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- W2004386051 abstract "Retrospective small-scale virtual screening (VS) based on benchmarking data sets has been widely used to estimate ligand enrichments of VS approaches in the prospective (i.e. real-world) efforts. However, the intrinsic differences of benchmarking sets to the real screening chemical libraries can cause biased assessment. Herein, we summarize the history of benchmarking methods as well as data sets and highlight three main types of biases found in benchmarking sets, i.e. analogue bias, artificial enrichment and false negative. In addition, we introduce our recent algorithm to build maximum-unbiased benchmarking sets applicable to both ligand-based and structure-based VS approaches, and its implementations to three important human histone deacetylases (HDACs) isoforms, i.e. HDAC1, HDAC6 and HDAC8. The leave-one-out cross-validation (LOO CV) demonstrates that the benchmarking sets built by our algorithm are maximum-unbiased as measured by property matching, ROC curves and AUCs." @default.
- W2004386051 created "2016-06-24" @default.
- W2004386051 creator A5008008726 @default.
- W2004386051 creator A5040382093 @default.
- W2004386051 creator A5046200146 @default.
- W2004386051 creator A5046787731 @default.
- W2004386051 creator A5089487649 @default.
- W2004386051 date "2015-01-01" @default.
- W2004386051 modified "2023-10-18" @default.
- W2004386051 title "Benchmarking methods and data sets for ligand enrichment assessment in virtual screening" @default.
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