BioDrugScreen: a computational drug design resource for ranking molecules docked to the human proteome

dc.contributor.authorLi, Liwei
dc.contributor.authorBum-Erdene, Khuchtumur
dc.contributor.authorBaenziger, Peter H.
dc.contributor.authorRosen, Joshua J.
dc.contributor.authorHemmert, Jamison R.
dc.contributor.authorNellis, Joy A.
dc.contributor.authorPierce, Marlon E.
dc.contributor.authorMeroueh, Samy O.
dc.contributor.departmentBiochemistry and Molecular Biology, School of Medicineen_US
dc.date.accessioned2020-05-21T20:16:50Z
dc.date.available2020-05-21T20:16:50Z
dc.date.issued2009-11-18
dc.description.abstractBioDrugScreen is a resource for ranking molecules docked against a large number of targets in the human proteome. Nearly 1600 molecules from the freely available NCI diversity set were docked onto 1926 cavities identified on 1589 human targets resulting in >3 million receptor–ligand complexes requiring >200 000 cpu-hours on the TeraGrid. The targets in BioDrugScreen originated from Human Cancer Protein Interaction Network, which we have updated, as well as the Human Druggable Proteome, which we have created for the purpose of this effort. This makes the BioDrugScreen resource highly valuable in drug discovery. The receptor–ligand complexes within the database can be ranked using standard and well-established scoring functions like AutoDock, DockScore, ChemScore, X-Score, GoldScore, DFIRE and PMF. In addition, we have scored the complexes with more intensive GBSA and PBSA approaches requiring an additional 120 000 cpu-hours on the TeraGrid. We constructed a simple interface to enable users to view top-ranking molecules and access purchasing and other information for further experimental exploration.en_US
dc.eprint.versionFinal published versionen_US
dc.identifier.citationLiwei Li, Khuchtumur Bum-Erdene, Peter H. Baenziger, Joshua J. Rosen, Jamison R. Hemmert, Joy A. Nellis, Marlon E. Pierce, Samy O. Meroueh, BioDrugScreen: a computational drug design resource for ranking molecules docked to the human proteome, Nucleic Acids Research, Volume 38, Issue suppl_1, 1 January 2010, Pages D765–D773, https://doi.org/10.1093/nar/gkp852en_US
dc.identifier.urihttps://hdl.handle.net/1805/22858
dc.language.isoen_USen_US
dc.publisherOxford University Pressen_US
dc.relation.isversionof10.1093/nar/gkp852en_US
dc.relation.journalNucleic Acids Researchen_US
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0*
dc.sourcePublisheren_US
dc.subjectHuman proteome targetsen_US
dc.subjectBioDrugScreen resourceen_US
dc.subjectDrug discoveryen_US
dc.subjectRanking moleculesen_US
dc.subjectScoring functionsen_US
dc.titleBioDrugScreen: a computational drug design resource for ranking molecules docked to the human proteomeen_US
dc.typeArticleen_US
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