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Application of conformational space annealing to the protein structure modeling using cryo‐EM maps
Conformational space annealing (CSA), a global optimization method, has been applied to various protein structure modeling tasks. In this paper, we applied CSA to the cryo‐EM structure modeling task by combining the python subroutine of CSA (PyCSA) and the fast relax ( FastRelax ) protocol of PyRose...
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Published in: | Journal of computational chemistry 2023-11, Vol.44 (30), p.2332-2346 |
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creator | Park, Jimin Joung, InSuk Joo, Keehyoung Lee, Jooyoung |
description | Conformational space annealing (CSA), a global optimization method, has been applied to various protein structure modeling tasks. In this paper, we applied CSA to the cryo‐EM structure modeling task by combining the python subroutine of CSA (PyCSA) and the fast relax (
FastRelax
) protocol of PyRosetta. Refinement of initial structures generated from two methods, rigid fitting of predicted structures to the Cryo‐EM map and de novo protein modeling by tracing the Cryo‐EM map, was performed by CSA. In the refinement of the rigid‐fitted structures, the final models showed that CSA can generate reliable atomic structures of proteins, even when large movements of protein domains were required. In the de novo modeling case, although the overall structural qualities of the final models were rather dependent on the initial models, the final models generated by CSA showed improved MolProbity scores and cross‐correlation coefficients to the maps. These results suggest that CSA can accomplish flexible fitting and refinement together by sampling diverse conformations effectively and thus can be utilized for cryo‐EM structure modeling. |
doi_str_mv | 10.1002/jcc.27200 |
format | article |
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FastRelax
) protocol of PyRosetta. Refinement of initial structures generated from two methods, rigid fitting of predicted structures to the Cryo‐EM map and de novo protein modeling by tracing the Cryo‐EM map, was performed by CSA. In the refinement of the rigid‐fitted structures, the final models showed that CSA can generate reliable atomic structures of proteins, even when large movements of protein domains were required. In the de novo modeling case, although the overall structural qualities of the final models were rather dependent on the initial models, the final models generated by CSA showed improved MolProbity scores and cross‐correlation coefficients to the maps. These results suggest that CSA can accomplish flexible fitting and refinement together by sampling diverse conformations effectively and thus can be utilized for cryo‐EM structure modeling.</description><identifier>ISSN: 0192-8651</identifier><identifier>EISSN: 1096-987X</identifier><identifier>DOI: 10.1002/jcc.27200</identifier><language>eng</language><publisher>New York: Wiley Subscription Services, Inc</publisher><subject>Annealing ; Correlation coefficients ; Global optimization ; Modelling ; Proteins</subject><ispartof>Journal of computational chemistry, 2023-11, Vol.44 (30), p.2332-2346</ispartof><rights>2023 Wiley Periodicals LLC.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c250t-27939125fab31c248bc77faeb929d5f4c02e8097bc5e6f3a0c4099c544d59d4a3</cites><orcidid>0000-0003-2654-712X</orcidid></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></links><search><creatorcontrib>Park, Jimin</creatorcontrib><creatorcontrib>Joung, InSuk</creatorcontrib><creatorcontrib>Joo, Keehyoung</creatorcontrib><creatorcontrib>Lee, Jooyoung</creatorcontrib><title>Application of conformational space annealing to the protein structure modeling using cryo‐EM maps</title><title>Journal of computational chemistry</title><description>Conformational space annealing (CSA), a global optimization method, has been applied to various protein structure modeling tasks. In this paper, we applied CSA to the cryo‐EM structure modeling task by combining the python subroutine of CSA (PyCSA) and the fast relax (
FastRelax
