MIB: Metal Ion-Binding Site Prediction and Docking Server
The structure of a protein determines its biological function(s) and its interactions with other factors; the binding regions tend to be conserved in sequence and structure, and the interacting residues involved are usually in close 3D space. The Protein Data Bank currently contains more than 110 00...
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Veröffentlicht in: | Journal of chemical information and modeling 2016-12, Vol.56 (12), p.2287-2291 |
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creator | Lin, Yu-Feng Cheng, Chih-Wen Shih, Chung-Shiuan Hwang, Jenn-Kang Yu, Chin-Sheng Lu, Chih-Hao |
description | The structure of a protein determines its biological function(s) and its interactions with other factors; the binding regions tend to be conserved in sequence and structure, and the interacting residues involved are usually in close 3D space. The Protein Data Bank currently contains more than 110 000 protein structures, approximately one-third of which contain metal ions. Identifying and characterizing metal ion-binding sites is thus essential for investigating a protein’s function(s) and interactions. However, experimental approaches are time-consuming and costly. The web server reported here was built to predict metal ion-binding residues and to generate the predicted metal ion-bound 3D structure. Binding templates have been constructed for regions that bind 12 types of metal ion-binding residues have been used to construct binding templates. The templates include residues within 3.5 Å of the metal ion, and the fragment transformation method was used for structural comparison between query proteins and templates without any data training. Through the adjustment of scoring functions, which are based on the similarity of structure and binding residues. Twelve kinds of metal ions (Ca2+, Cu2+, Fe3+, Mg2+, Mn2+, Zn2+, Cd2+, Fe2+, Ni2+, Hg2+, Co2+, and Cu+) binding residues prediction are supported. MIB also provides the metal ions docking after prediction. The MIB server is available at http://bioinfo.cmu.edu.tw/MIB/. |
doi_str_mv | 10.1021/acs.jcim.6b00407 |
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The Protein Data Bank currently contains more than 110 000 protein structures, approximately one-third of which contain metal ions. Identifying and characterizing metal ion-binding sites is thus essential for investigating a protein’s function(s) and interactions. However, experimental approaches are time-consuming and costly. The web server reported here was built to predict metal ion-binding residues and to generate the predicted metal ion-bound 3D structure. Binding templates have been constructed for regions that bind 12 types of metal ion-binding residues have been used to construct binding templates. The templates include residues within 3.5 Å of the metal ion, and the fragment transformation method was used for structural comparison between query proteins and templates without any data training. Through the adjustment of scoring functions, which are based on the similarity of structure and binding residues. Twelve kinds of metal ions (Ca2+, Cu2+, Fe3+, Mg2+, Mn2+, Zn2+, Cd2+, Fe2+, Ni2+, Hg2+, Co2+, and Cu+) binding residues prediction are supported. MIB also provides the metal ions docking after prediction. The MIB server is available at http://bioinfo.cmu.edu.tw/MIB/.