Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA.
Nucleic Acids Res. 2010 Jan;38(Database issue):D765-73. doi: 10.1093/nar/gkp852. Epub 2009 Nov 18.
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.
BioDrugScreen 是一个资源,用于对人类蛋白质组中大量靶标上对接的分子进行排名。将近 1600 种来自 NCI 免费多样性集的分子被对接在 1589 个人类靶标上的 1926 个腔上,这导致了超过 300 万个受体-配体复合物,需要在 TeraGrid 上使用超过 200000 个 cpu 小时。BioDrugScreen 中的靶标源自人类癌症蛋白质相互作用网络,我们已经对其进行了更新,以及我们为该项目创建的人类可成药蛋白质组。这使得 BioDrugScreen 资源在药物发现中非常有价值。数据库中的受体-配体复合物可以使用标准的、成熟的评分函数进行评分,如 AutoDock、DockScore、ChemScore、X-Score、GoldScore、DFIRE 和 PMF。此外,我们还使用更密集的 GBSA 和 PBSA 方法对复合物进行了评分,这在 TeraGrid 上需要额外的 120000 个 cpu 小时。我们构建了一个简单的界面,使用户能够查看排名靠前的分子,并访问购买信息和其他信息,以进行进一步的实验探索。