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[摘要]：A computational mol. network anal. of various high-throughput screening (HTS) data sets including inhibition assays and cell-based screens organizes screening hits according to different local structure-activity relationships (SARs). The resulting network representations make it possible to focus on different local SAR environments in screening data. We have designed a simple scoring function accounting for similarity and potency relationships among hits that identifies SAR pathways leading from active compds. in different SAR contexts to key compds. forming activity cliffs. From these pathways, SAR information can be extd. and utilized to select hits for further anal. In clusters of hits related by different local SARs, alternative pathways can be systematically explored and ranked according to SAR information content, which makes it possible to prioritize hits in a consistent manner. |
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