In Figure , we were able to validate our model's ability to identify allosterically sensitive residues on the PDZ3 domain. In the following section, we will focus on the interactions between the β2-β3 loop and the α3-helix to demonstrate how our approach can be used to gain deeper insight at a more local level. By calculating the difference in the Cα-atom root mean squared fluctuations RMSF (ΔRMSF) across the entire PDZ3 domain for the unliganded and peptide bound simulations (Figure ), we were able to identify that the N-terminal portion of the α2-helix, the β2-β3 loop and the α3-helix were all destabilized in the absence of the peptide (Figure ), although the destabilization in the helices is comparatively minor. By analyzing our per feature (per interaction) scores, we were then able to identify several interactions which likely resulted in this destabilization, which are depicted in Figure . This interaction network structurally begins from the α2-helix and passes through the β2-β3 loop to end at the α3-helix (Figure ). By measuring the correlation between interacting pairs in these regions (Figure ), we are also able to confirm a high degree of correlation between these regions. This was especially true in the case of interacting pairs, such as H372, G329, G330 and F400 (Figure ). Beyond this, we can refer back to the PyContact 1 determined interaction strength for any given interaction and identify how this interaction differed for the unliganded and peptide bound simulations over time. In this case we focused on the salt bridge between E334 on the β2-β3 loop and R399 on the α3-helix (Figure ). By extracting the kernel density estimations generated for each feature in the unliganded and peptide bound states (a part of the process to calculate the JS-Distance for each feature, see the Methodology sections), we identified this salt bridge to be clearly weakened in the unliganded state (Figure ). This observation also helps to rationalize the observed destabilization of this region in the absence of the peptide (Figure ). Residues are color mapped from red (more flexible in the unliganded simulations), through white (equally flexible in both simulations) to blue (more flexible in the peptide bound simulations). Key non-covalent interactions identified by our package as important (see Table ) between the α2-helix, β2-β3 loop and α3-helix are indicated with black dashes. (B) The linear correlation of the β2-β3 loop residues to the α2-and α3-helices of the PDZ3 domain determined from our MD simulations with the peptide bound (equivalent results for the unliganded simulations are presented in Figure ). (C) PyContact 1 calculated interaction strength against simulation time for the unliganded and peptide bound simulations for the salt bridge interaction between E334 and R399. The dotted lines drawn every 100 ns represent the start of a new replica. (D) Kernel density estimations of the normalized interaction strength of the E334-R399 salt bridge for both the unliganded and peptide bound MD simulations.