Computational drug discovery

被引:199
|
作者
Ou-Yang, Si-sheng [1 ]
Lu, Jun-yan [1 ]
Kong, Xiang-qian [1 ]
Liang, Zhong-jie [1 ]
Luo, Cheng [1 ]
Jiang, Hualiang [1 ]
机构
[1] Chinese Acad Sci, Shanghai Inst Mat Med, State Key Lab Drug Res, Drug Discovery & Design Ctr, Shanghai 201203, Peoples R China
基金
中国国家自然科学基金; 国家高技术研究发展计划(863计划);
关键词
computational drug discovery; target identification; lead discovery; PROTEIN-LIGAND INTERACTIONS; HUMAN CYCLOPHILIN-A; MOLECULAR SIMILARITY; TARGET IDENTIFICATION; SCORING FUNCTION; CONFORMATIONAL GENERATION; CHEMICAL INHIBITORS; BINDING AFFINITIES; ACCURATE DOCKING; ACTIVE COMPOUNDS;
D O I
10.1038/aps.2012.109
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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.
引用
收藏
页码:1131 / 1140
页数:10
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