Implicit Solvents for the Polarizable Atomic Multipole AMOEBA Force Field

Computational protein design, ab initio protein/RNA folding, and protein–ligand screening can be too computationally demanding for explicit treatment of solvent. For these applications, implicit solvent offers a compelling alternative, which we describe here for the polarizable atomic multipole AMOE...

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Veröffentlicht in:Journal of chemical theory and computation 2021-04, Vol.17 (4), p.2323-2341
Hauptverfasser: Corrigan, Rae A, Qi, Guowei, Thiel, Andrew C, Lynn, Jack R, Walker, Brandon D, Casavant, Thomas L, Lagardere, Louis, Piquemal, Jean-Philip, Ponder, Jay W, Ren, Pengyu, Schnieders, Michael J
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container_issue 4
container_start_page 2323
container_title Journal of chemical theory and computation
container_volume 17
creator Corrigan, Rae A
Qi, Guowei
Thiel, Andrew C
Lynn, Jack R
Walker, Brandon D
Casavant, Thomas L
Lagardere, Louis
Piquemal, Jean-Philip
Ponder, Jay W
Ren, Pengyu
Schnieders, Michael J
description Computational protein design, ab initio protein/RNA folding, and protein–ligand screening can be too computationally demanding for explicit treatment of solvent. For these applications, implicit solvent offers a compelling alternative, which we describe here for the polarizable atomic multipole AMOEBA force field based on three treatments of continuum electrostatics: numerical solutions to the nonlinear and linearized versions of the Poisson–Boltzmann equation (PBE), the domain-decomposition conductor-like screening model (ddCOSMO) approximation to the PBE, and the analytic generalized Kirkwood (GK) approximation. The continuum electrostatics models are combined with a nonpolar estimator based on novel cavitation and dispersion terms. Electrostatic model parameters are numerically optimized using a least-squares style target function based on a library of 103 small-molecule solvation free energy differences. Mean signed errors for the adaptive Poisson–Boltzmann solver (APBS), ddCOSMO, and GK models are 0.05, 0.00, and 0.00 kcal/mol, respectively, while the mean unsigned errors are 0.70, 0.63, and 0.58 kcal/mol, respectively. Validation of the electrostatic response of the resulting implicit solvents, which are available in the Tinker (or Tinker-HP), OpenMM, and Force Field X software packages, is based on comparisons to explicit solvent simulations for a series of proteins and nucleic acids. Overall, the emergence of performative implicit solvent models for polarizable force fields opens the door to their use for folding and design applications.
doi_str_mv 10.1021/acs.jctc.0c01286
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Chem. Theory Comput</addtitle><description>Computational protein design, ab initio protein/RNA folding, and protein–ligand screening can be too computationally demanding for explicit treatment of solvent. For these applications, implicit solvent offers a compelling alternative, which we describe here for the polarizable atomic multipole AMOEBA force field based on three treatments of continuum electrostatics: numerical solutions to the nonlinear and linearized versions of the Poisson–Boltzmann equation (PBE), the domain-decomposition conductor-like screening model (ddCOSMO) approximation to the PBE, and the analytic generalized Kirkwood (GK) approximation. The continuum electrostatics models are combined with a nonpolar estimator based on novel cavitation and dispersion terms. Electrostatic model parameters are numerically optimized using a least-squares style target function based on a library of 103 small-molecule solvation free energy differences. 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Chem. Theory Comput</addtitle><date>2021-04-13</date><risdate>2021</risdate><volume>17</volume><issue>4</issue><spage>2323</spage><epage>2341</epage><pages>2323-2341</pages><issn>1549-9618</issn><eissn>1549-9626</eissn><abstract>Computational protein design, ab initio protein/RNA folding, and protein–ligand screening can be too computationally demanding for explicit treatment of solvent. For these applications, implicit solvent offers a compelling alternative, which we describe here for the polarizable atomic multipole AMOEBA force field based on three treatments of continuum electrostatics: numerical solutions to the nonlinear and linearized versions of the Poisson–Boltzmann equation (PBE), the domain-decomposition conductor-like screening model (ddCOSMO) approximation to the PBE, and the analytic generalized Kirkwood (GK) approximation. The continuum electrostatics models are combined with a nonpolar estimator based on novel cavitation and dispersion terms. Electrostatic model parameters are numerically optimized using a least-squares style target function based on a library of 103 small-molecule solvation free energy differences. Mean signed errors for the adaptive Poisson–Boltzmann solver (APBS), ddCOSMO, and GK models are 0.05, 0.00, and 0.00 kcal/mol, respectively, while the mean unsigned errors are 0.70, 0.63, and 0.58 kcal/mol, respectively. Validation of the electrostatic response of the resulting implicit solvents, which are available in the Tinker (or Tinker-HP), OpenMM, and Force Field X software packages, is based on comparisons to explicit solvent simulations for a series of proteins and nucleic acids. 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subjects Amoeba
Approximation
Boltzmann transport equation
Cavitation
Chemical Sciences
Conductors
Domain decomposition methods
Electrostatics
Folding
Free energy
Ligands
Mathematical models
Models, Chemical
Molecular Mechanics
Multipoles
Nucleic acids
or physical chemistry
Proteins
Proteins - chemistry
Screening
Solvation
Solvents
Solvents - chemistry
Static Electricity
Theoretical and
title Implicit Solvents for the Polarizable Atomic Multipole AMOEBA Force Field
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