对接(动物)
码头
标杆管理
计算机科学
化学
化学空间
虚拟筛选
化学
药物发现
计算生物学
人工智能
数据挖掘
机器学习
医学
生物
生物化学
业务
护理部
营销
作者
Michael M. Mysinger,Michael Carchia,John J. Irwin,Brian K. Shoichet
摘要
A key metric to assess molecular docking remains ligand enrichment against challenging decoys. Whereas the directory of useful decoys (DUD) has been widely used, clear areas for optimization have emerged. Here we describe an improved benchmarking set that includes more diverse targets such as GPCRs and ion channels, totaling 102 proteins with 22886 clustered ligands drawn from ChEMBL, each with 50 property-matched decoys drawn from ZINC. To ensure chemotype diversity, we cluster each target's ligands by their Bemis–Murcko atomic frameworks. We add net charge to the matched physicochemical properties and include only the most dissimilar decoys, by topology, from the ligands. An online automated tool (http://decoys.docking.org) generates these improved matched decoys for user-supplied ligands. We test this data set by docking all 102 targets, using the results to improve the balance between ligand desolvation and electrostatics in DOCK 3.6. The complete DUD-E benchmarking set is freely available at http://dude.docking.org.
科研通智能强力驱动
Strongly Powered by AbleSci AI