While nearest-neighbor interactions dominate the coupling matrices for both geometries and charges, the character of the strongest non-nearest-neighbor interactions differs. For geometric coupling, these strongest interactions are still close in sequence, with the strongest couplings generally occurring between second-nearest neighbors (i.e., Ser14-Arg16 or Trp6-Lys8). These are particularly strong for residues at the end of the a-helix or in the turn of the Trp-cage. The strongest couplings are also essentially identical between TC5b and TC10b variants, with none of them involving the mutated residues (Figure ). Thus, from a geometric perspective, the Ca couplings do not distinguish the two peptides. Turning instead to the charge coupling, we observe the strongest non-nearest-neighbor couplings to form an interaction map in TC10b that is distinct from TC5b (Figure ). Namely, both peptides have strong interactions in the a-helix for residues Asn1-Gln5 (TC5b) or Asp1-Ala4 (TC10b) and Gln5-Lys8 as well as in the salt bridge between Asp 9 and Arg16 (Figure ). However, the more structurally stable TC10b forms a circle of tight interactions with strong couplings for Arg16-Ser20 and Asp1-Ser20 which are not analogously present in TC5b (Figure ). Thus, the charge coupling analysis suggests that a potential source of stability for TC10b is a network of residue couplings that form throughout the protein. The observations on Trp-cage suggest that charge coupling can provide insights into residue-residue interactions not otherwise evident from geometric coupling. However, it remains computationally demanding to obtain full electronic structure descriptions of proteins. To emphasize the value of such analysis, we computed the relationship between charge coupling and geometric coupling over all residue pairs in the two proteins (Figure ). For the residues most strongly geometrically coupled, charge couplings tend to be negative (i.e., charge mediated, Figure ). However, very weak geometric coupling occurs alongside both positive and negative charge coupling (e.g., 1-16 vs 1-20 in TC10b, Figure ). A potential path forward is highlighted by the fact that we consistently obtained good agreement between charges on 20 ps of SQM dynamics with those from a much smaller subset of DFT QM snapshots. Thus, a relatively small number of single points sampled from classical molecular dynamics may reveal charge-mediated interactions as long as the trajectories are somewhat consistent with full ab initio MD. It is also expected as computing power and algorithms advance, fully ab initio, fragment-based, or dynamics using neural network potentials could make these calculations even more tractable.