University of Pittsburgh.
Brief Bioinform. 2021 Jul 20;22(4). doi: 10.1093/bib/bbaa239.
Delineating the fingerprint or feature vector of a receptor/protein will facilitate the structural and biological studies, as well as the rational design and development of drugs with high affinities and selectivity. However, protein is complicated by its different functional regions that can bind to some of its protein partner(s), substrate(s), orthosteric ligand(s) or allosteric modulator(s) where cogent methods like molecular fingerprints do not work well. We here elaborate a scoring-function-based computing protocol Molecular Complex Characterizing System to help characterize the binding feature of protein-ligand complexes. Based on the reported receptor-ligand interactions, we first quantitate the energy contribution of each individual residue which may be an alternative of MD-based energy decomposition. We then construct a vector for the energy contribution to represent the pattern of the ligand recognition at a receptor and qualitatively analyze the matching level with other receptors. Finally, the energy contribution vector is explored for extensive use in similarity and clustering. The present work provides a new approach to cluster proteins, a perspective counterpart for determining the protein characteristics in the binding, and an advanced screening technique where molecular docking is applicable.
描绘受体/蛋白质的指纹或特征向量将有助于结构和生物学研究,以及具有高亲和力和选择性的药物的合理设计和开发。然而,蛋白质的不同功能区域使其变得复杂,这些区域可以与某些蛋白质伴侣、底物、正构配体或变构调节剂结合,而分子指纹等有力方法在这种情况下效果不佳。我们在这里详细阐述了一种基于评分函数的计算协议——分子复合物特征系统,以帮助描述蛋白质-配体复合物的结合特征。基于报道的受体-配体相互作用,我们首先量化每个可能是基于 MD 的能量分解的替代方法的单个残基的能量贡献。然后,我们为能量贡献构建一个向量,以表示配体在受体上的识别模式,并定性分析与其他受体的匹配程度。最后,探索能量贡献向量在相似性和聚类中的广泛应用。本工作为聚类蛋白质提供了一种新方法,为确定结合中的蛋白质特征提供了一个视角,为分子对接适用的筛选技术提供了一种先进的方法。