In Silico 3 D Structure Prediction of Activated GPCRs as a Drug Target
In Silico 3 D Structure Prediction of Activated GPCRs as a Drug Target
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作为药物靶点的激活 GPCR 的计算机三维结构预测
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通讯作者：
Takanori Harada
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作者：
Y. Ishino;Takanori Harada
本文介绍了一种预测g蛋白偶联受体（gpcr）生物活性结构的新方法，该方法具有较高的准确性，可用于计算机虚拟筛选。我们提出了一种模拟GPCR热波动的新方法，通过结合不同时间尺度上的波动来模拟蛋白质的构象变化。该方法的核心思想是通过分子动力学模拟，在皮秒或纳秒时间尺度上计算出GPCR蛋白各原子在热波动下的平均三维坐标，然后通过包含受体-配体对接模拟功能的进化计算，确定GPCR蛋白各螺旋在更宽时间尺度上的旋转角度。用人白三烯B4受体BLT1作为GPCR样本，对该方法进行了验证。我们的研究表明，所建立的方法能够提供激活GPCR的适当3D结构，以与其激动剂对接。KeywordsGPCR;蛋白质结构预测；进化计算;受体-配体对接仿真；分子动力学模拟
This paper describes a novel method to predict the biologically activated structures of G-protein-coupled receptors (GPCRs) with high accuracy so that the structures predicted can be used in in silico virtual screening. We propose a new method for modeling GPCR thermal fluctuations, where conformation changes of the proteins are modeled by combining fluctuations on different time scales. The core idea of the method is that a molecular dynamics simulation is used to calculate an average 3D coordinates of all atoms of a GPCR protein against heat fluctuation on the picosecond or nanosecond time scale, and then the evolutionary computation including receptor-ligand docking simulations functions to determine the rotation angle of each helix of a GPCR protein as a movement on wider time scale. The method was validated using human leukotriene B4 receptor BLT1 as a sample GPCR. Our study demonstrated that the established method was able to provide the appropriate 3D structure of the activated GPCR to dock with its agonists. KeywordsGPCR; protein structure prediction; evolutionary computation; receptor-ligand docking simulation; molecular dynamics simulation
影响因子：
56.9
作者：
V. Cherezov;D. Rosenbaum;M. Hanson;S. Rasmussen;Foon Sun Thian;T. S. Kobilka;Hee-Jung Choi;P. Kuhn-P
通讯作者：
V. Cherezov;D. Rosenbaum;M. Hanson;S. Rasmussen;Foon Sun Thian;T. S. Kobilka;Hee-Jung Choi;P. Kuhn-P
影响因子：
56.9
作者：
Palczewski, K;Kumasaka, T;Miyano, M
通讯作者：
Miyano, M