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 |
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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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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.</description><identifier>ISSN: 1549-9618</identifier><identifier>EISSN: 1549-9626</identifier><identifier>DOI: 10.1021/acs.jctc.0c01286</identifier><identifier>PMID: 33769814</identifier><language>eng</language><publisher>United States: American Chemical Society</publisher><subject>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</subject><ispartof>Journal of chemical theory and computation, 2021-04, Vol.17 (4), p.2323-2341</ispartof><rights>2021 American Chemical Society</rights><rights>Copyright American Chemical Society Apr 13, 2021</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a495t-bc25454f47a5b3134555bc4a118fbea18d44e8d8116064f4fccc462d5b6f0bc63</citedby><cites>FETCH-LOGICAL-a495t-bc25454f47a5b3134555bc4a118fbea18d44e8d8116064f4fccc462d5b6f0bc63</cites><orcidid>0000-0003-1260-4592 ; 0000-0002-5613-1910 ; 0000-0001-5450-9230 ; 0000-0001-6615-9426 ; 0000-0003-3628-9347 ; 0000-0002-7251-0910</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://pubs.acs.org/doi/pdf/10.1021/acs.jctc.0c01286$$EPDF$$P50$$Gacs$$H</linktopdf><linktohtml>$$Uhttps://pubs.acs.org/doi/10.1021/acs.jctc.0c01286$$EHTML$$P50$$Gacs$$H</linktohtml><link.rule.ids>230,314,780,784,885,2765,27076,27924,27925,56738,56788</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33769814$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.science/hal-03183306$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Corrigan, Rae A</creatorcontrib><creatorcontrib>Qi, Guowei</creatorcontrib><creatorcontrib>Thiel, Andrew C</creatorcontrib><creatorcontrib>Lynn, Jack R</creatorcontrib><creatorcontrib>Walker, Brandon D</creatorcontrib><creatorcontrib>Casavant, Thomas L</creatorcontrib><creatorcontrib>Lagardere, Louis</creatorcontrib><creatorcontrib>Piquemal, Jean-Philip</creatorcontrib><creatorcontrib>Ponder, Jay W</creatorcontrib><creatorcontrib>Ren, Pengyu</creatorcontrib><creatorcontrib>Schnieders, Michael J</creatorcontrib><title>Implicit Solvents for the Polarizable Atomic Multipole AMOEBA Force Field</title><title>Journal of chemical theory and computation</title><addtitle>J. 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. 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.</description><subject>Amoeba</subject><subject>Approximation</subject><subject>Boltzmann transport equation</subject><subject>Cavitation</subject><subject>Chemical Sciences</subject><subject>Conductors</subject><subject>Domain decomposition methods</subject><subject>Electrostatics</subject><subject>Folding</subject><subject>Free energy</subject><subject>Ligands</subject><subject>Mathematical models</subject><subject>Models, Chemical</subject><subject>Molecular Mechanics</subject><subject>Multipoles</subject><subject>Nucleic acids</subject><subject>or physical chemistry</subject><subject>Proteins</subject><subject>Proteins - chemistry</subject><subject>Screening</subject><subject>Solvation</subject><subject>Solvents</subject><subject>Solvents - chemistry</subject><subject>Static Electricity</subject><subject>Theoretical and</subject><issn>1549-9618</issn><issn>1549-9626</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kc1rGzEQxUVoyVd7z6ks9NJA7Wr0Ze2l4Ia4MTik0PYstFptLaO1XGnXkPz10caOSQM9SYx-782MHkIXgMeACXzRJo1XpjNjbDAQKY7QKXBWjkpBxJvDHeQJOktphTGljNBjdELpRJQS2Cmaz9uNd8Z1xc_gt3bdpaIJseiWtvgRvI7uQVfeFtMutM4Ut73v3CYMhdu762_TYhaiscXMWV-_Q28b7ZN9vz_P0e_Z9a-rm9Hi7vv8aroYaVbyblQZwhlnDZtoXlGgjHNeGaYBZFNZDbJmzMpaAggsMtYYY5ggNa9Egysj6Dn6uvPd9FVra5NnjtqrTXStjvcqaKf-fVm7pfoTtkoCEUzIbHC5M1i-kt1MF2qoYQqSUiy2kNlP-2Yx_O1t6lTrkrHe67UNfVKEY0EmHMQw18dX6Cr0cZ2_IlMk787KyWCId5SJIaVom8MEgNWQqcqZqiFTtc80Sz68XPggeA4xA593wJP0uel__R4B-xar-A</recordid><startdate>20210413</startdate><enddate>20210413</enddate><creator>Corrigan, Rae A</creator><creator>Qi, Guowei</creator><creator>Thiel, Andrew C</creator><creator>Lynn, Jack R</creator><creator>Walker, Brandon D</creator><creator>Casavant, Thomas L</creator><creator>Lagardere, Louis</creator><creator>Piquemal, Jean-Philip</creator><creator>Ponder, Jay W</creator><creator>Ren, Pengyu</creator><creator>Schnieders, Michael J</creator><general>American Chemical Society</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SR</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope><scope>1XC</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-1260-4592</orcidid><orcidid>https://orcid.org/0000-0002-5613-1910</orcidid><orcidid>https://orcid.org/0000-0001-5450-9230</orcidid><orcidid>https://orcid.org/0000-0001-6615-9426</orcidid><orcidid>https://orcid.org/0000-0003-3628-9347</orcidid><orcidid>https://orcid.org/0000-0002-7251-0910</orcidid></search><sort><creationdate>20210413</creationdate><title>Implicit Solvents for the Polarizable Atomic Multipole AMOEBA Force Field</title><author>Corrigan, Rae A ; 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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. Overall, the emergence of performative implicit solvent models for polarizable force fields opens the door to their use for folding and design applications.</abstract><cop>United States</cop><pub>American Chemical Society</pub><pmid>33769814</pmid><doi>10.1021/acs.jctc.0c01286</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0003-1260-4592</orcidid><orcidid>https://orcid.org/0000-0002-5613-1910</orcidid><orcidid>https://orcid.org/0000-0001-5450-9230</orcidid><orcidid>https://orcid.org/0000-0001-6615-9426</orcidid><orcidid>https://orcid.org/0000-0003-3628-9347</orcidid><orcidid>https://orcid.org/0000-0002-7251-0910</orcidid><oa>free_for_read</oa></addata></record> |
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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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