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揭示神经降压素受体 1 的分级激活机制。

Revealing the graded activation mechanism of neurotensin receptor 1.

机构信息

College of Chemistry and Life Science, Beijing University of Technology, Beijing, China.

Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, School of Pharmacy, Chengdu University, Chengdu, China.

出版信息

Int J Biol Macromol. 2024 Oct;278(Pt 1):134488. doi: 10.1016/j.ijbiomac.2024.134488. Epub 2024 Aug 5.

Abstract

Graded activation contributes to the precise regulation of GPCR activity, presenting new opportunities for drug design. In this work, a total of 10 μs enhanced-sampling simulations are performed to provide molecular insights into the binding dynamics differences of the neurotensin receptor 1 (NTSR1) to the full agonist SRI-9829, partial agonist RTI-3a and inverse agonist SR48692. The possible graded activation mechanism of NTSR1 is revealed by an integrated analysis utilizing the reweighted potential of mean force (PMF), deep learning (DL) and transfer entropy (TE). Specifically, the orthosteric pocket is observed to undergo expansion and contraction, with the G-protein-binding site experiencing interconversions among the inactive, intermediate and active-like states. Detailed structural comparisons capture subtle conformational differences arising from ligand binding in allosteric signaling, which can well explain the graded activation. Critical microswitches that contribute to graded activation are efficiently identified with the DL model. TE calculations enable the visualization of allosteric communication networks within the receptor, elucidating the driver-responder relationships associated with signal transduction. Fortunately, the dissociation of the full agonist from the orthosteric pocket is observed. The current findings systematically reveal the mechanism of NTSR1 graded activation, and also provide implications for structure-based drug design.

摘要

分级激活有助于精确调节 G 蛋白偶联受体(GPCR)的活性,为药物设计带来了新的机会。在这项工作中,我们进行了总计 10 μs 的增强采样模拟,以提供对神经降压素受体 1(NTSR1)与完全激动剂 SRI-9829、部分激动剂 RTI-3a 和反向激动剂 SR48692 结合动力学差异的分子见解。通过利用重加权平均力势(PMF)、深度学习(DL)和转移熵(TE)的综合分析,揭示了 NTSR1 可能的分级激活机制。具体来说,观察到正位口袋经历扩张和收缩,G 蛋白结合位点在非活性、中间和类似活性状态之间发生转换。详细的结构比较捕捉到了变构信号中配体结合引起的细微构象差异,这可以很好地解释分级激活。利用 DL 模型有效地识别了有助于分级激活的关键微开关。TE 计算能够可视化受体内部的变构通讯网络,阐明与信号转导相关的驱动-响应关系。幸运的是,观察到完全激动剂从正位口袋的解离。目前的研究结果系统地揭示了 NTSR1 分级激活的机制,并为基于结构的药物设计提供了启示。

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