistry and Biochemistry, University of California Merced, Merced, California 95343, United States
| | - Arthur Pyuskulyan
- Department of Chemistry and Biochemistry, University of California Merced, Merced, California 95343, United States
| | - Katherine Donahoe
- Department of Chemistry and Biochemistry, University of California Merced, Merced, California 95343, United States
| | - Ajay Khanna
- Department of Chemistry and Biochemistry, University of California Merced, Merced, California 95343, United States
| | - Liang Shi
- Department of Chemistry and Biochemistry, University of California Merced, Merced, California 95343, United States
| | - Christine M Isborn
- Department of Chemistry and Biochemistry, University of California Merced, Merced, California 95343, United States
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2
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Greff da Silveira L, Livotto PR, Padula D, Vilhena JG, Prampolini G. Accurate Quantum-Mechanically Derived Force-Fields through a Fragment-Based Approach: Balancing Specificity and Transferability in the Prediction of Self-Assembly in Soft Matter. J Chem Theory Comput 2022; 18:6905-6919. [PMID: 36260420 DOI: 10.1021/acs.jctc.2c00747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The wide range of time/length scales covered by self-assembly in soft matter makes molecular dynamics (MD) the ideal candidate for simulating such a supramolecular phenomenon at an atomistic level. However, the reliability of MD outcomes heavily relies on the accuracy of the adopted force-field (FF). The spontaneous re-ordering in liquid crystalline materials stands as a clear example of such collective self-assembling processes, driven by a subtle and delicate balance between supramolecular interactions and single-molecule flexibility. General-purpose transferable FFs often dramatically fail to reproduce such complex phenomena, for example, the error on the transition temperatures being larger than 100 K. Conversely, quantum-mechanically derived force-fields (QMD-FFs), specifically tailored for the target system, were recently shown (J. Phys. Chem. Lett.2022,13, 243) to allow for the required accuracy as they not only well reproduced transition temperatures but also yielded a quantitative agreement with the experiment on a wealth of structural, dynamic, and thermodynamic properties. The main drawback of this strategy stands in the computational burden connected to the numerous quantum mechanical (QM) calculations usually required for a target-specific parameterization, which has undoubtedly hampered the routine application of QMD-FFs. In this work, we propose a fragment-based strategy to extend the applicability of QMD-FFs, in which the amount of QM calculations is significantly reduced, being a single-molecule-optimized geometry and its Hessian matrix the only QM information required. To validate this route, a new FF is assembled for a large mesogen, exploiting the parameters obtained for two smaller liquid crystalline molecules, in this and previous work. Lengthy MD simulations are carried out with the new transferred QMD-FF, observing again a spontaneous re-orientation in the correct range of temperatures, with good agreement with the available experimental measures. The present results strongly suggest that a partial transfer of QMD-FF parameters can be invoked without a significant loss of accuracy, thus paving the way to exploit the method's intrinsic predictive capabilities in the simulation of novel soft materials.
