Protein tertiary structure prediction using a branch and bound algorithm
We report a new method for predicting protein tertiary structure from sequence and secondary structure information. The predictions result from global optimization of a potential energy function, including van der Waals, hydrophobic, and excluded volume terms. The optimization algorithm, which is ba...
Gespeichert in:
Veröffentlicht in: | Proteins, structure, function, and bioinformatics structure, function, and bioinformatics, 1999-04, Vol.35 (1), p.41-57 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 57 |
---|---|
container_issue | 1 |
container_start_page | 41 |
container_title | Proteins, structure, function, and bioinformatics |
container_volume | 35 |
creator | Eyrich, Volker A. Standley, Daron M. Felts, Anthony K. Friesner, Richard A. |
description | We report a new method for predicting protein tertiary structure from sequence and secondary structure information. The predictions result from global optimization of a potential energy function, including van der Waals, hydrophobic, and excluded volume terms. The optimization algorithm, which is based on the αBB method developed by Floudas and coworkers (Costas and Floudas, J Chem Phys 1994;100:1247–1261), uses a reduced model of the protein and is implemented in both distance and dihedral angle space, enabling a side‐by‐side comparison of methodologies. For a set of eight small proteins, representing the three basic types—all α, all β, and mixed α/β—the algorithm locates low‐energy native‐like structures (less than 6Å root mean square deviation from the native coordinates) starting from an unfolded state. Serial and parallel implementations of this methodology are discussed. Proteins 1999;35:41–57. © 1999 Wiley‐Liss, Inc. |
doi_str_mv | 10.1002/(SICI)1097-0134(19990401)35:1<41::AID-PROT5>3.0.CO;2-N |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_69637488</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>69637488</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3975-875225267eb82a43215777482ef83481a20d6507bc13cec62ba40b0948c05aa23</originalsourceid><addsrcrecordid>eNqFkF1v0zAUhi0EYmXwF1Cu0HaRcvwV2wVNGoF1laZ2sMEujxzX3TzapNiJYP-elIwJCSRufCTrPc9rP4QcURhTAPb64GJWzg4pGJUD5eKAGmNAAD3kckLfCjqZHM_e5-efFpfyiI9hXC7esHz-iIweVh6TEWitci613CPPUroFgMLw4inZ6ysMMC1H5PQ8Nq0Pddb62AYb77LUxs61XfTZNvplcG1o6qxLob7ObFZFW7ubzNbLrGq6_rTr6yaG9mbznDxZ2XXyL-7nPvl88uGyPM3PFtNZeXyWO26UzLWSjElWKF9pZgVnVCqlhGZ-pbnQ1DJYFhJU5Sh33hWssgIqMEI7kNYyvk9eDdxtbL51PrW4Ccn59drWvukSFqbgPU_3wS9D0MUmpehXuI1h0_8QKeDOMeLOMe6E4U4Y_naMXCJFQRF7x_jLMXIELBfIcN6DX96_oKs2fvkHdpDaB66GwPew9nd_1f6v9V-lw0VPzgdySK3_8UC28SsWiiuJV_MpfhTTkwuj3qHiPwEQwaXo</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>69637488</pqid></control><display><type>article</type><title>Protein tertiary structure prediction using a branch and bound algorithm</title><source>MEDLINE</source><source>Access via Wiley Online Library</source><creator>Eyrich, Volker A. ; Standley, Daron M. ; Felts, Anthony K. ; Friesner, Richard A.</creator><creatorcontrib>Eyrich, Volker A. ; Standley, Daron M. ; Felts, Anthony K. ; Friesner, Richard A.</creatorcontrib><description>We report a new method for predicting protein tertiary structure from sequence and secondary structure information. The predictions result from global optimization of a potential energy function, including van der Waals, hydrophobic, and excluded volume terms. The optimization algorithm, which is based on the αBB method developed by Floudas and coworkers (Costas and Floudas, J Chem Phys 1994;100:1247–1261), uses a reduced model of the protein and is implemented in both distance and dihedral angle space, enabling a side‐by‐side comparison of methodologies. For a set of eight small proteins, representing the three basic types—all α, all β, and mixed α/β—the algorithm locates low‐energy native‐like structures (less than 6Å root mean square deviation from the native coordinates) starting from an unfolded state. Serial and parallel implementations of this methodology are discussed. Proteins 1999;35:41–57. © 1999 Wiley‐Liss, Inc.