GEMDOCK: A generic evolutionary method for molecular docking
We have developed an evolutionary approach for flexible ligand docking. This approval, GEMDOCK, uses a Generic Evolutionary Method for molecular DOCKing and an empirical scoring function. The former combines both discrete and continuous global search strategies with local search strategies to speed...
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Veröffentlicht in: | Proteins, structure, function, and bioinformatics structure, function, and bioinformatics, 2004-05, Vol.55 (2), p.288-304 |
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creator | Yang, Jinn-Moon Chen, Chun-Chen |
description | We have developed an evolutionary approach for flexible ligand docking. This approval, GEMDOCK, uses a Generic Evolutionary Method for molecular DOCKing and an empirical scoring function. The former combines both discrete and continuous global search strategies with local search strategies to speed up convergence, whereas the latter results in rapid recognition of potential ligands. GEMDOCK was tested on a diverse data set of 100 protein–ligand complexes from the Protein Data Bank. In 79% of these complexes, the docked lowest energy ligand structures had root‐mean‐square derivations (RMSDs) below 2.0 Å with respect to the corresponding crystal structures. The success rate increased to 85% if the structure water molecules were retained. We evaluated GEMDOCK on two cross‐docking experiments in which each ligand of a protein ensemble was docked into each protein of the ensemble. Seventy‐six percent of the docked structures had RMSDs below 2.0 Å when the ligands were docked into foreign structures. We analyzed and validated GEMDOCK with respect to various search spaces and scoring functions, and found that if the scoring function was perfect, then the predicted accuracy was also essentially perfect. This study suggests that GEMDOCK is a useful tool for molecular recognition and may be used to systematically evaluate and thus improve scoring functions. Proteins 2004. © 2004 Wiley‐Liss, Inc. |
doi_str_mv | 10.1002/prot.20035 |
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This approval, GEMDOCK, uses a Generic Evolutionary Method for molecular DOCKing and an empirical scoring function. The former combines both discrete and continuous global search strategies with local search strategies to speed up convergence, whereas the latter results in rapid recognition of potential ligands. GEMDOCK was tested on a diverse data set of 100 protein–ligand complexes from the Protein Data Bank. In 79% of these complexes, the docked lowest energy ligand structures had root‐mean‐square derivations (RMSDs) below 2.0 Å with respect to the corresponding crystal structures. The success rate increased to 85% if the structure water molecules were retained. We evaluated GEMDOCK on two cross‐docking experiments in which each ligand of a protein ensemble was docked into each protein of the ensemble. Seventy‐six percent of the docked structures had RMSDs below 2.0 Å when the ligands were docked into foreign structures. We analyzed and validated GEMDOCK with respect to various search spaces and scoring functions, and found that if the scoring function was perfect, then the predicted accuracy was also essentially perfect. This study suggests that GEMDOCK is a useful tool for molecular recognition and may be used to systematically evaluate and thus improve scoring functions. Proteins 2004. © 2004 Wiley‐Liss, Inc.</description><identifier>ISSN: 0887-3585</identifier><identifier>EISSN: 1097-0134</identifier><identifier>DOI: 10.1002/prot.20035</identifier><identifier>PMID: 15048822</identifier><language>eng</language><publisher>Hoboken: Wiley Subscription Services, Inc., A Wiley Company</publisher><subject>Algorithms ; Binding Sites ; Computational Biology - methods ; cross-docking ; Databases, Protein ; Evolution, Molecular ; evolutionary algorithm ; HIV Protease - metabolism ; hybrid docking ; Hydrogen Bonding ; Immunoglobulin Fab Fragments - metabolism ; Internet ; Ligands ; Models, Molecular ; molecular recognition ; Mutation - genetics ; Probability ; Protein Binding ; protein-ligand docking ; Proteins - genetics ; Proteins - metabolism ; Recombination, Genetic ; Reproducibility of Results ; Sensitivity and Specificity ; Software ; Static Electricity ; structure-based drug design ; Thermodynamics</subject><ispartof>Proteins, structure, function, and bioinformatics, 2004-05, Vol.55 (2), p.288-304</ispartof><rights>Copyright © 2004 Wiley‐Liss, Inc.