Accelerated molecular dynamics: a promising and efficient simulation method for biomolecules
Many interesting dynamic properties of biological molecules cannot be simulated directly using molecular dynamics because of nanosecond time scale limitations. These systems are trapped in potential energy minima with high free energy barriers for large numbers of computational steps. The dynamic ev...
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Veröffentlicht in: | The Journal of chemical physics 2004-06, Vol.120 (24), p.11919-11929 |
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creator | Hamelberg, Donald Mongan, John McCammon, J Andrew |
description | Many interesting dynamic properties of biological molecules cannot be simulated directly using molecular dynamics because of nanosecond time scale limitations. These systems are trapped in potential energy minima with high free energy barriers for large numbers of computational steps. The dynamic evolution of many molecular systems occurs through a series of rare events as the system moves from one potential energy basin to another. Therefore, we have proposed a robust bias potential function that can be used in an efficient accelerated molecular dynamics approach to simulate the transition of high energy barriers without any advance knowledge of the location of either the potential energy wells or saddle points. In this method, the potential energy landscape is altered by adding a bias potential to the true potential such that the escape rates from potential wells are enhanced, which accelerates and extends the time scale in molecular dynamics simulations. Our definition of the bias potential echoes the underlying shape of the potential energy landscape on the modified surface, thus allowing for the potential energy minima to be well defined, and hence properly sampled during the simulation. We have shown that our approach, which can be extended to biomolecules, samples the conformational space more efficiently than normal molecular dynamics simulations, and converges to the correct canonical distribution. |
doi_str_mv | 10.1063/1.1755656 |
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These systems are trapped in potential energy minima with high free energy barriers for large numbers of computational steps. The dynamic evolution of many molecular systems occurs through a series of rare events as the system moves from one potential energy basin to another. Therefore, we have proposed a robust bias potential function that can be used in an efficient accelerated molecular dynamics approach to simulate the transition of high energy barriers without any advance knowledge of the location of either the potential energy wells or saddle points. In this method, the potential energy landscape is altered by adding a bias potential to the true potential such that the escape rates from potential wells are enhanced, which accelerates and extends the time scale in molecular dynamics simulations. Our definition of the bias potential echoes the underlying shape of the potential energy landscape on the modified surface, thus allowing for the potential energy minima to be well defined, and hence properly sampled during the simulation. We have shown that our approach, which can be extended to biomolecules, samples the conformational space more efficiently than normal molecular dynamics simulations, and converges to the correct canonical distribution.</description><identifier>ISSN: 0021-9606</identifier><identifier>EISSN: 1089-7690</identifier><identifier>DOI: 10.1063/1.1755656</identifier><identifier>PMID: 15268227</identifier><language>eng</language><publisher>United States</publisher><subject>Binding Sites ; Computational Biology ; Computer Simulation ; Energy Transfer ; Models, Biological ; Thermodynamics</subject><ispartof>The Journal of chemical physics, 2004-06, Vol.120 (24), p.11919-11929</ispartof><rights>(c)2004 American Institute of Physics.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c347t-953baf1799e7c34162771f5fae00a7dec2a045b16e427ecf6e772d04cec312123</citedby><cites>FETCH-LOGICAL-c347t-953baf1799e7c34162771f5fae00a7dec2a045b16e427ecf6e772d04cec312123</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/15268227$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hamelberg, Donald</creatorcontrib><creatorcontrib>Mongan, John</creatorcontrib><creatorcontrib>McCammon, J Andrew</creatorcontrib><title>Accelerated molecular dynamics: a promising and efficient simulation method for biomolecules</title><title>The Journal of chemical physics</title><addtitle>J Chem Phys</addtitle><description>Many interesting dynamic properties of biological molecules cannot be simulated directly using molecular dynamics because of nanosecond time scale limitations. These systems are trapped in potential energy minima with high free energy barriers for large numbers of computational steps. The dynamic evolution of many molecular systems occurs through a series of rare events as the system moves from one potential energy basin to another. Therefore, we have proposed a robust bias potential function that