Markov state model construction. Markov state models (MSMs) allow for the construction of a transition probability matrix of a system at equilibrium, which is used to obtain the relative populations of conformational states and the transition timescales between them. This can be accomplished by running short MD simulations of a system in replicate, increasing the likelihood that slow transitions are observed compared to a single long trajectory. To build an MSM, relevant features of the system are selected and transformed using time-lagged independent component analysis (TICA) to resolve coordinates corresponding to the slowest motions of the system. From there, a set of metastable states can be identified by clustering along the TICA space. A transition probability matrix can be calculated by estimating the number of transitions between metastable states at some fixed lag time, τ .