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Affiliation(s)
- Leandro Greff da Silveira
- Instituto de Química (Universidade Federal do Rio Grande do Sul), Avenida Bento Gonçalves 9500, CEP 91501-970Porto Alegre, Brazil
| | - Paolo Roberto Livotto
- Instituto de Química (Universidade Federal do Rio Grande do Sul), Avenida Bento Gonçalves 9500, CEP 91501-970Porto Alegre, Brazil
| | - Daniele Padula
- Dipartimento di Biotecnologie, Chimica e Farmacia (Università di Siena), via Aldo Moro 2, 53100Siena, SI, Italy
| | - J G Vilhena
- Departamento de Física Teórica de la Materia Condensada (Universidad Autónoma de Madrid), E-28049Madrid, Spain.,Condensed Matter Physics Center (IFIMAC) (Universidad Autónoma de Madrid), E-28049Madrid, Spain
| | - Giacomo Prampolini
- Istituto di Chimica dei Composti OrganoMetallici (ICCOM-CNR), Area della Ricerca, via G. Moruzzi 1, I-56124Pisa, Italy
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3
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P. Oliveira M, Hünenberger PH. Systematic optimization of a fragment-based force field against experimental pure-liquid properties considering large compound families: application to oxygen and nitrogen compounds. Phys Chem Chem Phys 2021; 23:17774-17793. [PMID: 34350931 PMCID: PMC8386690 DOI: 10.1039/d1cp02001c] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 06/30/2021] [Indexed: 12/04/2022]
Abstract
The CombiFF approach is a workflow for the automated refinement of force-field parameters against experimental condensed-phase data, considering entire classes of organic molecules constructed using a fragment library via combinatorial isomer enumeration. One peculiarity of this approach is that it relies on an electronegativity-equalization scheme to account for induction effects within molecules, with values of the atomic hardness and electronegativity as electrostatic parameters, rather than the partial charges themselves. In a previous article [M. P. Oliveira, M. Andrey, S. R. Rieder, L. Kern, D. F. Hahn, S. Riniker, B. A. C. Horta and P. H. Hünenberger, J. Chem. Theory. Comput. 2020, 16, 7525], CombiFF was introduced and applied to calibrate a GROMOS-compatible united-atom force field for the saturated acyclic (halo-)alkane family. Here, this scheme is employed for the construction of a corresponding force field for saturated acyclic compounds encompassing eight common chemical functional groups involving oxygen and/or nitrogen atoms, namely: ether, aldehyde, ketone, ester, alcohol, carboxylic acid, amine, and amide. Monofunctional as well as homo-polyfunctional compounds are considered. A total of 1712 experimental liquid densities ρliq and vaporization enthalpies ΔHvap concerning 1175 molecules are used for the calibration (339 molecules) and validation (836 molecules) of the 102 non-bonded interaction parameters of the force field. Using initial parameter values based on the GROMOS 2016H66 parameter set, convergence is reached after five iterations. Given access to one processor per simulated system, this operation only requires a few days of wall-clock computing time. After optimization, the root-mean-square deviations from experiment are 29.9 (22.4) kg m-3 for ρliq and 4.1 (5.5) kJ mol-1 for ΔHvap for the calibration (validation) set. Thus, a very good level of agreement with experiment is achieved in terms of these two properties, although the errors are inhomogeneously distributed across the different chemical functional groups.
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Affiliation(s)
- Marina P. Oliveira
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCICH-8093 ZürichSwitzerland+41 44 632 5503
| | - Philippe H. Hünenberger
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCICH-8093 ZürichSwitzerland+41 44 632 5503
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4
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Keith JA, Vassilev-Galindo V, Cheng B, Chmiela S, Gastegger M, Müller KR, Tkatchenko A. Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems. Chem Rev 2021; 121:9816-9872. [PMID: 34232033 PMCID: PMC8391798 DOI: 10.1021/acs.chemrev.1c00107] [Citation(s) in RCA: 190] [Impact Index Per Article: 63.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Indexed: 12/23/2022]
Abstract
Machine learning models are poised to make a transformative impact on chemical sciences by dramatically accelerating computational algorithms and amplifying insights available from computational chemistry methods. However, achieving this requires a confluence and coaction of expertise in computer science and physical sciences. This Review is written for new and experienced researchers working at the intersection of both fields. We first provide concise tutorials of computational chemistry and machine learning methods, showing how insights involving both can be achieved. We follow with a critical review of noteworthy applications that demonstrate how computational chemistry and machine learning can be used together to provide insightful (and useful) predictions in molecular and materials modeling, retrosyntheses, catalysis, and drug design.
