Overall, we have demonstrated how Markov state modeling can be combined with short, parallel MD trajectories in order to define discrete states based on the slow dynamics of a system. We verify that the discrete states of the T4 L99A binding pocket previously established in experiment 10 can also be observed in MD, although even longer MD simulations of native systems do not sample any conformational changes. Thus, we simulate a series of mixed systems in order to estimate the transition timescales between states. Our timescale estimates are consistent with previous findings, where it was shown that for the T4 L99A system, the choice of starting protein conformational state heavily influences which conformations are sampled through the course of the simulation. For known systems undergoing discrete conformational changes upon binding of a congeneric ligand series, we suggest combining short, replicate MD simulations of different bound ligands with MSMs to resolve biologically-relevant slow motions of the system. We believe the coordinates resolved from kinetic information offers an alternative to RMSD-based definitions and can be used to establish more robust state definitions for other biological systems. slow transitions for each system and snapshots of trajectory frames along various points of the TICA surface.