The number of Independent Components (ICs) was chosen so as to preserves 95% of the total kinetic variance of the dataset; this is 22 and 20 dimensions for the NonPol and Pol conditions, respectively. Discretization of the TICA space was then performed using k-means clustering as implemented in Pyemma 47 to segregate the multi-dimensional TICAspace into microstates. The number of cluster centers may have a significant impact upon the metastable state identification, and in this case the value of 100 was selected heuristically based upon convergence of the VAMP2 scores at a chosen lag time (Supporting information, Figure ). The lagtime (τ ) is chosen based on the convergence of implied relaxation timescales (ITS):