COMPUTER SIMULATIONS OF PROTEIN STRUCTURE AND DYNAMICS

计算机模拟提供了最详细的理论方法 可用于在分子水平上研究蛋白质。拟议的研究 致力于开发更精确的分子检测方法 溶剂化蛋白质的动力学模拟及其在生物化学研究中的应用 目前蛋白质静电学领域中的生物物理问题， 动力学，和折叠。这项提案的具体目标是在 下一个资助期是在两个领域：一、蛋白质溶剂化的研究和 使用显式溶剂模型的蛋白质中的静电效应，以及ii。 天然蛋白和部分蛋白的结构和动力学研究 通过计算机模拟核磁共振现象研究溶液中的折叠态。 I.蛋白质溶剂化和蛋白质中静电效应的研究 使用显式溶剂模型。 静电效应在模拟中的当前处理 必须改进显性溶剂。在下一个授权期内，我们将 继续开发处理静电特性的方法 在基于我们的广义反应的溶剂化蛋白质的模拟中 场(GRF)模型和快速Ewald求和方法。公钥基础设施分析 蛋白质的变化为理解pH的影响提供了一种手段 蛋白质的稳定性和pH依赖的构象变化。我们将使用 更准确的显式溶剂模拟来预测pKA在 一系列表征良好的模型化合物，包括二胺和 二元酸和蛋白质中，包括继续研究PKA在 溶菌酶。预测免费电量的分子线性响应模型 我们开发的溶液中的能量为我们提供了一个强大的 此项目的分析工具。 用计算机模拟研究蛋白质的结构和动力学 核磁共振现象。 在与实验核磁共振小组的持续合作中，我们将使用 模拟补充蛋白质结构的实验核磁共振研究 和动态感。我们将集中讨论(1)核磁共振序列的分解 将参数转化为集体运动和更局部化的运动，(2)分析 大时间尺度上蛋白质运动对核磁共振的贡献 松弛，以及(3)结构和内部的比较 完全折叠和部分折叠蛋白质的动力学。我们将使用的蛋白质 重点包括人类转化生长因子(HTGFpha)和 α-乳清蛋白。这项工作将更清楚地揭示这些信息。 关于核磁共振弛豫中包含的函数重要运动 实验。α-乳清蛋白模拟将提供详细的 一种结构和动力学断裂的分子图像 部分折叠的蛋白质来补充核磁共振实验。

Computer simulations provide the most detailed theoretical method available to study proteins at a molecular level. The proposed research is focused on the development of more accurate methods for molecular dynamics simulations of solvated proteins, and their application to current biophysical problems in the areas of protein electrostatics, dynamics, and folding. The specific goals of this proposal during the next grant period are in two areas: I. the study of protein solvation and electrostatic effects in proteins using explicit solvent models, and II. the study of protein structure and dynamics of native and partially folded states in solution by computer modeling of NMR phenomena. I. The study of protein solvation and electrostatic effects in proteins using explicit solvent models. The current treatment of electrostatic effects in simulations with explicit solvent must be improved. During the next grant period, we will continue our development of methods for treating electrostatic properties in simulations of solvated proteins based on our generalized reaction field (GRF) model and on fast Ewald sum methods. The analysis of pKa shifts in proteins provides a means for understanding pH effects on protein stability and pH dependent conformational changes. We will use the more accurate explicit solvent simulations to predict pKa shifts in a series of well characterized model compounds, including diamines and diacids, and in proteins, including continued work on pKa shifts in lysozyme. A molecular linear response model for predicting charging free energies in solution which we have developed provides us with a powerful analysis tool for this project. II. The study of protein structure and dynamics by computer modeling of NMR phenomena. In a continuing collaboration with experimental NMR groups, we will use simulations to complement experimental NMR studies of protein structure and dynamics. We will focus on (1) the decomposition of NMR order parameters into collective, and more localized motions, (2) analysis of the contributions of protein motions on longer time scales to NMR relaxation, and (3) a comparison between the structure and internal dynamics of fully and partially folded protein. The proteins we will focus on include the human transforming growth factor (hTGFalpha) and alpha-lactalbumin. This work will bring out more clearly the information about functionally important motions contained in NMR relaxation experiments. The alpha-lactalbumin simulations will provide a detailed molecular picture of the structural and dynamical fractures of a partially folded protein to complement NMR experiments.