Abstract
ABSTRACT
Allosteric communication is fundamental to the function of proteins, but identifying the residue‐level pathways through which signals travel and their directionality is still a major challenge. Here we present a multi‐metric information‐theoretic framework that identifies candidate allosteric communication pathways from a single protein crystal structure in seconds. The method combines Transfer Entropy (TE) from the Gaussian Network Model to assign a model‐based directional asymmetry to residue‐residue coupling, Mutual Information (MI) to quantify coupling strength, and Conditional Mutual Information (CMI) to detect relay residues that mediate indirect couplings. At the network level, Burton–Pemantle ensemble random spanning trees provide robustness‐weighted betweenness centrality, differentiating persistent communication bottlenecks from occasional hubs. Kullback–Leibler (KL) divergence of the magnitude of the net transfer entropy distributions quantifies network rewiring and identifies allosteric switches. We validate the framework on four experimentally characterized systems: PDZ3 of PSD‐95, p38α MAP kinase, KRAS WT versus the oncogenic G12D mutant, and kinesin‐5 in ATP versus ADP bound states. Quantitative validation shows that the workflow captures previously reported hotspots and exceeds MI‐only and contact graph shortest‐path baselines on the all‐paths overlap metric, while performing at least as well as topology‐matched random controls. Computations take from ~14 s for a 110‐residue domain to ~7 min for a 350‐residue domain. on a standard laptop. Thus, the method can be applied systematically to large families of proteins.