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dc.contributor.authorVreven, Thom
dc.contributor.authorHwang, Howook
dc.contributor.authorPierce, Brian G.
dc.contributor.authorWeng, Zhiping
dc.date2022-08-11T08:07:59.000
dc.date.accessioned2022-08-23T15:38:22Z
dc.date.available2022-08-23T15:38:22Z
dc.date.issued2014-03-01
dc.date.submitted2015-06-24
dc.identifier.citationBrief Bioinform. 2014 Mar;15(2):169-76. doi: 10.1093/bib/bbt047. Epub 2013 Jul 1. <a href="http://dx.doi.org/10.1093/bib/bbt047">Link to article on publisher's site</a>
dc.identifier.issn1467-5463 (Linking)
dc.identifier.doi10.1093/bib/bbt047
dc.identifier.pmid23818491
dc.identifier.urihttp://hdl.handle.net/20.500.14038/25921
dc.description.abstractWe compared the performance of template-free (docking) and template-based methods for the prediction of protein-protein complex structures. We found similar performance for a template-based method based on threading (COTH) and another template-based method based on structural alignment (PRISM). The template-based methods showed similar performance to a docking method (ZDOCK) when the latter was allowed one prediction for each complex, but when the same number of predictions was allowed for each method, the docking approach outperformed template-based approaches. We identified strengths and weaknesses in each method. Template-based approaches were better able to handle complexes that involved conformational changes upon binding. Furthermore, the threading-based and docking methods were better than the structural-alignment-based method for enzyme-inhibitor complex prediction. Finally, we show that the near-native (correct) predictions were generally not shared by the various approaches, suggesting that integrating their results could be the superior strategy.
dc.language.isoen_US
dc.relation<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=23818491&dopt=Abstract">Link to Article in PubMed</a>
dc.relation.urlhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3956070/
dc.subjectAlgorithms
dc.subjectComputational Biology
dc.subjectDatabases, Protein
dc.subjectProtein Conformation
dc.subject*Protein Interaction Domains and Motifs
dc.subjectProtein Interaction Mapping
dc.subjectSequence Alignment
dc.subjectSoftware
dc.subjectStructural Homology, Protein
dc.subjectBiochemistry, Biophysics, and Structural Biology
dc.subjectBioinformatics
dc.subjectComputational Biology
dc.subjectIntegrative Biology
dc.subjectStructural Biology
dc.subjectSystems Biology
dc.titleEvaluating template-based and template-free protein-protein complex structure prediction
dc.typeJournal Article
dc.source.journaltitleBriefings in bioinformatics
dc.source.volume15
dc.source.issue2
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/bioinformatics_pubs/61
dc.identifier.contextkey7256020
html.description.abstract<p>We compared the performance of template-free (docking) and template-based methods for the prediction of protein-protein complex structures. We found similar performance for a template-based method based on threading (COTH) and another template-based method based on structural alignment (PRISM). The template-based methods showed similar performance to a docking method (ZDOCK) when the latter was allowed one prediction for each complex, but when the same number of predictions was allowed for each method, the docking approach outperformed template-based approaches. We identified strengths and weaknesses in each method. Template-based approaches were better able to handle complexes that involved conformational changes upon binding. Furthermore, the threading-based and docking methods were better than the structural-alignment-based method for enzyme-inhibitor complex prediction. Finally, we show that the near-native (correct) predictions were generally not shared by the various approaches, suggesting that integrating their results could be the superior strategy.</p>
dc.identifier.submissionpathbioinformatics_pubs/61
dc.contributor.departmentProgram in Bioinformatics and Integrative Biology
dc.source.pages169-76


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