Hierarchical Reduction Method of Protein Structures for Understanding Protein Dynamics

Abstract

Understanding protein dynamics is prerequisite for investigating the biological functions of proteins. Protein Dynamics has been understood based on atomistic model for protein structure. However, atomistic model has been computationally limited for large protein dynamics. In this talk, we address how to computationally solve the large protein dynamics problem by implementing the component mode synthesis method which allows the computations on low-frequency modes of large proteins. Specifically, component mode synthesis allows us to consider the vibration motion of each protein domain instead of whole protein structure, and then the dynamic characterization of each domain is assembled to provide the insight into dynamics of whole protein structure. (see Fig. 1) Hemoglobin was chosen as one of the model proteins in present study. Fig. 2(a) represents Hemoglobin model, Fig. 2(b) displays constraint points at boundaries between adjacent components. The mean-square fluctuations of model proteins are compared by both GNM and component mode synthesis in Fig. 3. It is remarkable that component mode synthesis provides the mean-square fluctuation qualitatively comparable to the one obtained by both GNM and experiment one, even though component allows one to reduce the computational burden on the mean-square fluctuation.This suggests that the proposed method may allow for gaining insight into dynamics of supramolecules with computational efficiency.Fig. 1. Configuration of a structure with components(a) Hemoglobin(pdb code: 1a3n)(b) Constraint points (dotted points) and four components (different colors)Fig. 2 Hemoglobin target modelFig. 3 Comparison of mean square fluctuation of X-ray crystallography, GNM modeling and component mode synthesis.