</rights><rights>Copyright 2004 Wiley-Liss, Inc.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4295-94f10c4cfe3d834bef658ee41279328798f9cbde7511e1fce446cd4166491a0e3</citedby><cites>FETCH-LOGICAL-c4295-94f10c4cfe3d834bef658ee41279328798f9cbde7511e1fce446cd4166491a0e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fprot.20035$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fprot.20035$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/15048822$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yang, Jinn-Moon</creatorcontrib><creatorcontrib>Chen, Chun-Chen</creatorcontrib><title>GEMDOCK: A generic evolutionary method for molecular docking</title><title>Proteins, structure, function, and bioinformatics</title><addtitle>Proteins</addtitle><description>We have developed an evolutionary approach for flexible ligand docking. This approval, GEMDOCK, uses a Generic Evolutionary Method for molecular DOCKing and an empirical scoring function. The former combines both discrete and continuous global search strategies with local search strategies to speed up convergence, whereas the latter results in rapid recognition of potential ligands. GEMDOCK was tested on a diverse data set of 100 protein–ligand complexes from the Protein Data Bank. In 79% of these complexes, the docked lowest energy ligand structures had root‐mean‐square derivations (RMSDs) below 2.0 Å with respect to the corresponding crystal structures. The success rate increased to 85% if the structure water molecules were retained. We evaluated GEMDOCK on two cross‐docking experiments in which each ligand of a protein ensemble was docked into each protein of the ensemble. Seventy‐six percent of the docked structures had RMSDs below 2.0 Å when the ligands were docked into foreign structures. We analyzed and validated GEMDOCK with respect to various search spaces and scoring functions, and found that if the scoring function was perfect, then the predicted accuracy was also essentially perfect. This study suggests that GEMDOCK is a useful tool for molecular recognition and may be used to systematically evaluate and thus improve scoring functions. Proteins 2004. © 2004 Wiley‐Liss, Inc.</description><subject>Algorithms</subject><subject>Binding Sites</subject><subject>Computational Biology - methods</subject><subject>cross-docking</subject><subject>Databases, Protein</subject><subject>Evolution, Molecular</subject><subject>evolutionary algorithm</subject><subject>HIV Protease - metabolism</subject><subject>hybrid docking</subject><subject>Hydrogen Bonding</subject><subject>Immunoglobulin Fab Fragments - metabolism</subject><subject>Internet</subject><subject>Ligands</subject><subject>Models, Molecular</subject><subject>molecular recognition</subject><subject>Mutation - genetics</subject><subject>Probability</subject><subject>Protein Binding</subject><subject>protein-ligand docking</subject><subject>Proteins - genetics</subject><subject>Proteins - metabolism</subject><subject>Recombination, Genetic</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</subject><subject>Software</subject><subject>Static Electricity</subject><subject>structure-based drug design</subject><subject>Thermodynamics</subject><issn>0887-3585</issn><issn>1097-0134</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kM1OwkAURidGI4hufADTlQuT4vy1MzVuCCAaEYzBuJyU6S1W2w7OtCpvbxHUnau7Ofck30HomOAuwZieL62puhRjFuygNsGR8DFhfBe1sZTCZ4EMWujAuReMcRixcB-1SIC5lJS20eVoeDeY9m8vvJ63gBJspj14N3ldZaaM7coroHo2iZca6xUmB13nsfUSo1-zcnGI9tI4d3C0vR30eDWc9a_98XR00--Nfc1pFPgRTwnWXKfAEsn4HNIwkACcUBExKkUk00jPExABIUBSDZyHOuEkDHlEYgysg0433mbpWw2uUkXmNOR5XIKpnRJESCwYb8CzDaitcc5CqpY2K5oZimC1bqXWrdR3qwY-2VrreQHJH7qN0wBkA3xkOaz-Uan7h-nsR-pvfjJXwefvT2xfVSiYCNTTZKTogDI-GYzUmH0B2neCAw</recordid><startdate>20040501</startdate><enddate>20040501</enddate><creator>Yang, Jinn-Moon</creator><creator>Chen, Chun-Chen</creator><general>Wiley Subscription Services, Inc., A Wiley Company</general><scope>BSCLL</scope><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>20040501</creationdate><title>GEMDOCK: