Browsing by Subject "Ranking molecules"

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    BioDrugScreen: a computational drug design resource for ranking molecules docked to the human proteome
    (Oxford University Press, 2009-11-18) Li, Liwei; Bum-Erdene, Khuchtumur; Baenziger, Peter H.; Rosen, Joshua J.; Hemmert, Jamison R.; Nellis, Joy A.; Pierce, Marlon E.; Meroueh, Samy O.; Biochemistry and Molecular Biology, School of Medicine
    BioDrugScreen 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.