Data Analysis of High-Throughput Screening Results: Application of Multidomain Clustering to the NCI Anti-HIV Data Set
The routine use of high-throughput screening (HTS) systems in the drug discovery process has resulted in an increasing need for fast, reliable analysis of massive amounts of data. A new automated multidomain clustering method that thoroughly analyzes screening data sets is used to examine both the active and the inactive compounds in a well-known, publicly available data set based on primary screening. Large and small compound sets that defined both chemical families and potential pharmacophore points were discovered. The detection of structure−activity relationships (SAR), aided by the unique classification method, is described in this article.