PROTEIN STRUCTURE MODELING USE BOTH EVOLUTIONARY RELATIONSHIPS AND PHYSICS-BA

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目及 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。 结构基因组计划旨在将所有蛋白质序列置于“建模”中， “距离”是一个已知的结构。 为了充分利用这种爆炸性的 信息，基于模板结构的蛋白质结构预测将 需要改进。 在研究蛋白质同源性建模的过程中， 高级别小组第五轮严格评估的程序 蛋白质结构预测（CASP 5）以及我们自己的一些程序， 我们发现了一些方法， 结构预测 由于蛋白质序列与 未知结构（靶标）和已知结构的蛋白质序列 (the模板）降低，序列比对方法的性能 目标和模板也减少。 这种下降尤其明显， 序列同一性低于~ 35%。 如果正确的序列比对可以 实现，然后可以大大更好的蛋白质结构模型， 构建了 这些更好的模型使它们更有可能 使用基于物理的模型进行改进，或者通过基于低分辨率网格的 模型、全原子分子力学（MM）模型或两者。实现这些 为了实现这些目标，我们首先选择构建一个结构预测“管道”， 只需要最少的步骤。 这将确保每一步都可以在以后 以确定如何推进该方法。 下面显示的流程图 揭示了我们将在今年夏天的CASP 6中使用和测试的方法。 程序 “probA”用于生成替代比对。 通常，我们将输出 100-500个备选路线。 从这些排列中，结构模型 使用MODELLER 6.2版程序构建。 这些结构模型是 然后用ProsaII中存在的统计潜力进行评估， 他人 Perl脚本已经被编写来实现程序之间的流。 然后对具有最低对相互作用能的模型进行目视检查 关于VMD 模型中不是从模板生成的循环区域，或 然后使用以下方法精制其它不良形成的二级结构元件： 使用MMTSB工具集增强采样方法。 （关于蛋白质的研讨会） 年夏天，在PSC举行了使用工具集进行结构预测的会议。 （2003年） 这些增强的采样方法包括模拟退火的 初始结构的集合或复制交换模拟。 的能量 的结果结构，然后将计算与MM-广义 天生的潜力和集群，以确定结构最接近的天然。 初步结果可在www.psc.edu/biomed/research/biostr上查阅。 随着我们的专业知识随着这些软件包的增加，我们将开始 自动化这个过程，着眼于开发一个用户网关， 一般研究社会快速有效地发展合理 基于同源性的分子模型。目前，A 提供这些服务的站点数量，之前CASP的结果 实验已经清楚地表明，多重序列的质量 对准加上次优对准的识别导致 上级结果。因此，我们希望这条管道是有效的。

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. Structural genomic programs aim to place all protein sequences within "modeling distance" of a known structure. To take full advantage of this explosion of information, protein structure predictions based on template structures will need to be improved. In the course of examining protein homology modeling procedures of high-ranking groups from Round 5 of the Critical Assessment of Structure Prediction of Proteins (CASP5) as well as some procedures of our own, we recognized some methods that may advance this particular area of protein structure prediction. As the sequence identity between a protein sequence with unknown structure (the target) and the protein sequence with known structure (the template) decreases, the performance of sequence alignment methods between target and template also decreases. This decrease is particularly notable when the sequence identity goes below ~35%. If a correct sequence alignment could be achieved, then considerably better protein structural models could be constructed. These better models make it more likely that they can then be refined with physics-based models, either through low-resolution lattice based models, all-atom molecular mechanical (MM) models or both. To achieve these goals, we first chose to construct a structure prediction "pipeline" that required a minimal amount of steps. This would insure that each step can later be examined to determine ways to advance the method. The flowchart shown below reveal the methods we will using and testing this summer in CASP6. The program "probA" is used to generate alternative alignments. Typically we will output 100-500 alternative alignments. From these alignments, structural models are constructed with the program MODELLER version 6.2. These structural models are then assessed with the statistical potentials present in ProsaII and possibly others. Perl scripts have been written to enable the flow between programs. The models with the lowest pair interaction energy are then visually examined with VMD. Loop regions in the model that are not built from the template or other poorly formed secondary structure elements will then be refined using enhanced sampling methods with the MMTSB toolset. (A workshop on protein structure prediction using the toolset was held at the PSC in the summer of 2003.) These enhanced sampling methods include simulated annealing of an ensemble of initial structures or replica-exchange simulations. The energies of the resulting structures will then be calculated with the MM-Generalized Born potential and clustered to determine structures closest to the native. Initial results are available at www.psc.edu/biomed/research/biostr. As our expertise increases with these software packages, we will begin automating this process with an eye towards developing a user gateway to allow the general research community to quickly and effectively develop reasonable homology-based molecular models for their systems. While there are currently a number of sites offering these services, the results from prior CASP experiments have clearly shown that the quality of the multiple sequence alignment coupled with the identification of suboptimal alignments leads to superior results. Thus, we expect this pipeline to be effective.