Performance of ZDOCK and IRAD in CAPRI rounds 28-34
dc.contributor.author | Vreven, Thom | |
dc.contributor.author | Pierce, Brian G. | |
dc.contributor.author | Borrman, Tyler M. | |
dc.contributor.author | Weng, Zhiping | |
dc.date | 2022-08-11T08:07:58.000 | |
dc.date.accessioned | 2022-08-23T15:37:55Z | |
dc.date.available | 2022-08-23T15:37:55Z | |
dc.date.issued | 2017-03-01 | |
dc.date.submitted | 2017-07-12 | |
dc.identifier.citation | <p>Proteins. 2017 Mar;85(3):408-416. doi: 10.1002/prot.25186. Epub 2016 Oct 24. <a href="https://doi.org/10.1002/prot.25186">Link to article on publisher's site</a></p> | |
dc.identifier.issn | 0887-3585 (Linking) | |
dc.identifier.doi | 10.1002/prot.25186 | |
dc.identifier.pmid | 27718275 | |
dc.identifier.uri | http://hdl.handle.net/20.500.14038/25826 | |
dc.description.abstract | We report the performance of our protein-protein docking pipeline, including the ZDOCK rigid-body docking algorithm, on 19 targets in CAPRI rounds 28-34. Following the docking step, we reranked the ZDOCK predictions using the IRAD scoring function, pruned redundant predictions, performed energy landscape analysis, and utilized our interface prediction approach RCF. In addition, we applied constraints to the search space based on biological information that we culled from the literature, which increased the chance of making a correct prediction. For all but two targets we were able to find and apply biological information and we found the information to be highly accurate, indicating that effective incorporation of biological information is an important component for protein-protein docking. | |
dc.language.iso | en_US | |
dc.relation | <p><a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=27718275&dopt=Abstract">Link to Article in PubMed</a></p> | |
dc.relation.url | https://doi.org/10.1002/prot.25186 | |
dc.subject | ZRANK | |
dc.subject | complex | |
dc.subject | docking | |
dc.subject | protein-protein interaction | |
dc.subject | structure | |
dc.subject | Biochemistry, Biophysics, and Structural Biology | |
dc.subject | Bioinformatics | |
dc.subject | Computational Biology | |
dc.subject | Integrative Biology | |
dc.subject | Systems Biology | |
dc.title | Performance of ZDOCK and IRAD in CAPRI rounds 28-34 | |
dc.type | Journal Article | |
dc.source.journaltitle | Proteins | |
dc.source.volume | 85 | |
dc.source.issue | 3 | |
dc.identifier.legacycoverpage | https://escholarship.umassmed.edu/bioinformatics_pubs/118 | |
dc.identifier.contextkey | 10417171 | |
html.description.abstract | <p>We report the performance of our protein-protein docking pipeline, including the ZDOCK rigid-body docking algorithm, on 19 targets in CAPRI rounds 28-34. Following the docking step, we reranked the ZDOCK predictions using the IRAD scoring function, pruned redundant predictions, performed energy landscape analysis, and utilized our interface prediction approach RCF. In addition, we applied constraints to the search space based on biological information that we culled from the literature, which increased the chance of making a correct prediction. For all but two targets we were able to find and apply biological information and we found the information to be highly accurate, indicating that effective incorporation of biological information is an important component for protein-protein docking.</p> | |
dc.identifier.submissionpath | bioinformatics_pubs/118 | |
dc.contributor.department | Program in Bioinformatics and Integrative Biology | |
dc.source.pages | 408-416 |