Literature DB >> 12509758

Knockouts model the 100 best-selling drugs--will they model the next 100?

Brian P Zambrowicz1, Arthur T Sands.   

Abstract

The biopharmaceutical industry is currently faced with a tremendous number of potential drug targets identified through the sequencing of the human genome. The challenge ahead is to delineate those targets with the greatest value for therapeutic intervention. Here, we critically evaluate mouse-knockout technology for target discovery and validation. A retrospective evaluation of the knockout phenotypes for the targets of the 100 best-selling drugs indicates that these phenotypes correlate well with known drug efficacy, illuminating a productive path forward for discovering future drug targets. Prospective mining of the druggable genome is being catalysed by large-scale mouse knockout programs combined with phenotypic screens focused on identifying targets that modulate mammalian physiology in a therapeutically relevant manner.

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Year:  2003        PMID: 12509758     DOI: 10.1038/nrd987

Source DB:  PubMed          Journal:  Nat Rev Drug Discov        ISSN: 1474-1776            Impact factor:   84.694


  80 in total

1.  Bioinformatical assay of human gene morbidity.

Authors:  Fyodor A Kondrashov; Aleksey Y Ogurtsov; Alexey S Kondrashov
Journal:  Nucleic Acids Res       Date:  2004-03-12       Impact factor: 16.971

Review 2.  New approaches to the representation and analysis of phenotype knowledge in human diseases and their animal models.

Authors:  Paul N Schofield; John P Sundberg; Robert Hoehndorf; Georgios V Gkoutos
Journal:  Brief Funct Genomics       Date:  2011-09       Impact factor: 4.241

3.  Derivation of rat embryonic stem cells and generation of protease-activated receptor-2 knockout rats.

Authors:  Satoshi Yamamoto; Mitsugu Nakata; Reiko Sasada; Yuki Ooshima; Takashi Yano; Tadahiro Shinozawa; Yasuhiro Tsukimi; Michiyasu Takeyama; Yoshio Matsumoto; Tadatoshi Hashimoto
Journal:  Transgenic Res       Date:  2011-10-15       Impact factor: 2.788

Review 4.  Fishing for answers with transposons.

Authors:  Shannon A Wadman; Karl J Clark; Perry B Hackett
Journal:  Mar Biotechnol (NY)       Date:  2005-05-05       Impact factor: 3.619

Review 5.  Decompartmentalizing target validation-thinking outside the pipeline boxes.

Authors:  Rob Hooft van Huijsduijnen; Christian Rommel
Journal:  J Mol Med (Berl)       Date:  2006-08-05       Impact factor: 4.599

6.  Interrogating the druggable genome with structural informatics.

Authors:  Kevin Hambly; Joseph Danzer; Steven Muskal; Derek A Debe
Journal:  Mol Divers       Date:  2006-09-22       Impact factor: 2.943

7.  Quantitative systems-level determinants of human genes targeted by successful drugs.

Authors:  Lixia Yao; Andrey Rzhetsky
Journal:  Genome Res       Date:  2007-12-14       Impact factor: 9.043

Review 8.  Drug metabolism and pharmacokinetics, the blood-brain barrier, and central nervous system drug discovery.

Authors:  Mohammad S Alavijeh; Mansoor Chishty; M Zeeshan Qaiser; Alan M Palmer
Journal:  NeuroRx       Date:  2005-10

9.  Alpha1-adrenergic receptors prevent a maladaptive cardiac response to pressure overload.

Authors:  Timothy D O'Connell; Philip M Swigart; M C Rodrigo; Shinji Ishizaka; Shuji Joho; Lynne Turnbull; Laurence H Tecott; Anthony J Baker; Elyse Foster; William Grossman; Paul C Simpson
Journal:  J Clin Invest       Date:  2006-04       Impact factor: 14.808

10.  Differential proteomic analysis of caveolin-1 KO cells reveals Sh2b3 and Clec12b as novel interaction partners of caveolin-1 and Capns1 as a potential mediator of caveolin-1-induced apoptosis.

Authors:  Yogesh M Kulkarni; Changxing Liu; Qi Qi; Yanmei Zhu; David J Klinke; Jun Liu
Journal:  Analyst       Date:  2013-11-21       Impact factor: 4.616

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