基于遗传结构知识的低分辨率结构解析方法的研究

Elucidating the biochemical function of the protein is one of the important topic in the post-genome era. The research on the protein function can provide direct support to the research of medical treatment, drug discovery and bio-material. The function of a protein is definitely determined by its 3D structure. The most popular approaches for obtaining a 3D protein structure are structure prediction and physics experiment. Through physics experiment, the accuracy of the obtained structure is higher, but the expense is also higher. On the contrary, through structure prediction, the accuracy is lower and the expense is lower. Therefore, how to combine these two approaches together to improve the efficiency of tackling a protein structure has already turned to a hot topic in the field of protein structure analysis. In this research, the model of structure prediction is going to be introduced to the process of tackling a protein structure through X-ray crystallography. The structure templates with genetically conserved structure information are generated from the structure prediction model. Then, the templates are applied to interprate the electron density map of the target protein by means of image processing approach. In this way, a highly accurate structure model of the target protein is expected. Moreover, this research places the focus on the structure analysis of the proteins with the important biochemical functions whose electron density maps are poor and difficult to interpret due to the limitation of the current experiment condition. The purpose of this research is enhancing the coverage of X-ray protein crystallography, lowering the expense of the experiments, shortening the period of obtaining a protein structure and making a new way in analyzing a protein structure through crystallography.

揭示各种蛋白质的生化功能是后基因组时代的重要课题之一。对蛋白质功能的研究可以为医疗,制药,生物材料等领域的研究提供直接的知识支持。蛋白质的功能是由其三维结构所决定的，获得蛋白质结构的方式可分为物理实验和模拟预测两种。通过物理实验获得的结构精确度高，但实验成本高。模拟预测的方法成本低，但结构精确度也低。如何将两者有效的结合起来，已成为结构解析这个包含多学科知识的交叉领域的热点研究之一。本项目将模拟预测的方法引入蛋白质结晶衍射方法中,利用结构预测方法提供的具有遗传保有性的结构模板信息，应用图像处理理论的相关方法对电子密度图进行解释，以达到获得高精度的蛋白质结构模型的目的。特别是对一些由于实验条件的限制，而难以获得质量理想的电子密度图且具有重要生化功能的蛋白质的结构解析。期望通过新方法的开发，扩大晶体衍射方法的适用范围，降低结构解析的成本，缩短解析的周期，为蛋白质晶体结构解析研究提供新的思路。

揭示各种蛋白质的生化功能是后基因组时代的重要课题之一。对蛋白质功能的研究可以为医疗,制药,生物材料等领域的研究提供直接的知识支持。蛋白质的功能是由其三维结构所决定的,获得蛋白质结构的方式可分为物理实验和模拟预测两种。在本项目中，我们将模拟预测的方法引入蛋白质结晶衍射方法中，取得了一些成果。首先，应用图像处理的方法，在多蛋白分子的电子密度图中，将单个的蛋白分子所占有的区域识别出来，在这方面的研究已经取得了一些进展；之后应用预测方法筛选适合蛋白序列的模板，这部分我们利用已有的预测软件来完成；而后应用这些模板对得到的蛋白分子电子密度图进行解释，这方面我们也取得了一些进展；最后，将整体方法应用于蛋白结构解析，我们用这类方法完成了一些蛋白分子结构的搭建和精密化。