Mathematical quantification of binding complementarity using intersection surface area (ISA) and geometric sensitivity index (GSI).

The R292K mutation in Influenza Neuraminidase (NA) significantly hinders the efficacy of clinical inhibitors, yet the physical basis of this resistance remains under-explored. In this study, we introduce a novel computational framework integrating Molecular Dynamics (MD) simulations with a geometric Intersection Surface Area (ISA) model. Our results demonstrate that the R292K mutation induces a structural destabilization characterized by a ∼11.5 kcal/mol increase in binding free energy and a 15-21% reduction in intersection binding volume ([Formula: see text]). Notably, Zanamivir (Ligand D) exhibited the highest geometric sensitivity with a 27.2% reduction in [Formula: see text], providing a structural rationale for its observed clinical susceptibility patterns. This integrated geometric-MD approach offers an indicative screening framework for evaluating next-generation neuraminidase inhibitors against emerging viral mutants.