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Computational drug discovery

期刊

ACTA PHARMACOLOGICA SINICA
卷 33, 期 9, 页码 1131-1140

出版社

ACTA PHARMACOLOGICA SINICA
DOI: 10.1038/aps.2012.109

关键词

computational drug discovery; target identification; lead discovery

资金

  1. State Key Program of Basic Research of China [2009CB918502]
  2. National Natural Science Foundation of China [21021063, 20972174, 91029704]
  3. Chinese Academy of Sciences [XDA01040305]
  4. National High Technology Research and Development Program of China [2012AA020302]

向作者/读者索取更多资源

Computational drug discovery is an effective strategy for accelerating and economizing drug discovery and development process. Because of the dramatic increase in the availability of biological macromolecule and small molecule information, the applicability of computational drug discovery has been extended and broadly applied to nearly every stage in the drug discovery and development workflow, including target identification and validation, lead discovery and optimization and preclinical tests. Over the past decades, computational drug discovery methods such as molecular docking, pharmacophore modeling and mapping, de novo design, molecular similarity calculation and sequence-based virtual screening have been greatly improved. In this review, we present an overview of these important computational methods, platforms and successful applications in this field.

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