title: Chemoinformatics and chemical genomics: potential utility of in silico methods.
abstract: Computational life sciences and informatics are inseparably intertwined and they lie at the heart of modern biology, predictive quantitative modeling and high-performance computing. Two of the applied biological disciplines that are poised to benefit from such progress are pharmacology and toxicology. This review will describe in silico chemoinformatics methods such as (quantitative) structure-activity relationship modeling and will overview how chemoinformatic technologies are considered in applied regulatory research. Given the post-genomics era and large-scale repositories of omics data that are available, this review will also address potential applications of in silico techniques in chemical genomics. Chemical genomics utilizes small molecules to explore the complex biological phenomena that may not be not amenable to straightforward genetic approach. The reader will gain the understanding that chemoinformatics stands at the interface of chemistry and biology with enabling systems for mapping, statistical modeling, pattern recognition, imaging and database tools. The great potential of these technologies to help address complex issues in the toxicological sciences is appreciated with the applied goal of the protection of public health.
authors.affiliation: Science and Research Staff, Office of Pharmaceutical Science, Center for Drug Evaluation and Research, US Food and Drug Administration, White Oak 51, Room 4128, 10903 New Hampshire Avenue, Silver Spring, MD 20993-0002, USA. luis.valerio@fda.hhs.gov
authors.forename: Luis G
authors.initials: LG
authors.lastname: Valerio
authors.forename: Supratim
authors.initials: S
authors.lastname: Choudhuri
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D016208:Databases, Factual; D020869:Gene Expression Profiling; D023281:Genomics / Q000379:methods*; D006801:Humans; D048088:Informatics / Q000379:methods*; D021281:Quantitative Structure-Activity Relationship; D014116:Toxicology / Q000379:methods*