title: Structure-activity relationship approaches and applications.
abstract: New techniques and software have enabled ubiquitous use of structure-activity relationships (SARs) in the pharmaceutical industry and toxicological sciences. We review the status of SAR technology by using examples to underscore the advances as well as the unique technical challenges. Applying SAR involves two steps: Characterization of the chemicals under investigation, and application of chemometric approaches to explore data patterns or to establish the relationships between structure and activity. We describe generally but not exhaustively the SAR methodologies popular use in toxicology, including representation of chemical structure, and chemometric techniques where models are both unsupervised and supervised. The utility of SAR technology is most evident when supervised methods are used to predict toxicity of untested chemicals based only on chemical structure. Such models can predict on both an ordinal scale (e.g., active vs inactive) or a continuouis scale (e.g., median lethal dose [LD50] dose). The reader is also referred to a companion paper in this issue that discusses quantitative structure-activity relationship (QSAR) methods that have advanced markedly over the past decade.
authors.affiliation: Center for Toxicoinformatics, National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Road, Jefferson, Arkansas 72079, USA.
authors.forename: Weida
authors.initials: W
authors.lastname: Tong
authors.forename: William J
authors.initials: WJ
authors.lastname: Welsh
authors.forename: Leming
authors.initials: L
authors.lastname: Shi
authors.forename: Hong
authors.initials: H
authors.lastname: Fang
authors.forename: Roger
authors.initials: R
authors.lastname: Perkins
mesh_terms: D005544:Forecasting; D008962:Models, Theoretical; D012107:Research Design; D012984:Software; D013329:Structure-Activity Relationship; D014116:Toxicology / Q000639:trends*