Armstrong’s Exclusion-Zone SASA Formula and Model

The solvent-accessible surface area (SASA) is a key metric in computational biochemistry, structural biology, and molecular modeling. Classical methods such as Shrake–Rupley, Lee–Richards, and LCPO rely on geometric sampling or tessellation, which introduces systematic deviations and significant computational cost. In this work, I present Armstrong’s Exclusion-Zone SASA Model, an analytical framework that integrates atomic radii, bond lengths, and probe radii into a corrected effective radius, enabling direct calculation of sterically adjusted SASA values. Benchmarking across molecules from water to hemoglobin shows that my model consistently produces results that more accurately reflect true solvent accessibility while completing calculations virtually instantaneously, even for large proteins. Unlike static classical approaches, my model inherently adapts to variations in bond lengths induced by temperature and pressure, making it well-suited for dynamic simulations and studies under extreme conditions. By uniting accuracy, efficiency, and physical scalability, this method establishes a practical and generalizable standard for SASA estimation with direct applications in protein folding, ligand binding, and drug discovery.