Literature DB >> 11560058

Smart screening: approaches to efficient HTS.

M F Engels1, P Venkatarangan.   

Abstract

Faced with the prospect of a rising number of potential drug targets and given almost unlimited access to internal and external chemistry resources, the 'brute-force' approach to high-throughput screening (HTS) is becoming increasingly unattractive. Pharmaceutical companies realize that they have both to increase the scope of screening experiments and improve on the efficiency of the screening process per se. In acknowledging this development, hybrid screening strategies have been suggested that unite in silico and in vitro screening in one integrated process. The partnering of both screening approaches in one process is believed to exploit the potential of HTS in much smarter and more cost-efficient ways. This review will describe some recent applications of this new screening paradigm and discuss the impact of integrating these novel strategies in the drug discovery process.

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Year:  2001        PMID: 11560058

Source DB:  PubMed          Journal:  Curr Opin Drug Discov Devel        ISSN: 1367-6733


  4 in total

Review 1.  Global analysis of large-scale chemical and biological experiments.

Authors:  David E Root; Brian P Kelley; Brent R Stockwell
Journal:  Curr Opin Drug Discov Devel       Date:  2002-05

2.  The power of chemical genomics to study the link between endomembrane system components and the gravitropic response.

Authors:  Marci Surpin; Marcela Rojas-Pierce; Clay Carter; Glenn R Hicks; Jacob Vasquez; Natasha V Raikhel
Journal:  Proc Natl Acad Sci U S A       Date:  2005-03-16       Impact factor: 11.205

3.  Surrogate docking: structure-based virtual screening at high throughput speed.

Authors:  Sukjoon Yoon; Andrew Smellie; David Hartsough; Anton Filikov
Journal:  J Comput Aided Mol Des       Date:  2005-11-16       Impact factor: 3.686

4.  A maximum common substructure-based algorithm for searching and predicting drug-like compounds.

Authors:  Yiqun Cao; Tao Jiang; Thomas Girke
Journal:  Bioinformatics       Date:  2008-07-01       Impact factor: 6.937

  4 in total

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