</description><identifier>ISSN: 1549-9596</identifier><identifier>EISSN: 1549-960X</identifier><identifier>DOI: 10.1021/acs.jcim.6b00407</identifier><identifier>PMID: 27976886</identifier><language>eng</language><publisher>United States: American Chemical Society</publisher><subject>Binding Sites ; Cations - metabolism ; Databases, Protein ; Internet ; Ions ; Metals ; Metals - metabolism ; Molecular Docking Simulation ; Protein Conformation ; Proteins ; Proteins - chemistry ; Proteins - metabolism ; Software</subject><ispartof>Journal of chemical information and modeling, 2016-12, Vol.56 (12), p.2287-2291</ispartof><rights>Copyright © 2016 American Chemical Society</rights><rights>Copyright American Chemical Society Dec 27, 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a3217-c72a4448da01502968f7fdfb7f23f0139f17553c9f292a0c5d13fa47c7aa1f7a3</citedby><cites>FETCH-LOGICAL-a3217-c72a4448da01502968f7fdfb7f23f0139f17553c9f292a0c5d13fa47c7aa1f7a3</cites><orcidid>0000-0002-8363-6244</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.jcim.6b00407$$EPDF$$P50$$Gacs$$H</linktopdf><linktohtml>$$Uhttps://pubs.acs.org/doi/10.1021/acs.jcim.6b00407$$EHTML$$P50$$Gacs$$H</linktohtml><link.rule.ids>314,780,784,2765,27076,27924,27925,56738,56788</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27976886$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lin, Yu-Feng</creatorcontrib><creatorcontrib>Cheng, Chih-Wen</creatorcontrib><creatorcontrib>Shih, Chung-Shiuan</creatorcontrib><creatorcontrib>Hwang, Jenn-Kang</creatorcontrib><creatorcontrib>Yu, Chin-Sheng</creatorcontrib><creatorcontrib>Lu, Chih-Hao</creatorcontrib><title>MIB: Metal Ion-Binding Site Prediction and Docking Server</title><title>Journal of chemical information and modeling</title><addtitle>J. Chem. Inf. Model</addtitle><description>The structure of a protein determines its biological function(s) and its interactions with other factors; the binding regions tend to be conserved in sequence and structure, and the interacting residues involved are usually in close 3D space. The Protein Data Bank currently contains more than 110 000 protein structures, approximately one-third of which contain metal ions. Identifying and characterizing metal ion-binding sites is thus essential for investigating a protein’s function(s) and interactions. However, experimental approaches are time-consuming and costly. The web server reported here was built to predict metal ion-binding residues and to generate the predicted metal ion-bound 3D structure. Binding templates have been constructed for regions that bind 12 types of metal ion-binding residues have been used to construct binding templates. The templates include residues within 3.5 Å of the metal ion, and the fragment transformation method was used for structural comparison between query proteins and templates without any data training. Through the adjustment of scoring functions, which are based on the similarity of structure and binding residues. Twelve kinds of metal ions (Ca2+, Cu2+, Fe3+, Mg2+, Mn2+, Zn2+, Cd2+, Fe2+, Ni2+, Hg2+, Co2+, and Cu+) binding residues prediction are supported. MIB also provides the metal ions docking after prediction. The MIB server is available at http://bioinfo.cmu.edu.tw/MIB/.</description><subject>Binding Sites</subject><subject>Cations - metabolism</subject><subject>Databases, Protein</subject><subject>Internet</subject><subject>Ions</subject><subject>Metals</subject><subject>Metals - metabolism</subject><subject>Molecular Docking Simulation</subject><subject>Protein Conformation</subject><subject>Proteins</subject><subject>Proteins - chemistry</subject><subject>Proteins - metabolism</subject><subject>Software</subject><issn>1549-9596</issn><issn>1549-960X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kEtLAzEURoMotlb3rmTAjQun5jXJxJ2tr0KLggruQppJJHUeNZkR_PfO9LUQXOVCzvfdywHgFMEhghhdKR2GC-2KIZtDSCHfA32UUBELBt_3t3MiWA8chbCAkBDB8CHoYS44S1PWB2I2GV1HM1OrPJpUZTxyZebKj-jF1SZ69iZzunZVGakyi24r_bn6M_7b-GNwYFUezMnmHYC3-7vX8WM8fXqYjG-msSIY8VhzrCilaaYgSiAWLLXcZnbOLSYWIiIs4klCtLBYYAV1kiFiFeWaK4UsV2QALta9S199NSbUsnBBmzxXpamaIFGaYJZSyNIWPf-DLqrGl-11HUUxZozSloJrSvsqBG-sXHpXKP8jEZSdVtlqlZ1WudHaRs42xc28MNkusPXYApdrYBXdLf2v7xczZoCQ</recordid><startdate>20161227</startdate><enddate>20161227</enddate><creator>Lin, Yu-Feng</creator><creator>Cheng, Chih-Wen</creator><creator>Shih, Chung-Shiuan</creator><creator>Hwang, Jenn-Kang</creator><creator>Yu, Chin-Sheng</creator><creator>Lu, Chih-Hao</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><orcidid>https://orcid.org/0000-0002-8363-6244</orcidid></search><sort><creationdate>20161227</creationdate><title>MIB: