标杆管理
虚拟筛选
计算机科学
水准点(测量)
工作流程
诱饵
集合(抽象数据类型)
机器学习
数据挖掘
数据库
生物信息学
药物发现
化学
生物
业务
营销
受体
生物化学
程序设计语言
地理
大地测量学
作者
Matthias R. Bauer,Tamer M. Ibrahim,Simon Vogel,Frank M. Boeckler
摘要
The application of molecular benchmarking sets helps to assess the actual performance of virtual screening (VS) workflows. To improve the efficiency of structure-based VS approaches, the selection and optimization of various parameters can be guided by benchmarking. With the DEKOIS 2.0 library, we aim to further extend and complement the collection of publicly available decoy sets. Based on BindingDB bioactivity data, we provide 81 new and structurally diverse benchmark sets for a wide variety of different target classes. To ensure a meaningful selection of ligands, we address several issues that can be found in bioactivity data. We have improved our previously introduced DEKOIS methodology with enhanced physicochemical matching, now including the consideration of molecular charges, as well as a more sophisticated elimination of latent actives in the decoy set (LADS). We evaluate the docking performance of Glide, GOLD, and AutoDock Vina with our data sets and highlight existing challenges for VS tools. All DEKOIS 2.0 benchmark sets will be made accessible at http://www.dekois.com.
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