title: On various metrics used for validation of predictive QSAR models with applications in virtual screening and focused library design.
abstract: Quantitative structure-activity relationships (QSARs) have important applications in drug discovery research, environmental fate modeling, property prediction, etc. Validation has been recognized as a very important step for QSAR model development. As one of the important objectives of QSAR modeling is to predict activity/property/toxicity of new chemicals falling within the domain of applicability of the developed models and QSARs are being used for regulatory decisions, checking reliability of the models and confidence of their predictions is a very important aspect, which can be judged during the validation process. One prime application of a statistically significant QSAR model is virtual screening for molecules with improved potency based on the pharmacophoric features and the descriptors appearing in the QSAR model. Validated QSAR models may also be utilized for design of focused libraries which may be subsequently screened for the selection of hits. The present review focuses on various metrics used for validation of predictive QSAR models together with an overview of the application of QSAR models in the fields of virtual screening and focused library design for diverse series of compounds with citation of some recent examples.
authors.affiliation: Drug Theoretics and Cheminformatics Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700 032, India. kunalroy_in@yahoo.com
authors.forename: Kunal
authors.initials: K
authors.lastname: Roy
authors.forename: Indrani
authors.initials: I
authors.lastname: Mitra
mesh_terms: D000818:Animals; D015195:Drug Design; D006801:Humans; D008954:Models, Biological; D021281:Quantitative Structure-Activity Relationship; D054852:Small Molecule Libraries / Q000737:chemistry / Q000494:pharmacology
chemical_list: D054852:Small Molecule Libraries