Noonan Theresa, Denzinger Katrin, Talagayev Valerij, Chen Yu, Puls Kristina, Wolf Clemens Alexander, Liu Sijie, Nguyen Trung Ngoc, Wolber Gerhard
Department of Pharmaceutical and Medicinal Chemistry, Institute of Pharmacy, Freie Universität Berlin, Königin-Luise-Straße 2+4, D-14195 Berlin, Germany.
Pharmaceuticals (Basel). 2022 Oct 22;15(11):1304. doi: 10.3390/ph15111304.
G protein-coupled receptors (GPCRs) are amongst the most pharmaceutically relevant and well-studied protein targets, yet unanswered questions in the field leave significant gaps in our understanding of their nuanced structure and function. Three-dimensional pharmacophore models are powerful computational tools in in silico drug discovery, presenting myriad opportunities for the integration of GPCR structural biology and cheminformatics. This review highlights success stories in the application of 3D pharmacophore modeling to drug design, the discovery of biased and allosteric ligands, scaffold hopping, QSAR analysis, hit-to-lead optimization, GPCR de-orphanization, mechanistic understanding of GPCR pharmacology and the elucidation of ligand-receptor interactions. Furthermore, advances in the incorporation of dynamics and machine learning are highlighted. The review will analyze challenges in the field of GPCR drug discovery, detailing how 3D pharmacophore modeling can be used to address them. Finally, we will present opportunities afforded by 3D pharmacophore modeling in the advancement of our understanding and targeting of GPCRs.
G蛋白偶联受体（GPCRs）是与药物关系最为密切且研究最为深入的蛋白质靶点之一，但该领域尚未解决的问题使我们对其细微结构和功能的理解存在重大空白。三维药效团模型是计算机辅助药物发现中强大的计算工具，为整合GPCR结构生物学和化学信息学提供了无数机会。本综述重点介绍了三维药效团模型在药物设计、偏向性和别构配体发现、骨架跃迁、定量构效关系（QSAR）分析、苗头化合物到先导化合物的优化、GPCR去孤儿化、GPCR药理学机制理解以及配体-受体相互作用阐明等方面的成功案例。此外，还强调了在纳入动力学和机器学习方面的进展。本综述将分析GPCR药物发现领域的挑战，详细说明三维药效团模型如何用于应对这些挑战。最后，我们将展示三维药效团模型在增进我们对GPCRs的理解和靶向方面所带来的机会。
