Chemogenomics in drug discovery: computational methods based on the comparison of binding sites

被引:0
|
作者
Vulpetti, Anna [1 ]
Kalliokoski, Tuomo [1 ]
Milletti, Francesca [2 ]
机构
[1] CADD, Novartis Inst Biomed Res, CH-4002 Basel, Switzerland
[2] Hoffmann La Roche Inc, pRED Informat, Nutley, NJ USA
关键词
PROTEIN-LIGAND-BINDING; FUNCTIONAL CLASSIFICATION; SIMILARITY ANALYSIS; PREDICTION; SEQUENCE; POCKETS; POLYPHARMACOLOGY; IDENTIFICATION; DATABASE; EVOLUTIONARY;
D O I
10.4155/FMC.12.147
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
Novel computational methods for understanding relationships between ligands and all possible biological targets have emerged in recent years. Proteins are connected to each other based on the similarity of their ligands or based on the similarity of their binding sites. The assumption is that compounds sharing chemical similarity should share targets and that targets with a similar binding site should also share ligands. A large number of computational techniques have been developed to assess ligand and binding site similarity, which can be used to mike quantitative predictions of the most probable biological target of a given compound. This review covers the recent advances in new computational methods for relating biological targets based on the similarity of their binding sites. Binding site comparisons are used for the prediction of their most likely ligands, their possible cross reactivity and selectivity. These comparisons can also be used to infer the function of novel uncharacterized proteins.
引用
收藏
页码:1971 / 1979
页数:9
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