Theoretical Analysis of Slow Motions in Proteins

9603556贾德茨基这项研究的目标是(1)建立一个物理模型，将蛋白质骨架的运动与NH和CH键向量的自相关函数的集合平均值联系起来，这些自相关函数是用核磁共振测量的。为了克服计算蛋白质分子动力学的时间限制(1 Ns)，将使用二面角空间中随机行走的分子动力学--最近由赵和Jardezky提出的MCDIS-MD(蒙特卡罗二面角空间分子动力学)方法。基于研究人员的理论结果的相关函数将从轨迹中计算出来，这些函数可以被傅里叶变换为谱密度函数。还将构造各种二面角之间的概率分布和修正矩阵。(2)利用Lefevre等人发展的形式主义，通过对松弛数据的详细分析来确定相关的时间尺度。还有金和贾德斯基。选择了三种已经有大量松弛数据的蛋白质进行初步分析：溶菌酶、葡萄球菌核酸酶和色氨酸抑制因子。(3)使用Hoch的渗流形式来识别反映构象转变的轨道簇，并将从每个簇计算的光谱密度项与独立从实验得出的光谱密度项进行匹配。对能够解释核磁共振数据中慢动作项的运动类型进行建模将是对蛋白质动力学理解的重大进步。将蛋白质理解为一种分子机制--它确实是这样--需要对其结构和动力学的详细和准确的知识。到目前为止，蛋白质结构的知识已经非常广泛--超过1000个原子分辨率的结构已经通过X射线和核磁共振确定。相比之下，关于蛋白质动力学的知识仍然相当零碎。S对蛋白质运动的理论分子动力学模拟对理解蛋白质有很大的贡献，但由于理论和实践的原因，仍然局限于对非常快(皮纳秒)运动的研究。为了解释核磁共振弛豫和质子交换测量中包含的关于慢运动(在纳秒到微秒或更长时间尺度上)的信息，必须使用更强大的统计机械工具，例如根据本赠款条款开发的MCDIS-MD方法。

9603556 Jardetzky The goal of this research is to (1) To develop a physical model to relate the motion of the protein backbone to the ensemble average of auto-correlation functions for NH and CH bond vectors, which are measured using NMR. In order to overcome the time limit (1 ns) on calculating molecular dynamics of proteins, molecular dynamics with random walks in dihedral angle space - the MCDIS-MD (Monte Carlo in Dihedral Angle Space with Molecular Dynamics) procedure recently reported by Zhao and Jardetzky will be used. Correlation functions based on the investigator's theoretical results will be calculated from the trajectory, which can be Fourier transformed to spectral density functions. Probability distribution and correction matrices among the various dihedral angles will also be constructed. (2) To identify relevant time scales by carrying out a detailed analysis of relaxation data, using the formalisms developed by Lefevre et al. and King and Jardetsky. Three proteins on which extensive relaxation data are already available are chosen for the initial analysis: lysozyme staphylococcal nuclease and trp-repressor. (3) To use the percolation formalism of Hoch to identify clusters of trajectories that reflect conformational transitions that may be expected to be slow and to match the spectral density terms calculated from each cluster against the spectral density terms independently derived from experiment. Modeling the types of motions that can account for the slow motion terms in NMR data would be a significant advance in the understanding of protein dynamics. Understanding a protein as a molecular mechanism - which it is - requires detailed and accurate knowledge of its structure and dynamics. Knowledge of protein structure is by now very extensive - over 1000 structures at atomic resolution have been determined by x-ray and NMR. In contrast, knowledge of protein dynamics is still rather fragmentary. Theoretical Molecular Dynamics simulation s of protein motions have contributed greatly to the understanding of proteins, but remain limited to the study of very fast (piconanosecond) motions for both theoretical and practical reasons. To interpret the information on slow motions ( on nano-to microsecond or longer time scales) contained in NMR relaxation and proton exchange measurements, more powerful statistical mechanical tools must be applied, such as the MCDIS-MD method to be developed under the terms of this grant.