Metal Ion-Binding Site Prediction and Docking Server</title><author>Lin, Yu-Feng ; Cheng, Chih-Wen ; Shih, Chung-Shiuan ; Hwang, Jenn-Kang ; Yu, Chin-Sheng ; Lu, Chih-Hao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a3217-c72a4448da01502968f7fdfb7f23f0139f17553c9f292a0c5d13fa47c7aa1f7a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Binding Sites</topic><topic>Cations - metabolism</topic><topic>Databases, Protein</topic><topic>Internet</topic><topic>Ions</topic><topic>Metals</topic><topic>Metals - metabolism</topic><topic>Molecular Docking Simulation</topic><topic>Protein Conformation</topic><topic>Proteins</topic><topic>Proteins - chemistry</topic><topic>Proteins - metabolism</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lin, Yu-Feng</creatorcontrib><creatorcontrib>Cheng, Chih-Wen</creatorcontrib><creatorcontrib>Shih, Chung-Shiuan</creatorcontrib><creatorcontrib>Hwang, Jenn-Kang</creatorcontrib><creatorcontrib>Yu, Chin-Sheng</creatorcontrib><creatorcontrib>Lu, Chih-Hao</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of chemical information and modeling</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lin, Yu-Feng</au><au>Cheng, Chih-Wen</au><au>Shih, Chung-Shiuan</au><au>Hwang, Jenn-Kang</au><au>Yu, Chin-Sheng</au><au>Lu, Chih-Hao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MIB: Metal Ion-Binding Site Prediction and Docking Server</atitle><jtitle>Journal of chemical information and modeling</jtitle><addtitle>J. Chem. Inf. Model</addtitle><date>2016-12-27</date><risdate>2016</risdate><volume>56</volume><issue>12</issue><spage>2287</spage><epage>2291</epage><pages>2287-2291</pages><issn>1549-9596</issn><eissn>1549-960X</eissn><abstract>The structure of a protein determines its biological function(s) and its interactions with other factors; the binding regions tend to be conserved in sequence and structure, and the interacting residues involved are usually in close 3D space. The Protein Data Bank currently contains more than 110 000 protein structures, approximately one-third of which contain metal ions. Identifying and characterizing metal ion-binding sites is thus essential for investigating a protein’s function(s) and interactions. However, experimental approaches are time-consuming and costly. The web server reported here was built to predict metal ion-binding residues and to generate the predicted metal ion-bound 3D structure. Binding templates have been constructed for regions that bind 12 types of metal ion-binding residues have been used to construct binding templates. The templates include residues within 3.5 Å of the metal ion, and the fragment transformation method was used for structural comparison between query proteins and templates without any data training. Through the adjustment of scoring functions, which are based on the similarity of structure and binding residues. Twelve kinds of metal ions (Ca2+, Cu2+, Fe3+, Mg2+, Mn2+, Zn2+, Cd2+, Fe2+, Ni2+, Hg2+, Co2+, and Cu+) binding residues prediction are supported. MIB also provides the metal ions docking after prediction. The MIB server is available at http://bioinfo.cmu.edu.tw/MIB/.</abstract><cop>United States</cop><pub>American Chemical Society</pub><pmid>27976886</pmid><doi>10.1021/acs.jcim.6b00407</doi><tpages>5</tpages><orcidid>https://orcid.org/0000-0002-8363-6244</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Binding Sites Cations - metabolism Databases, Protein Internet Ions Metals Metals - metabolism Molecular Docking Simulation Protein Conformation Proteins Proteins - chemistry Proteins - metabolism Software |
title | MIB: Metal Ion-Binding Site Prediction and Docking Server |
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