title: Drug discovery and computational evolutionary analysis.
abstract: Drug discovery remains a difficult business with a very high level of attrition. Many steps in this long process use data generated from various species. One key challenge is to successfully translate the pre-clinical findings of target validation and safety studies in animal models to diverse human beings in the clinic. Advanced computational evolutionary analysis techniques combined with the increasing availability of sequence information enable the application of systematic evolutionary approaches to targets and pathways of interest to drug discovery. These analyses have the potential to increase our understanding of experimental differences observed between species.
authors.affiliation: GlaxoSmithKline, Molecular Discovery Research, Bioinformatics Analysis, Stevenage SG1 2NY, United Kingdom.
authors.forename: Joanna D
authors.initials: JD
authors.lastname: Holbrook
authors.forename: Philippe
authors.initials: P
authors.lastname: Sanseau
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D015195:Drug Design; D019143:Evolution, Molecular; D023281:Genomics / Q000379:methods*; D006801:Humans; D010802:Phylogeny; D012107:Research Design; D013045:Species Specificity