) protocol of PyRosetta. Refinement of initial structures generated from two methods, rigid fitting of predicted structures to the Cryo‐EM map and de novo protein modeling by tracing the Cryo‐EM map, was performed by CSA. In the refinement of the rigid‐fitted structures, the final models showed that CSA can generate reliable atomic structures of proteins, even when large movements of protein domains were required. In the de novo modeling case, although the overall structural qualities of the final models were rather dependent on the initial models, the final models generated by CSA showed improved MolProbity scores and cross‐correlation coefficients to the maps. These results suggest that CSA can accomplish flexible fitting and refinement together by sampling diverse conformations effectively and thus can be utilized for cryo‐EM structure modeling.</description><subject>Annealing</subject><subject>Correlation coefficients</subject><subject>Global optimization</subject><subject>Modelling</subject><subject>Proteins</subject><issn>0192-8651</issn><issn>1096-987X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNpdkL9OwzAQhy0EEqUw8AaWWGBIOdtxEo9VVf5IRSwgsUXuxYZUSRxsZ-jGI_CMPAlpy8Ryp5M-_fS7j5BLBjMGwG83iDOec4AjMmGgskQV-dsxmQBTPCkyyU7JWQgbABAySyekmvd9U6OOteuosxRdZ51v97duaOg1Gqq7zuim7t5pdDR-GNp7F03d0RD9gHHwhrauMntiCLuJfut-vr6XT7TVfTgnJ1Y3wVz87Sl5vVu-LB6S1fP942K-SpBLiAnPlVCMS6vXgiFPizXmudVmrbiqpE0RuClA5WuUJrNCA6agFMo0raSqUi2m5PqQO_b7HEyIZVsHNE2jO-OGUPJCsiIbI8SIXv1DN27w48s7KmeFGJukI3VzoNC7ELyxZe_rVvttyaDc-S5H3-Xet_gFjTl0nQ</recordid><startdate>20231115</startdate><enddate>20231115</enddate><creator>Park, Jimin</creator><creator>Joung, InSuk</creator><creator>Joo, Keehyoung</creator><creator>Lee, Jooyoung</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>JQ2</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-2654-712X</orcidid></search><sort><creationdate>20231115</creationdate><title>Application of conformational space annealing to the protein structure modeling using cryo‐EM maps</title><author>Park, Jimin ; Joung, InSuk ; Joo, Keehyoung ; Lee, Jooyoung</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c250t-27939125fab31c248bc77faeb929d5f4c02e8097bc5e6f3a0c4099c544d59d4a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Annealing</topic><topic>Correlation coefficients</topic><topic>Global optimization</topic><topic>Modelling</topic><topic>Proteins</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Park, Jimin</creatorcontrib><creatorcontrib>Joung, InSuk</creatorcontrib><creatorcontrib>Joo, Keehyoung</creatorcontrib><creatorcontrib>Lee, Jooyoung</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Computer Science Collection</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of computational chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Park, Jimin</au><au>Joung, InSuk</au><au>Joo, Keehyoung</au><au>Lee, Jooyoung</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Application of conformational space annealing to the protein structure modeling using cryo‐EM maps</atitle><jtitle>Journal of computational chemistry</jtitle><date>2023-11-15</date><risdate>2023</risdate><volume>44</volume><issue>30</issue><spage>2332</spage><epage>2346</epage><pages>2332-2346</pages><issn>0192-8651</issn><eissn>1096-987X</eissn><abstract>Conformational space annealing (CSA), a global optimization method, has been applied to various protein structure modeling tasks. In this paper, we applied CSA to the cryo‐EM structure modeling task by combining the python subroutine of CSA (PyCSA) and the fast relax (
FastRelax
) protocol of PyRosetta. Refinement of initial structures generated from two methods, rigid fitting of predicted structures to the Cryo‐EM map and de novo protein modeling by tracing the Cryo‐EM map, was performed by CSA. In the refinement of the rigid‐fitted structures, the final models showed that CSA can generate reliable atomic structures of proteins, even when large movements of protein domains were required. In the de novo modeling case, although the overall structural qualities of the final models were rather dependent on the initial models, the final models generated by CSA showed improved MolProbity scores and cross‐correlation coefficients to the maps. These results suggest that CSA can accomplish flexible fitting and refinement together by sampling diverse conformations effectively and thus can be utilized for cryo‐EM structure modeling.</abstract><cop>New York</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/jcc.27200</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0003-2654-712X</orcidid></addata></record> |
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subjects | Annealing Correlation coefficients Global optimization Modelling Proteins |
title | Application of conformational space annealing to the protein structure modeling using cryo‐EM maps |
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