Theoretical Analysis of Slow Motions in Proteins

本研究的目标是：(1)建立一个物理模型，将蛋白质骨架的运动与NMR测量的nhh和CH键向量的自相关函数的总体平均值联系起来。为了克服计算蛋白质分子动力学的时间限制（1 ns），我们将使用Zhao和Jardetzky最近报道的具有二面角空间随机行走的分子动力学程序MCDIS-MD （Monte Carlo In dihedral angle space with molecular dynamics）。根据研究者的理论结果从轨迹计算相关函数，并将其傅里叶变换为谱密度函数。构造了各二面角间的概率分布和校正矩阵。(2)利用Lefevre等人以及King和Jardetsky提出的形式，通过对松弛数据进行详细分析，确定相关的时间尺度。选择已有广泛松弛数据的三种蛋白质进行初步分析：溶菌酶葡萄球菌核酸酶和trp抑制因子。(3)使用Hoch的渗流形式来识别反映构象转变可能缓慢的轨迹簇，并将每个簇计算的谱密度项与实验独立得出的谱密度项进行匹配。对运动类型进行建模，可以解释核磁共振数据中的慢动作项，这将是对蛋白质动力学理解的重大进步。将蛋白质作为分子机制来理解——它确实如此——需要对其结构和动力学有详细而准确的了解。到目前为止，对蛋白质结构的了解非常广泛——通过x射线和核磁共振已经确定了1000多个原子分辨率的结构。相比之下，蛋白质动力学的知识仍然是相当零碎的。蛋白质运动的理论分子动力学模拟对蛋白质的理解做出了巨大贡献，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慢运动（在纳米到微秒或更长的时间尺度上）的信息，必须应用更强大的统计机械工具，例如MCDIS-MD方法，该方法将根据本赠款的条款开发。

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.