On-the-fly analysis of molecular dynamics simulation trajectories of proteins using the Bayesian inference method

Robust and reliable analyses of long trajectories from molecular dynamics simulations are important for investigations of functions and mechanisms of proteins. Structural fitting is necessary for various analyses of protein dynamics, thus removing time-dependent translational and rotational movements. However, the fitting is often difficult for highly flexible molecules. Thus, to address the issues, we proposed a fitting algorithm that uses the Bayesian inference method in combination with rotational fitting-weight improvements, and the well-studied globular protein systems trpcage and lysozyme were used for investigations. The present method clearly identified rigid core regions that fluctuate less than other regions and also separated core regions from highly fluctuating regions with greater accuracy than conventional methods. Our method also provided simultaneous variance-covariance matrix elements composed of atomic coordinates, allowing us to perform principle component analysis and prepare domain cross-correlation map during molecular dynamics simulations in an on-the-fly manner.