</description><identifier>ISSN: 0887-3585</identifier><identifier>EISSN: 1097-0134</identifier><identifier>DOI: 10.1002/(SICI)1097-0134(19990401)35:1<41::AID-PROT5>3.0.CO;2-N</identifier><identifier>PMID: 10090285</identifier><language>eng</language><publisher>New York: John Wiley & Sons, Inc</publisher><subject>Algorithms ; Computer Simulation ; global optimization ; Models, Chemical ; Monte Carlo Method ; parallel processing ; Protein Folding ; Protein Structure, Tertiary ; reduced model ; simulated annealing</subject><ispartof>Proteins, structure, function, and bioinformatics, 1999-04, Vol.35 (1), p.41-57</ispartof><rights>Copyright © 1999 Wiley‐Liss, Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c3975-875225267eb82a43215777482ef83481a20d6507bc13cec62ba40b0948c05aa23</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%2F%28SICI%291097-0134%2819990401%2935%3A1%3C41%3A%3AAID-PROT5%3E3.0.CO%3B2-N$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2F%28SICI%291097-0134%2819990401%2935%3A1%3C41%3A%3AAID-PROT5%3E3.0.CO%3B2-N$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/10090285$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Eyrich, Volker A.</creatorcontrib><creatorcontrib>Standley, Daron M.</creatorcontrib><creatorcontrib>Felts, Anthony K.</creatorcontrib><creatorcontrib>Friesner, Richard A.</creatorcontrib><title>Protein tertiary structure prediction using a branch and bound algorithm</title><title>Proteins, structure, function, and bioinformatics</title><addtitle>Proteins</addtitle><description>We report a new method for predicting protein tertiary structure from sequence and secondary structure information. The predictions result from global optimization of a potential energy function, including van der Waals, hydrophobic, and excluded volume terms. The optimization algorithm, which is based on the αBB method developed by Floudas and coworkers (Costas and Floudas, J Chem Phys 1994;100:1247–1261), uses a reduced model of the protein and is implemented in both distance and dihedral angle space, enabling a side‐by‐side comparison of methodologies. For a set of eight small proteins, representing the three basic types—all α, all β, and mixed α/β—the algorithm locates low‐energy native‐like structures (less than 6Å root mean square deviation from the native coordinates) starting from an unfolded state. Serial and parallel implementations of this methodology are discussed. Proteins 1999;35:41–57. © 1999 Wiley‐Liss, Inc.</description><subject>Algorithms</subject><subject>Computer Simulation</subject><subject>global optimization</subject><subject>Models, Chemical</subject><subject>Monte Carlo Method</subject><subject>parallel processing</subject><subject>Protein Folding</subject><subject>Protein Structure, Tertiary</subject><subject>reduced model</subject><subject>simulated annealing</subject><issn>0887-3585</issn><issn>1097-0134</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1999</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkF1v0zAUhi0EYmXwF1Cu0HaRcvwV2wVNGoF1laZ2sMEujxzX3TzapNiJYP-elIwJCSRufCTrPc9rP4QcURhTAPb64GJWzg4pGJUD5eKAGmNAAD3kckLfCjqZHM_e5-efFpfyiI9hXC7esHz-iIweVh6TEWitci613CPPUroFgMLw4inZ6ysMMC1H5PQ8Nq0Pddb62AYb77LUxs61XfTZNvplcG1o6qxLob7ObFZFW7ubzNbLrGq6_rTr6yaG9mbznDxZ2XXyL-7nPvl88uGyPM3PFtNZeXyWO26UzLWSjElWKF9pZgVnVCqlhGZ-pbnQ1DJYFhJU5Sh33hWssgIqMEI7kNYyvk9eDdxtbL51PrW4Ccn59drWvukSFqbgPU_3wS9D0MUmpehXuI1h0_8QKeDOMeLOMe6E4U4Y_naMXCJFQRF7x_jLMXIELBfIcN6DX96_oKs2fvkHdpDaB66GwPew9nd_1f6v9V-lw0VPzgdySK3_8UC28SsWiiuJV_MpfhTTkwuj3qHiPwEQwaXo</recordid><startdate>19990401</startdate><enddate>19990401</enddate><creator>Eyrich, Volker A.</creator><creator>Standley, Daron M.</creator><creator>Felts, Anthony K.</creator><creator>Friesner, Richard A.