Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7523
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dc.contributor.authorLi, Hongjianen_US
dc.contributor.authorProf. LEUNG Kwong Saken_US
dc.contributor.authorWong, Man-Honen_US
dc.date.accessioned2023-03-17T04:25:27Z-
dc.date.available2023-03-17T04:25:27Z-
dc.date.issued2012-
dc.identifier.citation2012 IEEE Symposium on Computational Intelligence and Computational Biology, CIBCB 2012 6217214, pp. 77-84en_US
dc.identifier.isbn978-146731189-2-
dc.identifier.urihttp://hdl.handle.net/20.500.11861/7523-
dc.description.abstractAutoDock Vina is a competitive protein-ligand docking tool well known for its fast execution and high accuracy. Nevertheless, when docking a massive number of ligands, Vina has to be run multiple times, repeating receptor parsing and grid maps building over and over again. There are tremendous requests for revising Vina to reuse precalculated data and incorporate built-in support for virtual screening. Hence we developed idock, inheriting from AutoDock Vina the accurate scoring function and the efficient optimization algorithm, and significantly improving the fundamental implementation and numerical model for even faster execution. idock achieves a speedup of 3.3 in terms of CPU time and a speedup of 7.5 in terms of elapsed time on average. idock is free and open source, available at https://GitHub.com/HongjianLi/idock. © 2012 IEEE.en_US
dc.description.sponsorshipIEEE Computational Intelligence Societyen_US
dc.language.isoenen_US
dc.relation.ispartof2012 IEEE Symposium on Computational Intelligence and Computational Biology, CIBCBen_US
dc.titleIdock: A multithreaded virtual screening tool for flexible ligand dockingen_US
dc.typeConference Paperen_US
dc.identifier.doi10.1109/CIBCB.2012.6217214-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
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