Salentin Sebastian, Haupt V Joachim, Daminelli Simone, Schroeder Michael
Biotechnology Center (BIOTEC), TU Dresden, Dresden, Germany.
Biotechnology Center (BIOTEC), TU Dresden, Dresden, Germany.
Prog Biophys Mol Biol. 2014 Nov-Dec;116(2-3):174-86. doi: 10.1016/j.pbiomolbio.2014.05.006. Epub 2014 Jun 9.
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.
检测蛋白质中远程结合位点的相似性对于药物重新定位和脱靶效应预测具有重要作用。各种非共价相互作用，如氢键和范德华力，驱动配体通过蛋白质中的结合位点进行分子识别。蛋白质 - 小分子复合物可用结构数量的增加推动了比较方法的发展。已经开发了几种方法来表征和比较蛋白质 - 配体相互作用模式。这些方法通常以指纹形式实现，主要用于对接分数的后处理和（脱）靶标预测。在后一种应用中，相互作用图谱检测不同配体结合相互作用中的相似性，从而识别蛋白质与其小分子配体之间的关键相互作用。相互作用模式相似性与结合位点相似性相关，因此有助于提高对具有不同整体结构的蛋白质结合位点相似性评估的精度。这使其对结构生物信息学中现有的药物重新定位方法具有价值。本文将综述目前用于表征和比较基于结构的相互作用模式（包括蛋白质 - 小分子和蛋白质 - 蛋白质相互作用）的方法，以及它们在靶标预测中的潜力。还将讨论相互作用类型集、灵活性或水介导的相互作用如何影响相互作用模式比较的问题。由于如今有大量的蛋白质 - 配体结构，通过将预测靶标的配体相互作用模式与已知靶标的模式进行比较，可以对预测靶标进行排名。与基于形状和氨基酸物理化学相似性比较整个结合位点的方法相比，这种基于知识的方法具有更高的精度。
