title: Large-Scale QSAR in Target Prediction and Phenotypic HTS Assessment.
abstract: The advent of in silico compound target prediction offers a potential paradigm shift in how large compound collections are understood and used strategically in high-throughput screens (HTS). Specifically, phenotypic HTS hits may be annotated both with known targets and predicted targets using large-scale QSAR models, enabling a more sophisticated hit assessment. Efforts in massive bioactivity data integration and standardization is empowering such compound-target annotations. These approaches differ fundamentally from the traditional role of QSAR in lead optimization and binding affinity predictions to global, probabilistic target predictions for thousands of human proteins.
authors.affiliation: Developmental and Molecular Pathways, Quantitative Biology, Novartis Institutes for BioMedical Research, 220 Massachusetts Ave., Cambridge, MA 02139 phone: 617-871-7155. jeremy.jenkins@novartis.com.
authors.forename: Jeremy L
authors.initials: JL
authors.lastname: Jenkins
keywords: Bayesian models; HTS fingerprints; Mechanism-of-action; Pathway enrichment; Phenotypic screening