Conformational changes play important roles in many biomolecular systems. The Generalized Master Equation provides a powerful tool to investigate the functional conformational changes from Molecular Dynamics (MD) simulations at atomic level. The GME utilizes the time-dependent transitions between each pairs of states, and explicitly considers the contribution of time-dependent memory kernels in the equation of dynamics. Previously, we have developed qMSM, a straightforward implementation of the GME. In qMSM, both the memory kernels and the long-time dynamics are calculated by the GME. This leads to numerical instability of qMSM when applied to large and complex biomolecular systems. To address this issue, we have developed a new theory called the integrative GME (IGME) to utilize the integration of memory kernels to remove the numerical fluctuations of simulation data. The IGME provides robust approaches to build GME and propagate dynamics for the slow dynamics of the studied system. We showed that the IGME could greatly outperform MSM and qMSM for large and complex systems, including the conformation dynamics of FIP35 WW domain, the clamp opening of RNA polymerase and the micro RNA recognition of the human Ago protein.

The integrative generalized-master-equation: A robust approach for building kinetic models of large biomolecular systems

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