诱饵
最大值和最小值
计算机科学
对接(动物)
数据挖掘
人工智能
算法
数学
化学
生物化学
医学
数学分析
护理部
受体
作者
Reed M. Stein,Yang Ying,Trent E. Balius,Matthew J. O’Meara,Jiankun Lyu,Jennifer J. Young,Khanh Tang,Brian K. Shoichet,John J. Irwin
标识
DOI:10.1021/acs.jcim.0c00598
摘要
Enrichment of ligands versus property-matched decoys is widely used to test and optimize docking library screens. However, the unconstrained optimization of enrichment alone can mislead, leading to false confidence in prospective performance. This can arise by over-optimizing for enrichment against property-matched decoys, without considering the full spectrum of molecules to be found in a true large library screen. Adding decoys representing charge extrema helps mitigate over-optimizing for electrostatic interactions. Adding decoys that represent the overall characteristics of the library to be docked allows one to sample molecules not represented by ligands and property-matched decoys but that one will encounter in a prospective screen. An optimized version of the DUD-E set (DUDE-Z), as well as Extrema and sets representing broad features of the library (Goldilocks), is developed here. We also explore the variability that one can encounter in enrichment calculations and how that can temper one's confidence in small enrichment differences. The new tools and new decoy sets are freely available at http://tldr.docking.org and http://dudez.docking.org.
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