Structure refinement and prediction by data-driven molecular dynamics simulations

Abstract

Proteins are polymers with extremely complicated structure and elaborate functions and form the basis of various biological phenomena occurring in vivo, such as molecular recognition, information transfer, enzymatic reaction, and etc. Since it is expected that there is a correlation (structure-function relationship) between their three-dimensional (3D) structure and function, 3D structures of many proteins have been solved by experimental methods such as X-ray / neutron diffraction experiment and nuclear magnetic resonance method (NMR). Especially recently, X-ray free electron laser and cryo-electron microscope have revealed the relationship between dynamical function and structural change at single-molecule level. In this research, we reproduce low resolution structure data by executing parallel cascaded MD we have developed using similarity with experimental data. We also show that it is possible to induce structural transitions by using dissimilarity with experimental data.