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Kantonen SM, Muddana HS, Schauperl M, Henriksen NM, Wang LP, Gilson MK. Data-Driven Mapping of Gas-Phase Quantum Calculations to General Force Field Lennard-Jones Parameters. J Chem Theory Comput 2020; 16:1115-1127. [PMID: 31917572 PMCID: PMC7101068 DOI: 10.1021/acs.jctc.9b00713] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Molecular dynamics simulations are helpful tools for a range of applications, ranging from drug discovery to protein structure determination. The successful use of this technology largely depends on the potential function, or force field, used to determine the potential energy at each configuration of the system. Most force fields encode all of the relevant parameters to be used in distinct atom types, each associated with parameters for all parts of the force field, typically bond stretches, angle bends, torsions, and nonbonded terms accounting for van der Waals and electrostatic interactions. Much attention has been paid to the nonbonded parameters and their derivation, which are important in particular due to their governance of noncovalent interactions, such as protein-ligand binding. Parametrization involves adjusting the nonbonded parameters to minimize the error between simulation results and experimental properties, such as heats of vaporization and densities of neat liquids. In this setting, determining the best set of atom types is far from trivial, and the large number of parameters to be fit for the atom types in a typical force field can make it difficult to approach a true optimum. Here, we utilize a previously described Minimal Basis Iterative Stockholder (MBIS) method to carry out an atoms-in-molecules partitioning of electron densities. Information from these atomic densities is then mapped to Lennard-Jones parameters using a set of mapping parameters much smaller than the typical number of atom types in a force field. This approach is advantageous in two ways: it eliminates atom types by allowing each atom to have unique Lennard-Jones parameters, and it greatly reduces the number of parameters to be optimized. We show that this approach yields results comparable to those obtained with the typed GAFF 1.7 force field, even when trained on a relatively small amount of experimental data.
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Affiliation(s)
- Sophie M Kantonen
- Skaggs School of Pharmacy and Pharmaceutical Sciences , University of California San Diego , 9500 Gilman Drive , La Jolla , California 92093-0736 , United States
| | - Hari S Muddana
- Skaggs School of Pharmacy and Pharmaceutical Sciences , University of California San Diego , 9500 Gilman Drive , La Jolla , California 92093-0736 , United States
- OpenEye Scientific Software, Inc. , 9 Bisbee Court, Suite D , Santa Fe , New Mexico 87508 , United States
| | - Michael Schauperl
- Skaggs School of Pharmacy and Pharmaceutical Sciences , University of California San Diego , 9500 Gilman Drive , La Jolla , California 92093-0736 , United States
| | - Niel M Henriksen
- Skaggs School of Pharmacy and Pharmaceutical Sciences , University of California San Diego , 9500 Gilman Drive , La Jolla , California 92093-0736 , United States
- AtomWise, Inc. , 717 Market Street, Suite 800 , San Francisco , California 94103 , United States
| | - Lee-Ping Wang
- Department of Chemistry , University of California Davis , One Shields Avenue , Davis , California 95616 , United States
| | - Michael K Gilson
- Skaggs School of Pharmacy and Pharmaceutical Sciences , University of California San Diego , 9500 Gilman Drive , La Jolla , California 92093-0736 , United States
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Toyoda S, Miyagawa H, Kitamura K, Amisaki T, Hashimoto E, Ikeda H, Kusumi A, Miyakawa N. Development of MD Engine: High-speed accelerator with parallel processor design for molecular dynamics simulations. J Comput Chem 1999. [DOI: 10.1002/(sici)1096-987x(19990130)20:2<185::aid-jcc1>3.0.co;2-l] [Citation(s) in RCA: 56] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Komeiji Y, Uebayasi M, Takata R, Shimizu A, Itsukashi K, Taiji M. Fast and accurate molecular dynamics simulation of a protein using a special-purpose computer. J Comput Chem 1997. [DOI: 10.1002/(sici)1096-987x(199709)18:12<1546::aid-jcc11>3.0.co;2-i] [Citation(s) in RCA: 68] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Abstract
In the past years, much effort has been put on the development of new methodologies and algorithms for the prediction of protein secondary and tertiary structures from (sequence) data; this is reviewed in detail. New approaches for these predictions such as neural network methods, genetic algorithms, machine learning, and graph theoretical methods are discussed. Secondary structure prediction algorithms were improved mostly by considering families of related proteins; however, for the reliable tertiary structure modeling of proteins, knowledge-based techniques are still preferred. Methods and examples with more or less successful results are described. Also, programs and parameterizations for energy minimisations, molecular dynamics, and electrostatic interactions have been improved, especially with respect to their former limits of applicability. Other topics discussed in this review include the use of traditional and on-line databases, the docking problem and surface properties of biomolecules, packing of protein cores, de novo design and protein engineering, prediction of membrane protein structures, the verification and reliability of model structures, and progress made with currently available software and computer hardware. In summary, the prediction of the structure, function, and other properties of a protein is still possible only within limits, but these limits continue to be moved.
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Affiliation(s)
- G Böhm
- Institut für Biotechnologie, Martin-Luther-Universität Halle-Wittenberg, Germany
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Amisaki T, Fujiwara T, Kusumi A, Miyagawa H, Kitamura K. Error evaluation in the design of a special-purpose processor that calculates nonbonded forces in molecular dynamics simulations. J Comput Chem 1995. [DOI: 10.1002/jcc.540160906] [Citation(s) in RCA: 23] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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