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

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 蛋白质结构既可以通过实验方法，如X射线结晶学和核磁共振技术确定，也可以通过理论方法，如蛋白质折叠和同源建模来确定。然而，许多确定的蛋白质结构通常不像期望的那样准确。因此，它们在重要领域的应用受到了严重的限制，而结构的改进一直是重要的和关键的。近几十年来，PDB数据库中测定和存储的高分辨蛋白质结构的数量不断增加，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，我们提出了一种基于知识的蛋白质结构精化方法。从2007年到2008年，我们做了以下工作。除了研究成对原子间距的距离分布外，我们还研究了侧链扭转角Cb-Ca-Ca-Cb，其中许多都有显著的分布。统计分析本质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Web服务(www.wku edu/~di.wu/psd)，使这种带有统计分析的几何特征可以访问，并有助于蛋白质模型的精化和分析。一份相关报告正在编写中，并将在生物信息学相关会议上提交。我们还开发了一种用于结构优化的计算方法。由距离分布和二面角分布得到的附加统计势可以合并到经验能量函数中。我们将这种想法专门应用于具有无序区的X射线结构，结果表明，通过使用额外的统计势，可以极大地精化这些区域。利用所获得的结果，我们已经为蛋白质结构优化项目提交了NIH R15拨款提案。我们还计划完成 2008-2009年的几件事，包括在晶体结构的无序区进行了大量的样品建模，并在核磁共振结构精细化和晶体结构精细化中使用了扭转角导出势。将编写一份更详细的报告并提交，以便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.