Our second model system is the enzyme Protein Tyrosine Phosphatase 1B (PTP1B), which contains a catalytic loop that undergoes a large scale (∼10 Å) conformational change in order to regulate its catalytic activity (Figure ). The WPD-loop can adopt two major conformations a "closed" (catalytically active) and "open" (catalytically inactive) conformation (Figure ). How the conformational state of the WPD-loop is allosterically regulated has been the focus of many prior studies including those using NMR, 92-94 X-ray crystallography, mutagenesis, and molecular simulations (see e.g. refs. , among many others). For PTP1B, we applied KIF to predict the key residues and interactions that are associated with the WPD-loops' conformational state, and compared our predictions to the aforementioned available experimental data. Further, we will utilize our package to characterize the allosteric signaling pathways from PTP1B's two known allosteric drug binding sites to the active site (Figure ). In order to do this, we performed a total of 20 x 100 ns MD simulations of PTP1B, starting 10 of these from the closed and 10 from the open WPDloop conformations of this enzyme. We then extracted 10,000 equally spaced frames from these simulations and used PyContact 1 to identify all the non-covalent interactions present within PTP1B, for subsequent analysis with our program. To go alongside the interactions (i.e., the features) generated from the PyContact 1 calculations, we classified the conformation of the WPD-loop in each frame in order to generate the target variable (for classification). For this, we used a simple rule-based scheme to define the conformation of the WPD-loop for each frame: "Closed" (if the WPD-loop RMSD to the closed loop crystal structure was ≤1.5 Å); or "Open" (if the WPD-loop RMSD to the open loop crystal structure was ≤1.5 Å); and "Neither" (if the WPD-loop RMSD to both the closed and open crystal structure conformations was ≤1.5 Å or if the RMSD was >1.5 Å to both crystal structures). This is an approximate classification, as the WPD-loop conformation can fall on a spectrum between "open" and "closed states", occupying multiple stable conformations along that spectrum. However, such a simplified definition enabled us to perform binary classification using both the ML and statistical analysis modules, by first discarding any frames that were classified as "Neither" (348 of 10,000 frames) according to the aforementioned protocol. The results from the ML module reflected the same issue as was described for the PDZ3 domain (only describing some and not all of the key interactions/residues, see the Supplementary Results), so herein we focus on our results generated only from the statistical analysis module.