Quantitative (and qualitative) structure-activity relationships, (Q)SARs, have been extensively developed for use in biochemistry and toxicology. Numerous applications exist in other fields, such as the physical sciences and ecological health; however they are beyond the scope of this review. In molecular biology, knowledge about genomes, proteomes, chemical structure and relationships between these molecules have been collected and stored in public databases. 1) These two methods are utilized in different ways to understand biological systems. For example, in the development of drugs, a biological database is used to identify a drug target using data acquired via high-throughput approaches (i.e. microarray data) and then (Q)SAR analysis is used to identify small molecules that bind the drug target. However binding to a target is insufficient for full evaluation of a compound's biological activity and eventual utility as a pesticide or pharmaceutical. It is also vital to understand the compound's adsorption, distribution, metabolism, excretion and toxicity (ADME-Tox) properties. This means that (Q)SAR analysis is insufficient to understand the pharmacokinetics of compounds in a biological system. One solution to this problem is to consider drug metabolites on an individual basis, integrating the enzymes that are responsible for the degradation/metabolism of a given compound as well as its metabolites. This analysis can reveal the dynamics of xenobiotics in biological systems. For example, Ekins et al. integrated QSAR coupled to a gene network dataset to examine drug metabolism and toxicity.2) However methods to incorporate integrated (Q)SAR analysis with that of a biological database are not sufficiently advanced for wide-scale application. In this review, we give a brief overview of (Q)SAR and a publicly available biological database. We then show an example of a combined chemical and genomics analysis by using SAR and pathway analysis of the biological degradation processes of endocrine disrupting chemicals (EDCs).
Structure-activity relationships
Overview of structure-activity relationships(Q)SARs are mathematical relationships that link chemical structure to biological (ecological, toxicological or pharmacological) activity for a series of compounds. There are a multitude of methods available that can be used in (Q)SAR analy- (Q)SARs estimate biological activity; however these models are insufficient to fully understand and predict the ADME-Tox processes of small molecules in biological systems. By integrating (Q)SARs with biological databases, the predictive capability of these models can be significantly improved. However, the techniques and methods for integrated analysis have not yet been sufficiently developed for these combined systems. In this review, we discuss standard (Q)SAR methods and biological database construction as well as provide an example of how SAR and metabolic pathway analysis can be combined to examine the biological degradation processes of endocrine disrupting chemicals.