Multiscale Estimation of Binding Kinetics Using Brownian Dynamics, Molecular Dynamics and Milestoning
The kinetic rate constants of binding were estimated for four biochemically relevant molecular systems by a method that uses milestoning theory to combine Brownian dynamics simulations with more detailed molecular dynamics simulations. The rate constants found using this method agreed well with expe...
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description | The kinetic rate constants of binding were estimated for four biochemically relevant molecular systems by a method that uses milestoning theory to combine Brownian dynamics simulations with more detailed molecular dynamics simulations. The rate constants found using this method agreed well with experimentally and theoretically obtained values. We predicted the association rate of a small charged molecule toward both a charged and an uncharged spherical receptor and verified the estimated value with Smoluchowski theory. We also calculated the kon rate constant for superoxide dismutase with its natural substrate, O2-, in a validation of a previous experiment using similar methods but with a number of important improvements. We also calculated the kon for a new system: the N-terminal domain of Troponin C with its natural substrate Ca2+. The kon calculated for the latter two systems closely resemble experimentally obtained values. This novel multiscale approach is computationally cheaper and more parallelizable when compared to other methods of similar accuracy. We anticipate that this methodology will be useful for predicting kinetic rate constants and for understanding the process of binding between a small molecule and a protein receptor. |
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The rate constants found using this method agreed well with experimentally and theoretically obtained values. We predicted the association rate of a small charged molecule toward both a charged and an uncharged spherical receptor and verified the estimated value with Smoluchowski theory. We also calculated the kon rate constant for superoxide dismutase with its natural substrate, O2-, in a validation of a previous experiment using similar methods but with a number of important improvements. We also calculated the kon for a new system: the N-terminal domain of Troponin C with its natural substrate Ca2+. The kon calculated for the latter two systems closely resemble experimentally obtained values. This novel multiscale approach is computationally cheaper and more parallelizable when compared to other methods of similar accuracy. We anticipate that this methodology will be useful for predicting kinetic rate constants and for understanding the process of binding between a small molecule and a protein receptor.</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1004381</identifier><identifier>PMID: 26505480</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Accuracy ; Algorithms ; Analysis ; Binding Sites ; Chemical properties ; Chemical reaction, Rate of ; Diffusion ; Funding ; Kinetics ; Ligands ; Methods ; Models, Chemical ; Models, Statistical ; Molecular Dynamics Simulation ; Protein Binding ; Protein Conformation ; Proteins ; Proteins - chemistry ; Proteins - ultrastructure ; R&D ; Research & development ; Scholarships & fellowships ; Solvents ; Supercomputers ; Superoxide</subject><ispartof>PLoS computational biology, 2015-10, Vol.11 (10), p.e1004381-e1004381</ispartof><rights>COPYRIGHT 2015 Public Library of Science</rights><rights>2015 Votapka, Amaro 2015 Votapka, Amaro</rights><rights>2015 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Votapka LW, Amaro RE (2015) Multiscale Estimation of Binding Kinetics Using Brownian Dynamics, Molecular Dynamics and Milestoning. 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The rate constants found using this method agreed well with experimentally and theoretically obtained values. We predicted the association rate of a small charged molecule toward both a charged and an uncharged spherical receptor and verified the estimated value with Smoluchowski theory. We also calculated the kon rate constant for superoxide dismutase with its natural substrate, O2-, in a validation of a previous experiment using similar methods but with a number of important improvements. We also calculated the kon for a new system: the N-terminal domain of Troponin C with its natural substrate Ca2+. The kon calculated for the latter two systems closely resemble experimentally obtained values. This novel multiscale approach is computationally cheaper and more parallelizable when compared to other methods of similar accuracy. We anticipate that this methodology will be useful for predicting kinetic rate constants and for understanding the process of binding between a small molecule and a protein receptor.