The full residue-residue matrix of GC measurements provides a robust dataset with a wide range of analyses to consider. Converting the measured correlation between residues into an adjacency matrix first, and then a full network, opens the correlated motion analysis to another myriad of graph theory analyses. In this work, we construct a weighted graph between residues by converting the r M I matrix into a weighted adjacency matrix A. Specifically, A(i, j) = -ln(r M I (i, j))D(i, j) where r M I (i, j) is the GC between residues (or nodes) i and j and D(i, j) is the shortest distance between any heavy atoms of residues i and j. In each case, the structure used to calculate the distances was the average structure from each individual MD simulation using a traditional whole protein RMS alignment, not the local alignment approach outlined in the previous section. In this definition, although no cutoff distance is necessary to define whether two residues can be connected, closer residues are prioritized.