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Affiliation(s)
- John A. Keith
- Department
of Chemical and Petroleum Engineering Swanson School of Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Valentin Vassilev-Galindo
- Department
of Physics and Materials Science, University
of Luxembourg, L-1511 Luxembourg City, Luxembourg
| | - Bingqing Cheng
- Accelerate
Programme for Scientific Discovery, Department
of Computer Science and Technology, 15 J. J. Thomson Avenue, Cambridge CB3 0FD, United Kingdom
| | - Stefan Chmiela
- Department
of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, 10587, Berlin, Germany
| | - Michael Gastegger
- Department
of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, 10587, Berlin, Germany
| | - Klaus-Robert Müller
- Machine
Learning Group, Technische Universität
Berlin, 10587, Berlin, Germany
- Department
of Artificial Intelligence, Korea University, Anam-dong, Seongbuk-gu, Seoul, 02841, Korea
- Max-Planck-Institut für Informatik, 66123 Saarbrücken, Germany
- Google Research, Brain Team, 10117 Berlin, Germany
| | - Alexandre Tkatchenko
- Department
of Physics and Materials Science, University
of Luxembourg, L-1511 Luxembourg City, Luxembourg
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5
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Vilhena JG, Greff da Silveira L, Livotto PR, Cacelli I, Prampolini G. Automated Parameterization of Quantum Mechanically Derived Force Fields for Soft Materials and Complex Fluids: Development and Validation. J Chem Theory Comput 2021; 17:4449-4464. [PMID: 34185536 DOI: 10.1021/acs.jctc.1c00213] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
The reliability of molecular dynamics (MD) simulations in predicting macroscopic properties of complex fluids and soft materials, such as liquid crystals, colloidal suspensions, or polymers, relies on the accuracy of the adopted force field (FF). We present an automated protocol to derive specific and accurate FFs, fully based on ab initio quantum mechanical (QM) data. The integration of the Joyce and Picky procedures, recently proposed by our group to provide an accurate description of simple liquids, is here extended to larger molecules, capable of exhibiting more complex fluid phases. While the standard Joyce protocol is employed to parameterize the intramolecular FF term, a new automated procedure is here proposed to handle the computational cost of the QM calculations required for the parameterization of the intermolecular FF term. The latter is thus obtained by integrating the old Picky procedure with a fragmentation reconstruction method (FRM) that allows for a reliable, yet computationally feasible sampling of the intermolecular energy surface at the QM level. The whole FF parameterization protocol is tested on a benchmark liquid crystal, and the performances of the resulting quantum mechanically derived (QMD) FF were compared with those delivered by a general-purpose, transferable one, and by the third, "hybrid" FF, where only the bonded terms were refined against QM data. Lengthy atomistic MD simulations are carried out with each FF on extended 5CB systems in both isotropic and nematic phases, eventually validating the proposed protocol by comparing the resulting macroscopic properties with other computational models and with experiments. The QMD-FF yields the best performances, reproducing both phases in the correct range of temperatures and well describing their structure, dynamics, and thermodynamic properties, thus providing a clear protocol that may be explored to predict such properties on other complex fluids or soft materials.
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Affiliation(s)
- J G Vilhena
- Department of Physics, University of Basel, Klingelbergstrasse 82, 4056 Basel, Switzerland
| | - Leandro Greff da Silveira
- Instituto de Química, Universidade Federal do Rio Grande do Sul, Avenida Bento Gonçalves 9500, CEP 91501-970 Porto Alegre, Brazil
| | - Paolo Roberto Livotto
- Instituto de Química, Universidade Federal do Rio Grande do Sul, Avenida Bento Gonçalves 9500, CEP 91501-970 Porto Alegre, Brazil
| | - Ivo Cacelli
- Dipartimento di Chimica e Chimica Industriale, Università di Pisa, Via G. Moruzzi 13, I-56124 Pisa, Italy
| | - Giacomo Prampolini
- Istituto di Chimica dei Composti OrganoMetallici, ICCOM-CNR, Area della Ricerca, via G. Moruzzi 1, I-56124 Pisa, Italy
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6
