COMPUTER SIMULATIONS OF PROTEIN STRUCTURE AND DYNAMICS

计算机模拟提供了最详细的理论方法

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.