Deciphering Allosteric Disease Mutations Through Intrinsic Dynamics

Allosteric regulation, driven by conformational and dynamic changes, is fundamental to many biological processes. A major challenge in disease genomics is understanding how specific somatic missense mutations affect protein function, especially when their impact structurally and functionally indirect. In this study, we investigate the link between such mutations and intrinsic protein dynamics, focusing on their allosteric roles. We have analyzed 2549 mutations across 190 human proteins from the ClinVar dataset, using the Gaussian Network Model (GNM) based Transfer Entropy (TE) method. Using the Transient Receptor Potential Mucolipin 1 (TRPML1) channel as a case study, we demonstrate that sequential removal of global modes reveals layered, causal allosteric interactions, where functional sites recur or emerge across various dynamic contexts. Pathogenic mutations significantly coincide with key information sources or sinks within collective information flow. Insights gained from TRPML1 served to inform a large-dataset analysis, providing a topographical view of mutation patterns across a wide range of human proteins and demonstrating broader applicability of this framework Our results provide mechanistic insights into how disease-associated mutations perturb protein dynamics, highlighting distinct components of functional motion and diverse dynamic behaviors offering a path toward allosteric-based interpretation of mutational impact in human disease.