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Oliveira MP, Andrey M, Rieder SR, Kern L, Hahn DF, Riniker S, Horta BAC, Hünenberger PH. Systematic Optimization of a Fragment-Based Force Field against Experimental Pure-Liquid Properties Considering Large Compound Families: Application to Saturated Haloalkanes. J Chem Theory Comput 2020; 16:7525-7555. [DOI: 10.1021/acs.jctc.0c00683] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Marina P. Oliveira
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Honggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Maurice Andrey
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Honggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Salomé R. Rieder
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Honggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Leyla Kern
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Honggerberg, HCI, CH-8093 Zürich, Switzerland
| | - David F. Hahn
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Honggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Sereina Riniker
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Honggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Bruno A. C. Horta
- Instituto de Química, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil
| | - Philippe H. Hünenberger
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Honggerberg, HCI, CH-8093 Zürich, Switzerland
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7
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Melcr J, Piquemal JP. Accurate Biomolecular Simulations Account for Electronic Polarization. Front Mol Biosci 2019; 6:143. [PMID: 31867342 PMCID: PMC6904368 DOI: 10.3389/fmolb.2019.00143] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Accepted: 11/20/2019] [Indexed: 11/29/2022] Open
Abstract
In this perspective, we discuss where and how accounting for electronic many-body polarization affects the accuracy of classical molecular dynamics simulations of biomolecules. While the effects of electronic polarization are highly pronounced for molecules with an opposite total charge, they are also non-negligible for interactions with overall neutral molecules. For instance, neglecting these effects in important biomolecules like amino acids and phospholipids affects the structure of proteins and membranes having a large impact on interpreting experimental data as well as building coarse grained models. With the combined advances in theory, algorithms and computational power it is currently realistic to perform simulations with explicit polarizable dipoles on systems with relevant sizes and complexity. Alternatively, the effects of electronic polarization can also be included at zero additional computational cost compared to standard fixed-charge force fields using the electronic continuum correction, as was recently demonstrated for several classes of biomolecules.
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Affiliation(s)
- Josef Melcr
- Groningen Biomolecular Sciences and Biotechnology Institute and the Zernike Institute for Advanced Materials, University of Groningen, Groningen, Netherlands
| | - Jean-Philip Piquemal
- Laboratoire de Chimie Théorique, Sorbonne Université, UMR7616 CNRS, Paris, France
- Institut Universitaire de France, Paris, France
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, United States
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8
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Célerse F, Lagardère L, Derat E, Piquemal JP. Massively Parallel Implementation of Steered Molecular Dynamics in Tinker-HP: Comparisons of Polarizable and Non-Polarizable Simulations of Realistic Systems. J Chem Theory Comput 2019; 15:3694-3709. [DOI: 10.1021/acs.jctc.9b00199] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Frédéric Célerse
- Laboratoire de Chimie Théorique, UMR 7616 CNRS, Sorbonne Université, 75005 Paris, France
- Institut Parisien de Chimie Moléculaire, UMR 8232 CNRS, Sorbonne Université, 75005 Paris, France
| | - Louis Lagardère
- Institut des Sciences du Calcul et des Données, Sorbonne Université, 75005 Paris, France
- Institut Parisien de Chimie Physique et Théorique, FR 2622 CNRS, Sorbonne Université, 75005 Paris, France
- Laboratoire de Chimie théorique, UMR 7616 CNRS, Sorbonne Université, 75005 Paris, France
| | - Etienne Derat
- Institut Parisien de Chimie Moléculaire, UMR 8232 CNRS, Sorbonne Université, 75005 Paris, France
| | - Jean-Philip Piquemal
- Laboratoire de Chimie Théorique, UMR 7616 CNRS, Sorbonne Université, 75005 Paris, France
