MULTI-SCALE PROTEIN STRUCTURE MODELING SIMULATION, AND PREDICTION

多尺度蛋白质结构建模模拟和预测

• 批准号: 7723274
• 负责人: JIANPENG MA
• 金额: $ 0.05万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7723274
• 关键词: Amino Acid Sequence; Area; Biophysics; Cell physiology; Complex; Computational Technique; Computer Retrieval of Information on Scientific Projects Database; Computer software; Data; Drug Design; F1-ATPase; Funding; Grant; Institution; Length; Methods; Modeling; Molecular; Motion; Movement; Numbers; Play; Protein Dynamics; Proteins; Research; Research Personnel; Resolution; Resources; Roentgen Rays; Role; Solutions; Source; Structure; System; Temperature; Tertiary Protein Structure; United States National Institutes of Health; X-Ray Crystallography; base; chaperonin; conformational conversion; insight; models and simulation; molecular dynamics; programs; protein structure; protein structure prediction; simulation; structural biology; structural genomics; success; vector

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. The proposed research involves four projects, described below, related to protein structure modeling, simulation, and prediction: (1) MULTI-RESOLUTION AND MULTI-LENGTH-SCALE SIMULATION OF SUPERMOLECULAR COMPLEXES: Large-scale conformational transitions in protein structures play an important role in a variety of cellular processes. Understanding such transitions is a central task of modern biophysics and structural biology. This project applies molecular dynamics simulation to model the motions of systems that involve coordinated large domain movements, such as the molecular chaperonin GroEL and F1-ATPase. (2) STRUCTURAL REFINEMENT FOR X-RAY CRYSTALLOGRAPHY USING NORMAL MODES: Traditional crystallographic refinement on X-ray data of proteins is limited by the enormous number of parameters required to describe the thermal fluctuations of the atoms. The use of normal mode vectors can significantly reduce the meaningful parameter set because the normal modes represent the intrinsic motions of the protein. This project aims to develop a software program that employs normal modes for crystallographic refinement. In addition to the benefits of reduced computational complexity, the normal mode model will provide more insight into protein dynamics because the anisotropic temperature factors calculated from the normal modes capture the motion inherent in the structure of the protein. (3) TOP-DOWN APPROACH TO PROTEIN STRUCTURE PREDICTION: Protein structure prediction is one of the most challenging areas in theoretical biophysics, and it plays an essential role in structural genomics and rational drug design. We recently developed OPUS, a conceptually new method that employs multi-scale, multi-layer and top-down prediction strategies. OPUS combines template-based and de novo methods to predict 3D protein structures from primary sequences. (4) PROTEIN DOMAIN RECOGNITION: Protein domain recognition is valuable for protein structure analysis, as it enables large proteins to be broken down into smaller, more palatable sub-structures that can be solved by experimental or computational techniques. Our ab initio domain recognition method has already demonstrated remarkable success in determining protein domain boundaries. This study aims to extend the prediction accuracy of the ab initio method by using a variety of experimental constraints, such as X-ray solution scattering data.

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。 建议的研究涉及四个项目，与蛋白质结构建模、模拟和预测有关：(1)超分子复合体的多分辨率和多长度尺度模拟：蛋白质结构中的大规模构象转变在各种细胞过程中发挥着重要作用。理解这种转变是现代生物物理学和结构生物学的中心任务。这个项目应用分子动力学模拟来模拟涉及协调的大域运动的系统的运动，例如分子伴侣GroEL和F1-ATPase。(2)正常模式下的X射线结晶学结构精化：传统的蛋白质X射线数据结晶学精化受到描述原子热涨落所需的大量参数的限制。使用简正模式向量可以显著减少有意义的参数集，因为简正模式代表了蛋白质的内在运动。这个项目的目的是开发一个软件程序，使用普通模式进行晶体细化。除了降低计算复杂性的好处外，简正模式模型还将提供对蛋白质动力学的更多洞察，因为从简正模式计算的各向异性温度因子捕获了蛋白质结构中固有的运动。(3)自上而下的蛋白质结构预测方法：蛋白质结构预测是理论生物物理学中最具挑战性的领域之一，在结构基因组学和合理的药物设计中起着至关重要的作用。我们最近开发了OPUS，这是一种概念上的新方法，采用了多尺度、多层和自上而下的预测策略。OPUS结合了基于模板的方法和从头开始的方法来预测初级序列中的3D蛋白质结构。(4)蛋白质结构域识别：蛋白质结构域识别对于蛋白质结构分析很有价值，因为它可以将大的蛋白质分解成更小、更容易接受的亚结构，这些亚结构可以通过实验或计算技术来解决。我们的从头算结构域识别方法已经在确定蛋白质结构域边界方面取得了显著的成功。本研究旨在利用各种实验约束条件，如X射线溶液散射数据，扩展从头算方法的预测精度。