Journal
JOURNAL OF CHEMICAL INFORMATION AND MODELING
Volume 45, Issue 6, Pages 1784-1790Publisher
AMER CHEMICAL SOC
DOI: 10.1021/ci0502808
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The standard activity threshold-based method (the top V approach), currently widely used in the high-throughput screening (HTS) data analysis, is ineffective at identifying good-quality hits. We have proposed a novel knowledge-based statistical approach, driven by the hidden structure-activity relationship (SAR) within a screening library, for primary hit selection. Application to an in-house ultrahigh-throughput screening (uHTS) campaign has demonstrated it call directly identify active scaffolds containing valuable SAR information with a greatly improved confirmation rate compared to the standard top X method (from 55% to 85%). This approach may help produce high-quality leads and expedite the hit-to-lead process in drug discovery.
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