Polypharmacology rescored: Protein-ligand interaction profiles for remote binding site similarity assessment

被引:99
作者
Salentin, Sebastian [1 ]
Haupt, V. Joachim [1 ]
Daminelli, Simone [1 ]
Schroeder, Michael [1 ]
机构
[1] Tech Univ Dresden, Biotechnol Ctr BIOTEC, Dresden, Germany
关键词
Fingerprints; Profiling; Binding site similarity; Drug repositioning; Polypharmacology; Protein-ligand interactions; MOLECULAR INTERACTION FINGERPRINTS; CATION-PI INTERACTIONS; RATIONAL DRUG DESIGN; HYDROGEN-BONDS; INTERACTION INFORMATION; SCORING FUNCTIONS; COMPLEXES; ALIGNMENT; DOCKING; DISCOVERY;
D O I
10.1016/j.pbiomolbio.2014.05.006
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Detection of remote binding site similarity in proteins plays an important role for drug repositioning and off-target effect prediction. Various non-covalent interactions such as hydrogen bonds and van-der-Waals forces drive ligands' molecular recognition by binding sites in proteins. The increasing amount of available structures of protein-small molecule complexes enabled the development of comparative approaches. Several methods have been developed to characterize and compare protein ligand interaction patterns. Usually implemented as fingerprints, these are mainly used for post processing docking scores and (off-)target prediction. In the latter application, interaction profiles detect similarities in the bound interactions of different ligands and thus identify essential interactions between a protein and its small molecule ligands. Interaction pattern similarity correlates with binding site similarity and is thus contributing to a higher precision in binding site similarity assessment of proteins with distinct global structure. This renders it valuable for existing drug repositioning approaches in structural bioinformatics. Current methods to characterize and compare structure-based interaction patterns both for protein-small-molecule and protein protein interactions as well as their potential in target prediction will be reviewed in this article. The question of how the set of interaction types, flexibility or water-mediated interactions, influence the comparison of interaction patterns will be discussed. Due to the wealth of protein ligand structures available today, predicted targets can be ranked by comparing their ligand interaction pattern to patterns of the known target. Such knowledge-based methods offer high precision in comparison to methods comparing whole binding sites based on shape and amino acid physicochemical similarity. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:174 / 186
页数:13
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