</creator><general>John Wiley & Sons, Inc</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>19990401</creationdate><title>Protein tertiary structure prediction using a branch and bound algorithm</title><author>Eyrich, Volker A. ; Standley, Daron M. ; Felts, Anthony K. ; Friesner, Richard A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3975-875225267eb82a43215777482ef83481a20d6507bc13cec62ba40b0948c05aa23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1999</creationdate><topic>Algorithms</topic><topic>Computer Simulation</topic><topic>global optimization</topic><topic>Models, Chemical</topic><topic>Monte Carlo Method</topic><topic>parallel processing</topic><topic>Protein Folding</topic><topic>Protein Structure, Tertiary</topic><topic>reduced model</topic><topic>simulated annealing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Eyrich, Volker A.</creatorcontrib><creatorcontrib>Standley, Daron M.</creatorcontrib><creatorcontrib>Felts, Anthony K.</creatorcontrib><creatorcontrib>Friesner, Richard A.</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>Eyrich, Volker A.</au><au>Standley, Daron M.</au><au>Felts, Anthony K.</au><au>Friesner, Richard A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Protein tertiary structure prediction using a branch and bound algorithm</atitle><jtitle>Proteins, structure, function, and bioinformatics</jtitle><addtitle>Proteins</addtitle><date>1999-04-01</date><risdate>1999</risdate><volume>35</volume><issue>1</issue><spage>41</spage><epage>57</epage><pages>41-57</pages><issn>0887-3585</issn><eissn>1097-0134</eissn><abstract>We report a new method for predicting protein tertiary structure from sequence and secondary structure information. The predictions result from global optimization of a potential energy function, including van der Waals, hydrophobic, and excluded volume terms. The optimization algorithm, which is based on the αBB method developed by Floudas and coworkers (Costas and Floudas, J Chem Phys 1994;100:1247–1261), uses a reduced model of the protein and is implemented in both distance and dihedral angle space, enabling a side‐by‐side comparison of methodologies. For a set of eight small proteins, representing the three basic types—all α, all β, and mixed α/β—the algorithm locates low‐energy native‐like structures (less than 6Å root mean square deviation from the native coordinates) starting from an unfolded state. Serial and parallel implementations of this methodology are discussed. Proteins 1999;35:41–57. © 1999 Wiley‐Liss, Inc.</abstract><cop>New York</cop><pub>John Wiley & Sons, Inc</pub><pmid>10090285</pmid><doi>10.1002/(SICI)1097-0134(19990401)35:1<41::AID-PROT5>3.0.CO;2-N</doi><tpages>17</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0887-3585 |
ispartof | Proteins, structure, function, and bioinformatics, 1999-04, Vol.35 (1), p.41-57 |
issn | 0887-3585 1097-0134 |
language | eng |
recordid | cdi_proquest_miscellaneous_69637488 |
source | MEDLINE; Access via Wiley Online Library |
subjects | Algorithms Computer Simulation global optimization Models, Chemical Monte Carlo Method parallel processing Protein Folding Protein Structure, Tertiary reduced model simulated annealing |
title | Protein tertiary structure prediction using a branch and bound algorithm |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T03%3A57%3A15IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Protein%20tertiary%20structure%20prediction%20using%20a%20branch%20and%20bound%20algorithm&rft.jtitle=Proteins,%20structure,%20function,%20and%20bioinformatics&rft.au=Eyrich,%20Volker%20A.&rft.date=1999-04-01&rft.volume=35&rft.issue=1&rft.spage=41&rft.epage=57&rft.pages=41-57&rft.issn=0887-3585&rft.eissn=1097-0134&rft_id=info:doi/10.1002/(SICI)1097-0134(19990401)35:1%3C41::AID-PROT5%3E3.0.CO;2-N&rft_dat=%3Cproquest_cross%3E69637488%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=69637488&rft_id=info:pmid/10090285&rfr_iscdi=true |