Computational Methods in Drug Discovery

被引:1182
|
作者
Sliwoski, Gregory [1 ]
Kothiwale, Sandeepkumar [1 ]
Meiler, Jens [1 ]
Lowe, Edward W., Jr. [1 ]
机构
[1] Vanderbilt Univ, Meiler Lab, Struct Biol Ctr, Nashville, TN 37235 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
STRUCTURE-BASED DESIGN; PROTEIN-COUPLED RECEPTORS; SMALL-MOLECULE INHIBITOR; HISTAMINE H-3 RECEPTOR; LIGAND BINDING-SITES; LONG-QT-SYNDROME; DE-NOVO DESIGN; STRUCTURE-METABOLISM RELATIONSHIPS; ITERATIVE PARTIAL EQUALIZATION; DEPENDENT ROTAMER LIBRARY;
D O I
10.1124/pr.112.007336
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature.
引用
收藏
页码:334 / 395
页数:62
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