Markov State Model Construction. All Markov state model (MSM) construction was done with PyEMMA (version 2.5.7) 69 and supporting root mean square error (RMSD) calculations used MDTraj (version 1.9.5). Trajectory data was featurized using several structural descriptors. Atomic pairwise distances between all Cα atoms as well as Tyr2Cζ, Trp9Cδ1, Asp3N, Thr8O and Gly7O (henceforth shorthanded as distances, d) were selected for the initial featurization. These atoms were selected to highlight potential interactions observed in prior work. Corresponding inverse distances (d -1 ) were also calculated to capture close-proximity interactions. In addition to distances, backbone dihedrals (ϕ-and ψ-angles, transformed to vectors on the unit circle to avoid periodicity artifacts) were calculated and analyzed separately and in combination with inverse distances. Dimensionality reduction of the featurized trajectory data was performed using tICA with a 50 ns lag time, and projection onto the 8 most significant independent components. Projections onto independent components 1 (IC1) and 2 (IC2) are shown for all nine force fields in Figure . To explore various possible microstate discretizations, the projected trajectory data was partitioned into 5, 10, 50, 75, 100 and 500 microstates using k-means clustering. For each state discretization, MSMs were constructed using 20 ns lagtime using a maximum likelihood estimator. The lagtime was chosen from an examination of MSM implied timescales as a function of lagtime, which plateau after 20 ns for all force fields.