Department of Pharmaceutical Sciences, Southern Illinois University, Edwardsville, IL 62026, United States.
Curr Top Med Chem. 2020;20(10):855-882. doi: 10.2174/1568026620666200226105312.
Drug discovery has focused on the paradigm "one drug, one target" for a long time. However, small molecules can act at multiple macromolecular targets, which serves as the basis for drug repurposing. In an effort to expand the target space, and given advances in X-ray crystallography, protein-protein interactions have become an emerging focus area of drug discovery enterprises. Proteins interact with other biomolecules and it is this intricate network of interactions that determines the behavior of the system and its biological processes. In this review, we briefly discuss networks in disease, followed by computational methods for protein-protein complex prediction. Computational methodologies and techniques employed towards objectives such as protein-protein docking, protein-protein interactions, and interface predictions are described extensively. Docking aims at producing a complex between proteins, while interface predictions identify a subset of residues on one protein that could interact with a partner, and protein-protein interaction sites address whether two proteins interact. In addition, approaches to predict hot spots and binding sites are presented along with a representative example of our internal project on the chemokine CXC receptor 3 B-isoform and predictive modeling with IP10 and PF4.
药物发现长期以来一直专注于“一种药物，一个靶点”的范式。然而，小分子可以作用于多个大分子靶点，这为药物再利用提供了基础。为了扩大靶点空间，并考虑到 X 射线晶体学的进步，蛋白质-蛋白质相互作用已成为药物发现企业的一个新兴重点领域。蛋白质与其他生物分子相互作用，正是这种错综复杂的相互作用网络决定了系统的行为及其生物过程。在这篇综述中，我们简要讨论了疾病网络，然后讨论了用于预测蛋白质-蛋白质复合物的计算方法。广泛描述了用于蛋白质-蛋白质对接、蛋白质-蛋白质相互作用和界面预测等目标的计算方法和技术。对接旨在产生蛋白质之间的复合物，而界面预测则识别一个蛋白质上可能与伴侣相互作用的残基子集，蛋白质-蛋白质相互作用位点则解决两个蛋白质是否相互作用。此外，还介绍了预测热点和结合位点的方法，并结合我们内部关于趋化因子 CXC 受体 3 B 亚型的项目和 IP10 和 PF4 的预测建模提供了一个代表性示例。
