Evaluation and Optimization of Virtual Screening Workflows with DEKOIS 2.0 鈥?A Public Library of Challenging Docking Benchmark Sets

详细信息    查看全文

• 作者：Matthias R. Bauer ; Tamer M. Ibrahim ; Simon M. Vogel ; Frank M. Boeckler
• 刊名：Journal of Chemical Information and Modeling
• 出版年：2013
• 出版时间：June 24, 2013
• 年：2013
• 卷：53
• 期：6
• 页码：1447-1462
• 全文大小：771K
• 年卷期：v.53,no.6(June 24, 2013)
• ISSN：1549-960X

文摘

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 m" class="extLink">http://www.dekois.com.