Validation of the sMD/MSM protocol on substrate simulations Systems including apo PTP1B, PTP1B with peptide substrate (reference), and PTP1B with substrate and each of the compounds 1-4 (Figure ), were put through the sMD/MSM workflow as follows. Steered MD simulations were performed, steering the WPD loop and the allosteric network residues, outlined in Supplementary Figures and. From each trajectory, 100 snapshots evenly sampling the observed WPD loop conformations were saved and used as starting points for follow-up 50 ns seeded MD simulations (200 trajectories, 10 µs total sampling time per model). Each trajectory was reduced to two features: WPD loop (residues 178-184) backbone root mean square distance (RMSD) to closed conformation, and the P loop (residues 214-218) backbone RMSD to closed conformation (Figure ). Featurised data of all systems considered here was pooled and clustered into 100 microstates using k-means clustering, an example of which is shown in Figure . Implied timescales (ITS) were computed using a range of lag times between 0.01 and 30 ns (Supplementary Figure ), and the final lag time chosen for all MSMs was Figure : The proposed joint sMD/MSM protocol for identifying allosteric modulators. a Steered MD trajectories are used to generate transitions between protein conformations that are presumed functionally active and inactive for the system of interest. Snapshots from the sMD trajectories are then used as seeds for a swarm of equilibrium MD simulations. b The resulting ensemble of MD trajectories for multiple states of the protein of interest are clustered together to generate a consistent definition of microstates for MSM construction. PCCA analysis is used on a reference system to generate a twostate definition to evaluate the percentage of active state population. c Comparing the probability that the system will be catalytically active with and without the ligand being investigated allows to model whether it will have an inhibitory effect Figure : Allosteric inhibitors of PTP1B reported in literature. a PTP1B with WPD loop in active (orange, PDB ID: 1SUG) and inactive (blue, PDB ID: 2HNP) conformations, the substrate peptide (dark green, PDB ID: 1EEO), as well as the allosteric binders shown in b: 1 (magenta, PDB ID: 1T4J), 2 (green, PDB ID: 1T48), 3 (cyan, PDB ID: 6B95), and 4 (yellow, PDB ID: 5QDL). Except for "apo" system simulations, all simulations included the peptide substrate as well. b Structures of reported allosteric inhibitor 1 and its weak analogue 2 ; tethered inhibitor 3 and non-covalently bound variant 3u; fragment binder 4 with unknown functional effect. Figure : Markov State Model features and results. a The features used to reduce data dimensionality: backbone RMSD to closed WPD loop conformation, and Asp181(Cγ)-Cys215(S) distance. b An example of the reference system data, with the microstate clusters overlayed. Each cluster is assigned to a metastable macrostate via PCCA (magenta -active, orange -inactive). Since all of the data was clustered together for consistency, some of the microstates for a given system are not populated. c Violin plots of active state probability distributions for each system, after 100 iterations of bootstrapping by resampling. The middle horizontal bar of each violin plot indicates the median active state probability, while the upper and lower bars indicate the maximum and minimum values. The dashed line marks the median active state probability of the reference system. 20 ns. Chapman-Kolmogorov (CK) tests for each MSM are available in Supplementary Figure .