Mohammad Moghadasi, Dima Kozakov, Artem B Mamonov, Pirooz Vakili, Sandor Vajda, Ioannis Ch Paschalidis
{"title":"A Message Passing Approach to Side Chain Positioning with Applications in Protein Docking Refinement.","authors":"Mohammad Moghadasi, Dima Kozakov, Artem B Mamonov, Pirooz Vakili, Sandor Vajda, Ioannis Ch Paschalidis","doi":"10.1109/cdc.2012.6426600","DOIUrl":null,"url":null,"abstract":"<p><p>We introduce a message-passing algorithm to solve the <i>Side Chain Positioning (SCP)</i> problem. SCP is a crucial component of <i>protein docking refinement</i>, which is a key step of an important class of problems in computational structural biology called <i>protein docking</i>. We model SCP as a combinatorial optimization problem and formulate it as a <i>Maximum Weighted Independent Set (MWIS)</i> problem. We then employ a modified and convergent belief-propagation algorithm to solve a relaxation of MWIS and develop randomized estimation heuristics that use the relaxed solution to obtain an effective MWIS feasible solution. Using a benchmark set of protein complexes we demonstrate that our approach leads to more accurate docking predictions compared to a baseline algorithm that does not solve the SCP.</p>","PeriodicalId":74517,"journal":{"name":"Proceedings of the ... IEEE Conference on Decision & Control. IEEE Conference on Decision & Control","volume":" ","pages":"2310-2315"},"PeriodicalIF":0.0000,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/cdc.2012.6426600","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... IEEE Conference on Decision & Control. IEEE Conference on Decision & Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/cdc.2012.6426600","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
We introduce a message-passing algorithm to solve the Side Chain Positioning (SCP) problem. SCP is a crucial component of protein docking refinement, which is a key step of an important class of problems in computational structural biology called protein docking. We model SCP as a combinatorial optimization problem and formulate it as a Maximum Weighted Independent Set (MWIS) problem. We then employ a modified and convergent belief-propagation algorithm to solve a relaxation of MWIS and develop randomized estimation heuristics that use the relaxed solution to obtain an effective MWIS feasible solution. Using a benchmark set of protein complexes we demonstrate that our approach leads to more accurate docking predictions compared to a baseline algorithm that does not solve the SCP.