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
- Institut Universitaire de France, 75005 Paris, France
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9
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Prampolini G, Ingrosso F, Segalina A, Caramori S, Foggi P, Pastore M. Dynamical and Environmental Effects on the Optical Properties of an Heteroleptic Ru(II)–Polypyridine Complex: A Multilevel Approach Combining Accurate Ground and Excited State QM-Derived Force Fields, MD and TD-DFT. J Chem Theory Comput 2018; 15:529-545. [DOI: 10.1021/acs.jctc.8b01031] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Giacomo Prampolini
- Istituto di Chimica dei Composti OrganoMetallici (ICCOM-CNR), Area della Ricerca, via G. Moruzzi 1, I-56124 Pisa, Italy
| | - Francesca Ingrosso
- Université de Lorraine, CNRS, Laboratoire de Physique et Chimie Théoriques, F-54000 Nancy, France
| | - Alekos Segalina
- Université de Lorraine, CNRS, Laboratoire de Physique et Chimie Théoriques, F-54000 Nancy, France
| | - Stefano Caramori
- Dipartimento di Scienze Chimiche e Farmaceutiche, Università degli Studi di Ferrara, Via Luigi Borsari 46, I-44100, Ferrara, Italy
| | - Paolo Foggi
- European Laboratory for Non Linear Spectroscopy (LENS), Università di Firenze, Via Nello Carrara 1, I-50019 Sesto Fiorentino Florence, Italy
- INO−CNR, Istituto Nazionale di Ottica, Consiglio Nazionale delle Ricerche, Largo Fermi 6, I-50125 Florence, Italy
- Dipartimento di Chimica, Biologia e Biotecnologie, Università di Perugia, Via Elce di Sotto 8, I-06123 Perugia, Italy
| | - Mariachiara Pastore
- Université de Lorraine, CNRS, Laboratoire de Physique et Chimie Théoriques, F-54000 Nancy, France
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10
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Greff da Silveira L, Jacobs M, Prampolini G, Livotto PR, Cacelli I. Development and Validation of Quantum Mechanically Derived Force-Fields: Thermodynamic, Structural, and Vibrational Properties of Aromatic Heterocycles. J Chem Theory Comput 2018; 14:4884-4900. [PMID: 30040902 DOI: 10.1021/acs.jctc.8b00218] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
A selection of several aromatic molecules, representative of the important class of heterocyclic compounds, has been considered for testing and validating an automated Force Field (FF) parametrization protocol, based only on Quantum Mechanical data. The parametrization is carried out separately for the intra- and intermolecular contributions, employing respectively the Joyce and Picky software packages, previously implemented and refined in our research group. The whole approach is here automated and integrated with a computationally effective yet accurate method, devised very recently ( J. Chem. THEORY Comput., 2018, 14, 543-556) to evaluate a large number of dimer interaction energies. The resulting quantum mechanically derived FFs are then used in extensive molecular dynamics simulations, in order to evaluate a number of thermodynamic, structural, and dynamic properties of the heterocycle's gas and liquid phases. The comparison with the available experimental data is good and furnishes a validation of the presented approach, which can be confidently exploited for the design of novel and more complex materials.
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Affiliation(s)
- Leandro Greff da Silveira
- Instituto de Química , Universidade Federal do Rio Grande do Sul , Avenida Bento Gonçalves 9500 , CEP 91501-970 Porto , Alegre , Brazil
| | - Matheus Jacobs
- Instituto de Química , Universidade Federal do Rio Grande do Sul , Avenida Bento Gonçalves 9500 , CEP 91501-970 Porto , Alegre , Brazil.,Institut für Physik , Humboldt-Universität zu Berlin , Newtonstrasse 15 , 12489 , Berlin , Germany.,IRIS Adelrshof , Humboldt-Universität zu Berlin , Zum Großen Windkanal 6 , 12489 , Berlin , Germany
| | - Giacomo Prampolini
- Istituto di Chimica dei Composti OrganoMetallici (ICCOM-CNR) , Area della Ricerca, via G. Moruzzi 1 , I-56124 Pisa , Italy
| | - Paolo Roberto Livotto
- Instituto de Química , Universidade Federal do Rio Grande do Sul , Avenida Bento Gonçalves 9500 , CEP 91501-970 Porto , Alegre , Brazil
| | - Ivo Cacelli
- Istituto di Chimica dei Composti OrganoMetallici (ICCOM-CNR) , Area della Ricerca, via G. Moruzzi 1 , I-56124 Pisa , Italy.,Dipartimento di Chimica e Chimica Industriale , Università di Pisa , Via G. Moruzzi 13 , I-56124 Pisa , Italy
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11
