Bolz Sarah Naomi, Schroeder Michael
Biotechnology Center (BIOTEC), CMCB, Technische Universität Dresden, Dresden, Germany.
Expert Opin Drug Discov. 2023 Jul-Dec;18(9):973-985. doi: 10.1080/17460441.2023.2239700. Epub 2023 Jul 25.
Promiscuity denotes the ability of ligands and targets to specifically interact with multiple binding partners. Despite negative aspects like side effects, promiscuity is receiving increasing attention in drug discovery as it can enhance drug efficacy and provides a molecular basis for drug repositioning. The three-dimensional structure of ligand-target complexes delivers exclusive insights into the molecular mechanisms of promiscuity and structure-based methods enable the identification of promiscuous interactions. With the recent breakthrough in protein structure prediction, novel possibilities open up to reveal unknown connections in ligand-target interaction networks.
This review highlights the significance of structure in the identification and characterization of promiscuity and evaluates the potential of protein structure prediction to advance our knowledge of drug-target interaction networks. It discusses the definition and relevance of promiscuity in drug discovery and explores different approaches to detecting promiscuous ligands and targets.
Examination of structural data is essential for understanding and quantifying promiscuity. The recent advancements in structure prediction have resulted in an abundance of targets that are well-suited for structure-based methods like docking. In silico approaches may eventually completely transform our understanding of drug-target networks by complementing the millions of predicted protein structures with billions of predicted drug-target interactions.
多配体性是指配体和靶点与多个结合伴侣特异性相互作用的能力。尽管存在副作用等负面影响,但多配体性在药物研发中受到越来越多的关注,因为它可以提高药物疗效,并为药物重新定位提供分子基础。配体 - 靶点复合物的三维结构为多配体性的分子机制提供了独特的见解,基于结构的方法能够识别多配体相互作用。随着蛋白质结构预测的最新突破,揭示配体 - 靶点相互作用网络中未知联系的新可能性出现了。
本综述强调了结构在多配体性识别和表征中的重要性,并评估了蛋白质结构预测在推进我们对药物 - 靶点相互作用网络认识方面的潜力。它讨论了多配体性在药物研发中的定义和相关性,并探索了检测多配体性配体和靶点的不同方法。
检查结构数据对于理解和量化多配体性至关重要。结构预测的最新进展产生了大量适合基于对接等结构方法的靶点。通过用数十亿个预测的药物 - 靶点相互作用补充数百万个预测的蛋白质结构,计算机模拟方法最终可能会彻底改变我们对药物 - 靶点网络的理解。