can be used in an efficient accelerated molecular dynamics approach to simulate the transition of high energy barriers without any advance knowledge of the location of either the potential energy wells or saddle points. In this method, the potential energy landscape is altered by adding a bias potential to the true potential such that the escape rates from potential wells are enhanced, which accelerates and extends the time scale in molecular dynamics simulations. Our definition of the bias potential echoes the underlying shape of the potential energy landscape on the modified surface, thus allowing for the potential energy minima to be well defined, and hence properly sampled during the simulation. We have shown that our approach, which can be extended to biomolecules, samples the conformational space more efficiently than normal molecular dynamics simulations, and converges to the correct canonical distribution.</description><subject>Binding Sites</subject><subject>Computational Biology</subject><subject>Computer Simulation</subject><subject>Energy Transfer</subject><subject>Models, Biological</subject><subject>Thermodynamics</subject><issn>0021-9606</issn><issn>1089-7690</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpFkE1LxDAURYMozji68A9IVoKLjnlpmzd1Nwx-wYAb3QklTV800jZj0i7m309lCq4eXA6H-y5j1yCWIFR6D0vAPFe5OmFzEKsiQVWIUzYXQkJSKKFm7CLGHyEEoMzO2QxyqVZS4px9ro2hhoLuqeatb8gMjQ683ne6dSY-cM13wbcuuu6L667mZK0zjrqeR9eObO98x1vqv33NrQ-8cn7SULxkZ1Y3ka6mu2AfT4_vm5dk-_b8ullvE5Nm2CdFnlbaAhYF4ZiAkohgc6tJCI01GalFllegKJNIxipClLXIDJkUJMh0wW6P3rHq70CxL8fC41uN7sgPsVQKU1XgagTvjqAJPsZAttwF1-qwL0GUf1OWUE5TjuzNJB2qlup_ctouPQDyDm7v</recordid><startdate>20040622</startdate><enddate>20040622</enddate><creator>Hamelberg, Donald</creator><creator>Mongan, John</creator><creator>McCammon, J Andrew</creator><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>7X8</scope></search><sort><creationdate>20040622</creationdate><title>Accelerated molecular dynamics: a promising and efficient simulation method for biomolecules</title><author>Hamelberg, Donald ; Mongan, John ; McCammon, J Andrew</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c347t-953baf1799e7c34162771f5fae00a7dec2a045b16e427ecf6e772d04cec312123</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Binding Sites</topic><topic>Computational Biology</topic><topic>Computer Simulation</topic><topic>Energy Transfer</topic><topic>Models, Biological</topic><topic>Thermodynamics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hamelberg, Donald</creatorcontrib><creatorcontrib>Mongan, John</creatorcontrib><creatorcontrib>McCammon, J Andrew</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>The Journal of chemical physics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hamelberg, Donald</au><au>Mongan, John</au><au>McCammon, J Andrew</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Accelerated molecular dynamics: a promising and efficient simulation method for biomolecules</atitle><jtitle>The Journal of chemical physics</jtitle><addtitle>J Chem Phys</addtitle><date>2004-06-22</date><risdate>2004</risdate><volume>120</volume><issue>24</issue><spage>11919</spage><epage>11929</epage><pages>11919-11929</pages><issn>0021-9606</issn><eissn>1089-7690</eissn><abstract>Many interesting dynamic properties of biological molecules cannot be simulated directly using molecular dynamics because of nanosecond time scale limitations. These systems are trapped in potential energy minima with high free energy barriers for large numbers of computational steps. The dynamic evolution of many molecular systems occurs through a series of rare events as the system moves from one potential energy basin to another. Therefore, we have proposed a robust bias potential function that can be used in an efficient accelerated molecular dynamics approach to simulate the transition of high energy barriers without any advance knowledge of the location of either the potential energy wells or saddle points. In this method, the potential energy landscape is altered by adding a bias potential to the true potential such that the escape rates from potential wells are enhanced, which accelerates and extends the time scale in molecular dynamics simulations. Our definition of the bias potential echoes the underlying shape of the potential energy landscape on the modified surface, thus allowing for the potential energy minima to be well defined, and hence properly sampled during the simulation. We have shown that our approach, which can be extended to biomolecules, samples the conformational space more efficiently than normal molecular dynamics simulations, and converges to the correct canonical distribution.</abstract><cop>United States</cop><pmid>15268227</pmid><doi>10.1063/1.1755656</doi><tpages>11</tpages></addata></record> |
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subjects | Binding Sites Computational Biology Computer Simulation Energy Transfer Models, Biological Thermodynamics |
title | Accelerated molecular dynamics: a promising and efficient simulation method for biomolecules |
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