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Analysis</subject><subject>Binding Sites</subject><subject>Chemical properties</subject><subject>Chemical reaction, Rate of</subject><subject>Diffusion</subject><subject>Funding</subject><subject>Kinetics</subject><subject>Ligands</subject><subject>Methods</subject><subject>Models, Chemical</subject><subject>Models, Statistical</subject><subject>Molecular Dynamics Simulation</subject><subject>Protein Binding</subject><subject>Protein Conformation</subject><subject>Proteins</subject><subject>Proteins - chemistry</subject><subject>Proteins - ultrastructure</subject><subject>R&D</subject><subject>Research & development</subject><subject>Scholarships & fellowships</subject><subject>Solvents</subject><subject>Supercomputers</subject><subject>Superoxide</subject><issn>1553-7358</issn><issn>1553-734X</issn><issn>1553-7358</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>DOA</sourceid><recordid>eNqVUk1vEzEQXSEQLYV_gGCPIJHgb3svldpSIKIBCejZ8u6OgyPHDvZuS_89Dkmj5oh88Hj83vPM81TVS4ymmEr8fhnHFIyfrrvWTTFCjCr8qDrGnNOJpFw9fhAfVc9yXiJUwkY8rY6I4IgzhY4rmI9-cLkzHurLPLiVGVwMdbT1uQu9C4v6iwswuC7X13lzPE_xNjgT6g93waxK_l09jx660Zu0z9Um9PXcechDDIX1vHpijc_wYrefVNcfL39efJ5cffs0uzi7mnRC4mHCGZNYqI7YFqRoEW9Iw1FjpABllRWKIowAWda3hFLCgAvMrbEM44a3JXdSvd7qrn3MeudQ1lhSygQRCBfEbIvoo1nqdSoNpzsdjdP_EjEttEmlXQ-aSMFUg7BsGDBpiAKquJA9aY1QrIOidbp7bWxX0HcQhmT8gejhTXC_9CLe6FILk0QVgTc7gRR_j8UsvSpfAd6bAHHc1E0U4UqSpkCnW-ii_JR2wcai2JXVQzE8BrDFbX3GSp-qIXij_faAUDAD_BkWZsxZz358_w_s10Ms22K7FHNOYPf9YqQ3g3lvu94Mpt4NZqG9eujVnnQ_ifQvlWXfDA</recordid><startdate>20151001</startdate><enddate>20151001</enddate><creator>Votapka, Lane W</creator><creator>Amaro, Rommie E</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</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>ISN</scope><scope>ISR</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20151001</creationdate><title>Multiscale Estimation of Binding Kinetics Using Brownian Dynamics, Molecular Dynamics and Milestoning</title><author>Votapka, Lane W ; Amaro, Rommie E</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c671t-5447168c2fbe76b05929509a76e8f8f683010e0f4db23324e5615faf41195bb23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>Analysis</topic><topic>Binding Sites</topic><topic>Chemical properties</topic><topic>Chemical reaction, Rate of</topic><topic>Diffusion</topic><topic>Funding</topic><topic>Kinetics</topic><topic>Ligands</topic><topic>Methods</topic><topic>Models, Chemical</topic><topic>Models, Statistical</topic><topic>Molecular Dynamics Simulation</topic><topic>Protein Binding</topic><topic>Protein Conformation</topic><topic>Proteins</topic><topic>Proteins - chemistry</topic><topic>Proteins - ultrastructure</topic><topic>R&D</topic><topic>Research & development</topic><topic>Scholarships & fellowships</topic><topic>Solvents</topic><topic>Supercomputers</topic><topic>Superoxide</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Votapka, Lane W</creatorcontrib><creatorcontrib>Amaro, Rommie E</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Canada</collection><collection>Gale In Context: Science</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ, Directory of Open Access Journals</collection><jtitle>PLoS computational biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Votapka, Lane W</au><au>Amaro, Rommie E</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multiscale Estimation of Binding Kinetics Using Brownian Dynamics, Molecular Dynamics and Milestoning</atitle><jtitle>PLoS computational biology</jtitle><addtitle>PLoS Comput Biol</addtitle><date>2015-10-01</date><risdate>2015</risdate><volume>11</volume><issue>10</issue><spage>e1004381</spage><epage>e1004381</epage><pages>e1004381-e1004381</pages><issn>1553-7358</issn><issn>1553-734X</issn><eissn>1553-7358</eissn><abstract>The kinetic rate constants of binding were estimated for four biochemically relevant molecular systems by a method that uses milestoning theory to combine Brownian dynamics simulations with more detailed molecular dynamics simulations. The rate constants found using this method agreed well with experimentally and theoretically obtained values. We predicted the association rate of a small charged molecule toward both a charged and an uncharged spherical receptor and verified the estimated value with Smoluchowski theory. We also calculated the kon rate constant for superoxide dismutase with its natural substrate, O2-, in a validation of a previous experiment using similar methods but with a number of important improvements. We also calculated the kon for a new system: the N-terminal domain of Troponin C with its natural substrate Ca2+. The kon calculated for the latter two systems closely resemble experimentally obtained values. This novel multiscale approach is computationally cheaper and more parallelizable when compared to other methods of similar accuracy. We anticipate that this methodology will be useful for predicting kinetic rate constants and for understanding the process of binding between a small molecule and a protein receptor.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>26505480</pmid><doi>10.1371/journal.pcbi.1004381</doi><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy Algorithms Analysis Binding Sites Chemical properties Chemical reaction, Rate of Diffusion Funding Kinetics Ligands Methods Models, Chemical Models, Statistical Molecular Dynamics Simulation Protein Binding Protein Conformation Proteins Proteins - chemistry Proteins - ultrastructure R&D Research & development Scholarships & fellowships Solvents Supercomputers Superoxide |
title | Multiscale Estimation of Binding Kinetics Using Brownian Dynamics, Molecular Dynamics and Milestoning |
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