PROTEIN STRUCTURAL REFINEMENT USING COARSE-GRAINED MODELS OVER HIGH PERF COMPUT

这个子项目是许多利用 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 蛋白质结构可以通过实验方法，如X射线晶体学和核磁共振（NMR）技术，或理论方法，如蛋白质折叠和同源建模来确定。然而，许多确定蛋白质结构的方法通常不像所期望的那样精确。因此，它们在重要领域的应用受到严重限制，结构细化一直是重要和关键的。近几十年来，PDB数据库中高分辨率蛋白质结构的确定和存储数量不断增加，这使得在结构数据库中进行统计分析成为可能。在这个项目中，我们提出了一个基于知识的蛋白质结构优化方法。2007-2008年，我们完成了以下工作。除了研究原子间距离的分布外，我们还研究了侧链扭转角Cb-Ca-Ca-Cb，其中许多具有显著的分布。统计分析基本上是这个项目中最重要的一步，我们还开发了一个用户友好的蛋白质结构建模社区的Web服务（www.wku.edu/~di.wu/psd），这样的几何特性与统计分析可以访问和有用的蛋白质模型的细化和分析。 正在编写一份相关报告，将在生物信息学相关会议上提出。我们还开发了一个计算方法的结构细化。从距离和二面角分布导出的额外统计势可以并入经验能量函数中。我们应用这种想法，特别是在X射线结构的无序区域和结果表明，这样的区域可以大大细化与采用额外的统计势。 使用所获得的结果，我们已经提交了NIH R15拨款建议的蛋白质结构的细化项目。我们还计划完成 2008-2009年的一些事情，包括在模拟晶体结构的无序区域中进行大量样品，以及在NMR结构精修和晶体结构精修中采用扭转角导出势。将编写一份更详细的报告，并提交今后在其他地方出版。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Protein structures can be determined through either experimental methods, such as X-ray crystallography and Nuclear Magnetic Resonance (NMR) technology, or theoretical methods, such as protein folding and homology modeling. However, many of determine protein structures are usually not as accurate as desired. Therefore, their applications have been severely limited in important fields, and structure refinement is always important and critical. In recent decades, the number of high resolution protein structures determined and deposited in PDB database is increasing, which makes it possible to conduct statistical analysis in the structural database. In this project, we propose a knowledge-based approach for protein structure refinement. From 2007-2008, we have finished the following work. Besides studying distance distributions of pair wise inter-atomic distances, we have studied side chain torsion angles Cb-Ca-Ca-Cb and many of them have significant distributions. The statistical analysis is essentially the most important step in this project, and also we have developed a user-friendly web service for protein structure modeling community ( www.wku.edu/~di.wu/psd ) so that such geometric prosperities with statistical analysis can be accessible and useful for refinement and analysis of protein models. A related report is in preparation and will be presented in bioinformatics related conferences. We have also developed a computational approach for structure refinement. Additional statistical potentials derived from distributions of distances and dihedral angles can be incorporated into the empirical energy function. We applied such idea specifically on X-ray structures with disorder regions and results have shown that such regions can be greatly refined with employing additional statistical potentials. Using obtained results, we have submitted a NIH R15 grant proposal for the project of protein structure refinement. We also plan to finish a few things from 2008-2009, including conducting a large number of samples in modeling disorder regions of crystal structures and employing torsion angle derived potentials in NMR structure refinement and crystal structure refinement. A more detailed report will be prepared and submitted for publication elsewhere in the future.