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

G蛋白偶联受体(GPCRs)是当今最重要的药物靶蛋白之一。然而，由于GPCRs很难结晶，除了少数蛋白质外，GPCRs的三维结构还没有得到X射线结晶学的确定。此外，由于GPCRs结构的巨大波动，在计算上预测GPCRs的准确构象是有限的，该研究发展了一种新的GPCR热涨落建模方法，该方法通过在多个时间尺度上组合涨落来模拟蛋白质的构象变化。这项研究提出了一种新的方法，通过使用包括受体-配体对接模拟在内的进化计算，从各种波动的候选结构中预测GPCR的最佳3D结构。以人白三烯B4受体BLT1为样本，对该方法进行了验证。

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.