A generic evolutionary method for molecular docking</title><author>Yang, Jinn-Moon ; Chen, Chun-Chen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4295-94f10c4cfe3d834bef658ee41279328798f9cbde7511e1fce446cd4166491a0e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Algorithms</topic><topic>Binding Sites</topic><topic>Computational Biology - methods</topic><topic>cross-docking</topic><topic>Databases, Protein</topic><topic>Evolution, Molecular</topic><topic>evolutionary algorithm</topic><topic>HIV Protease - metabolism</topic><topic>hybrid docking</topic><topic>Hydrogen Bonding</topic><topic>Immunoglobulin Fab Fragments - metabolism</topic><topic>Internet</topic><topic>Ligands</topic><topic>Models, Molecular</topic><topic>molecular recognition</topic><topic>Mutation - genetics</topic><topic>Probability</topic><topic>Protein Binding</topic><topic>protein-ligand docking</topic><topic>Proteins - genetics</topic><topic>Proteins - metabolism</topic><topic>Recombination, Genetic</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><topic>Software</topic><topic>Static Electricity</topic><topic>structure-based drug design</topic><topic>Thermodynamics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yang, Jinn-Moon</creatorcontrib><creatorcontrib>Chen, Chun-Chen</creatorcontrib><collection>Istex</collection><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>Proteins, structure, function, and bioinformatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yang, Jinn-Moon</au><au>Chen, Chun-Chen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>GEMDOCK: A generic evolutionary method for molecular docking</atitle><jtitle>Proteins, structure, function, and bioinformatics</jtitle><addtitle>Proteins</addtitle><date>2004-05-01</date><risdate>2004</risdate><volume>55</volume><issue>2</issue><spage>288</spage><epage>304</epage><pages>288-304</pages><issn>0887-3585</issn><eissn>1097-0134</eissn><abstract>We have developed an evolutionary approach for flexible ligand docking. This approval, GEMDOCK, uses a Generic Evolutionary Method for molecular DOCKing and an empirical scoring function. The former combines both discrete and continuous global search strategies with local search strategies to speed up convergence, whereas the latter results in rapid recognition of potential ligands. GEMDOCK was tested on a diverse data set of 100 protein–ligand complexes from the Protein Data Bank. In 79% of these complexes, the docked lowest energy ligand structures had root‐mean‐square derivations (RMSDs) below 2.0 Å with respect to the corresponding crystal structures. The success rate increased to 85% if the structure water molecules were retained. We evaluated GEMDOCK on two cross‐docking experiments in which each ligand of a protein ensemble was docked into each protein of the ensemble. Seventy‐six percent of the docked structures had RMSDs below 2.0 Å when the ligands were docked into foreign structures. We analyzed and validated GEMDOCK with respect to various search spaces and scoring functions, and found that if the scoring function was perfect, then the predicted accuracy was also essentially perfect. This study suggests that GEMDOCK is a useful tool for molecular recognition and may be used to systematically evaluate and thus improve scoring functions. Proteins 2004. © 2004 Wiley‐Liss, Inc.</abstract><cop>Hoboken</cop><pub>Wiley Subscription Services, Inc., A Wiley Company</pub><pmid>15048822</pmid><doi>10.1002/prot.20035</doi><tpages>17</tpages></addata></record> |
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subjects | Algorithms Binding Sites Computational Biology - methods cross-docking Databases, Protein Evolution, Molecular evolutionary algorithm HIV Protease - metabolism hybrid docking Hydrogen Bonding Immunoglobulin Fab Fragments - metabolism Internet Ligands Models, Molecular molecular recognition Mutation - genetics Probability Protein Binding protein-ligand docking Proteins - genetics Proteins - metabolism Recombination, Genetic Reproducibility of Results Sensitivity and Specificity Software Static Electricity structure-based drug design Thermodynamics |
title | GEMDOCK: A generic evolutionary method for molecular docking |
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