Promiscuity in drug discovery on the verge of the structural revolution: recent advances and future chances

被引:4
作者
Bolz, Sarah Naomi [1 ]
Schroeder, Michael [1 ,2 ]
机构
[1] Tech Univ Dresden, Biotechnol Ctr BIOTEC, CMCB, Dresden, Germany
[2] Tech Univ Dresden, Biotechnol Ctr BIOTEC, CMCB, Tatzberg 47-49, D-01307 Dresden, Germany
关键词
drug discovery; promiscuity; polypharmacology; drug repositioning; multi-target drug; protein structure prediction; structural bioinformatics; structure-based; ASSAY INTERFERENCE COMPOUNDS; PROTEIN-STRUCTURE; TARGET IDENTIFICATION; SCALE PREDICTION; WEB SERVER; BINDING; DOCKING; POLYPHARMACOLOGY; LIGANDS; PERSPECTIVE;
D O I
10.1080/17460441.2023.2239700
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
IntroductionPromiscuity 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.Areas coveredThis 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.Expert opinionExamination 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.
引用
收藏
页码:973 / 985
页数:13
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