Prediction of 3D Structure of Drug Target GPCR Using Evolutionary Computation

使用进化计算预测药物靶标 GPCR 的 3D 结构

• 批准号: 23500376
• 负责人: ISHINO Yoko
• 金额: $ 3.49万
• 依托单位: Yamaguchi University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2011
• 资助国家: 日本
• 起止时间: 2011 至 2013
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-23500376/
• 关键词: 生命分子計算; 進化計算; バイオインフォマティクス

G-Protein coupled receptors (GPCRs) are one of the most important drug target proteins today. However, the 3D structures of GPCRs have not yet been determined by X-ray crystallography, except a few proteins, because GPCRs are difficult to crystallize. In addition, due to the huge structural fluctuation of GPCRs, there is a limitation to computationally predict GPCR's accurate conformation.This study developed a new method for modeling GPCR thermal fluctuations, where conformation changes of the proteins are modeled by combining fluctuations on multiple time scales. This study proposed a novel method which predicts a best 3D structure of a GPCR from a variety of fluctuating candidate structures, by using the evolutionary computation including receptor-ligand docking simulations. The method was validated using human leukotriene B4 receptor BLT1 as a sample GPCR.

G蛋白偶联受体（GPCR）是当今最重要的药物靶蛋白之一。然而，除了少数蛋白质外，GPCR的3D结构尚未通过X射线晶体学确定，因为GPCR难以结晶。此外，由于GPCR的结构起伏很大，计算预测其构象存在一定的局限性，本研究提出了一种新的GPCR热起伏模型，将多个时间尺度上的热起伏结合起来模拟蛋白质的构象变化。本研究提出了一种新的方法，预测一个最好的3D结构的GPCR从各种波动的候选结构，通过使用进化计算，包括受体-配体对接模拟。使用人白三烯B4受体BLT 1作为样品GPCR对该方法进行了验证。

项目成果

Research Trend of Technology Management

技术管理研究动态

• 发表时间: 2014
• 期刊: Journal on Innovation and Sustainability
• 作者: レラトーレイサ;廣橋義寛;伊藤栄祐;加藤毅;Yoko Ishino
• 通讯作者: Yoko Ishino

Effects of Word-of-Mouth Communication on Product Diffusion: A Case of Medical Insurance Product

口碑传播对产品扩散的影响：以医疗保险产品为例

• 发表时间: 2013
• 作者: Masashi Miyazaki;Yoko Ishino and Shingo Takahashi
• 通讯作者: Yoko Ishino and Shingo Takahashi

An Approach towards Medical Insurance Business Innovation Based on Japanese Customer Survey Data

基于日本客户调查数据的医疗保险业务创新途径

• 发表时间: 2012
• 作者: J. Ito;Y. Tabei;K. Shimizu;K.Tomii;K. Tsuda;八木 文香，瀬尾 隆;Yoko Ishino
• 通讯作者: Yoko Ishino

A Comprehensive Calibration Method for Improving Protein Identification Accuracy in Proteomics with ESI-TOF-MS

利用 ESI-TOF-MS 提高蛋白质组学蛋白质鉴定准确性的综合校准方法

• 发表时间: 2013
• 作者: Ryota Miyata;Toru Aonishi ;Koji Kurata;Yoko Ishino
• 通讯作者: Yoko Ishino

Impact of the Novel Protein Structure Prediction on R&D Process in Drug Discovery and Development

新蛋白质结构预测对 R 的影响

• 发表时间: 2011
• 作者: 田中良弥;鳥羽岳太;山元大輔;Yoko Ishino
• 通讯作者: Yoko Ishino