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使用有监督分子动力学模拟深入了解腺苷 A1 受体拮抗剂选择性的关键决定因素。

New Insights into Key Determinants for Adenosine 1 Receptor Antagonists Selectivity Using Supervised Molecular Dynamics Simulations.

机构信息

Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, via Marzolo 5, 35131 Padova, Italy.

School of Life Sciences, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK.

出版信息

Biomolecules. 2020 May 7;10(5):732. doi: 10.3390/biom10050732.

Abstract

Adenosine receptors (ARs), like many otherGprotein-coupledreceptors (GPCRs), are targets of primary interest indrug design. However, one of the main limits for the development of drugs for this class of GPCRs is the complex selectivity profile usually displayed by ligands. Numerous efforts have been madefor clarifying the selectivity of ARs, leading to the development of many ligand-based models. The structure of the AR subtype A (AAR) has been recently solved,providing important structural insights. In the present work, we rationalized the selectivity profile of two selective AAR and AAR antagonists, investigating their recognition trajectories obtained by Supervised Molecular Dynamics from an unbound state and monitoring the role of the water molecules in the binding site.

摘要

腺苷受体 (ARs) 与许多其他 G 蛋白偶联受体 (GPCRs) 一样,是药物设计的主要目标。然而,此类 GPCR 配体的药物开发的主要限制之一是其复杂的选择性特征。为了阐明 ARs 的选择性,人们已经做出了许多努力,从而开发出了许多基于配体的模型。AR 亚型 A (AAR) 的结构最近已经被解析,提供了重要的结构见解。在本工作中,我们从无结合状态出发,通过有监督的分子动力学来研究两种选择性 AAR 和 AAR 拮抗剂的识别轨迹,以此来合理化它们的选择性特征,并监测结合位点中水分子的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6536/7278174/c149e0787b1b/biomolecules-10-00732-g001.jpg

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