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.
Tamura
Susan Y
SY
Bioreason, Inc., 150 Washington Avenue, Suite 220, Santa Fe, NM 87501, USA.
Bacha
Patricia A
PA
Gruver
Heather S
HS
Nutt
Ruth F
RF
D000465:Algorithms; D019380:Anti-HIV Agents / Q000737:chemistry* / Q000145:classification; D020650:Combinatorial Chemistry Techniques; D016208:Databases, Factual; D009316:National Institutes of Health (U.S.); D021281:Quantitative Structure-Activity Relationship; D014481:United States
D019380:Anti-HIV Agents