title: Exploiting QSAR methods in lead optimization.
abstract: Quantitative structure-activity relationship (QSAR) models play a key role in lead optimization, where the focus is on increased efficiency and lower attrition. When experimental data becomes rate limiting, a suitable model can bridge the experimental resource gap and direct investigation of a lead series toward productive lines. Technically, QSAR models can be readily generated and published to a wide community via the World Wide Web. We therefore focus this review on issues affecting model quality rather than on cataloguing models that are available. We also review the area of inverse QSAR, in which a model can be harnessed to semi-automated methods to provide an efficient way to explore vast areas of chemical space.
authors.affiliation: Novartis Institutes for BioMedical Research, CH-4002 Basel, Switzerland. nathan.brown@novartis.com
authors.forename: Nathan
authors.initials: N
authors.lastname: Brown
authors.forename: Richard A
authors.initials: RA
authors.lastname: Lewis
mesh_terms: D008956:Models, Chemical; D021281:Quantitative Structure-Activity Relationship; D013678:Technology, Pharmaceutical / Q000379:methods*