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Cerezo J, Prampolini G, Cacelli I. Developing accurate intramolecular force fields for conjugated systems through explicit coupling terms. Theor Chem Acc 2018. [DOI: 10.1007/s00214-018-2254-8] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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12
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Schlitter J. The Second Law of Thermodynamics as a Force Law. ENTROPY (BASEL, SWITZERLAND) 2018; 20:e20040234. [PMID: 33265325 PMCID: PMC7512749 DOI: 10.3390/e20040234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Revised: 03/22/2018] [Accepted: 03/27/2018] [Indexed: 06/12/2023]
Abstract
The second law of thermodynamics states the increase of entropy, Δ S > 0 , for real processes from state A to state B at constant energy from chemistry over biological life and engines to cosmic events. The connection of entropy to information, phase-space, and heat is helpful but does not immediately convince observers of the validity and basis of the second law. This gave grounds for finding a rigorous, but more easily acceptable reformulation. Here, we show using statistical mechanics that this principle is equivalent to a force law ⟨ ⟨ f ⟩ ⟩ > 0 in systems where mass centers and forces can be identified. The sign of this net force--the average mean force along a path from A to B--determines the direction of the process. The force law applies to a wide range of processes from machines to chemical reactions. The explanation of irreversibility by a driving force appears more plausible than the traditional formulation as it emphasizes the cause instead of the effect of motions.
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13
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Yao K, Herr JE, Toth DW, Mckintyre R, Parkhill J. The TensorMol-0.1 model chemistry: a neural network augmented with long-range physics. Chem Sci 2018; 9:2261-2269. [PMID: 29719699 PMCID: PMC5897848 DOI: 10.1039/c7sc04934j] [Citation(s) in RCA: 243] [Impact Index Per Article: 40.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Accepted: 01/17/2018] [Indexed: 12/24/2022] Open
Abstract
We construct a robust chemistry consisting of a nearsighted neural network potential, TensorMol-0.1, with screened long-range electrostatic and van der Waals physics. It is offered in an open-source Python package and achieves millihartree accuracy and a scalability to tens-of-thousands of atoms on ordinary laptops.
Traditional force fields cannot model chemical reactivity, and suffer from low generality without re-fitting. Neural network potentials promise to address these problems, offering energies and forces with near ab initio accuracy at low cost. However a data-driven approach is naturally inefficient for long-range interatomic forces that have simple physical formulas. In this manuscript we construct a hybrid model chemistry consisting of a nearsighted neural network potential with screened long-range electrostatic and van der Waals physics. This trained potential, simply dubbed “TensorMol-0.1”, is offered in an open-source Python package capable of many of the simulation types commonly used to study chemistry: geometry optimizations, harmonic spectra, open or periodic molecular dynamics, Monte Carlo, and nudged elastic band calculations. We describe the robustness and speed of the package, demonstrating its millihartree accuracy and scalability to tens-of-thousands of atoms on ordinary laptops. We demonstrate the performance of the model by reproducing vibrational spectra, and simulating the molecular dynamics of a protein. Our comparisons with electronic structure theory and experimental data demonstrate that neural network molecular dynamics is poised to become an important tool for molecular simulation, lowering the resource barrier to simulating chemistry.
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Affiliation(s)
- Kun Yao
- Dept. of Chemistry and Biochemistry , The University of Notre Dame du Lac , USA .
| | - John E Herr
- Dept. of Chemistry and Biochemistry , The University of Notre Dame du Lac , USA .
| | - David W Toth
- Dept. of Chemistry and Biochemistry , The University of Notre Dame du Lac , USA .
| | - Ryker Mckintyre
- Dept. of Chemistry and Biochemistry , The University of Notre Dame du Lac , USA .
| | - John Parkhill
- Dept. of Chemistry and Biochemistry , The University of Notre Dame du Lac , USA .
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