Activation Pathways of Neurotensin Receptor 1 Elucidated Using Statistical Machine Learning

被引:5
|
作者
Yadav, Prakarsh [2 ]
Farimani, Amir Barati [1 ]
机构
[1] Carnegie Mellon Univ, Dept Mech Engn, Biomed Engn Chem Engn & Machine Learning, Pittsburgh, PA 15213 USA
[2] Carnegie Mellon Univ, Dept Mech Engn, Pittsburgh, PA 15213 USA
来源
ACS CHEMICAL NEUROSCIENCE | 2022年 / 13卷 / 08期
基金
美国安德鲁·梅隆基金会;
关键词
neurotensin receptor; machine learning; conformational changes; activation mechanism; STRUCTURAL INSIGHTS; MOLECULAR-DYNAMICS;
D O I
10.1021/acschemneuro.2c00154
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
: Neurotensin receptor 1 (NTSR1) is a G-protein coupled receptor (GPCR) that mediates many biological processes through its interaction with the neurotensin (NTS) peptide. The NTSR1 protein is a clinically significant target as it is involved in the proliferation of cancer cells. Understanding the activation mechanism of NTSR1 is an important prerequisite for exploring the therapeutic potential of targeting NTSR1 and the development of drug molecules specific to NTSR1. Previous studies have been aimed at elucidating the structure of NTSR1 in the active and inactive conformations; however, the intermediate molecular pathway for NTSR1 activation dynamics is largely unknown. In this study, we performed extensive molecular dynamics (MD) simulations of the NTSR1 protein and analyzed its kinetic conformational changes to determine the microswitches that drive NTSR1 activation. To biophysically interpret the high-dimensional simulation trajectories, we used Markov state models and machine learning to elucidate the important and detailed conformational changes in NTSR1. Through the analysis of identified microswitches, we propose a mechanistic pathway for NTSR1 activation.
引用
收藏
页码:1333 / 1341
页数:9
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