Literature DB >> 17933683

Drug discovery and computational evolutionary analysis.

Joanna D Holbrook1, Philippe Sanseau.   

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.

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Year:  2007        PMID: 17933683     DOI: 10.1016/j.drudis.2007.08.015

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  3 in total

1.  The role of positive selection in determining the molecular cause of species differences in disease.

Authors:  Jessica J Vamathevan; Samiul Hasan; Richard D Emes; Heather Amrine-Madsen; Dilip Rajagopalan; Simon D Topp; Vinod Kumar; Michael Word; Mark D Simmons; Steven M Foord; Philippe Sanseau; Ziheng Yang; Joanna D Holbrook
Journal:  BMC Evol Biol       Date:  2008-10-06       Impact factor: 3.260

2.  Evolutionary patterning: a novel approach to the identification of potential drug target sites in Plasmodium falciparum.

Authors:  Pierre M Durand; Kubendran Naidoo; Theresa L Coetzer
Journal:  PLoS One       Date:  2008-11-10       Impact factor: 3.240

3.  Mixture models for gene expression experiments with two species.

Authors:  Yuhua Su; Lei Zhu; Alan Menius; Jason Osborne
Journal:  Hum Genomics       Date:  2014-08-01       Impact factor: 4.639

  3 in total

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