Markov State Modeling (MSM) is  used to predict both stationary and kinetic quantities on long timescales using a set of atomistic molecular dynamics simulations that are individually much shorter, thus addressing the well-known sampling problem in molecular dynamics simulation.

The MSM method enables an equilibrium binding model and its kinetic barrier heights to be reconstructed from multiple short off-equilibrium simulations. In any given simulated trajectory, only partial binding/unbinding transitions need to be observed. Trajectories are first geometrically clustered in a pre-defined conformational subspace from which a transition matrix (TM) is derived. Kinetic clustering of the eigenvectors of the TM enables metastable states to be identified and fluxes between them computed from transition path theory.