Armstrong’s Exclusion-Zone SASA Formula and Model

Solvent-accessible surface area (SASA) is a central quantity in computational biochemistry, structural biology, and molecular modeling, with applications ranging from protein folding to ligand binding. Widely used approaches such as Shrake-Rupley, Lee-Richards, and LCPO estimate SASA through geometric sampling or surface tessellation, introducing discretization error and significant computational overhead. Here, I introduce Armstrong’s Exclusion-Zone SASA model, a closed-form analytical framework that approximates solvent-accessible surface exclusion without explicit surface tessellation, using a physically motivated steric metric derived from atomic radii, bond lengths, and solvent probe size. The model enables direct and effectively instantaneous calculation of sterically adjusted SASA values while preserving the expected physical scaling behavior across molecular sizes. Benchmarking across systems ranging from small molecules to large proteins demonstrates systematic recovery of solvent-accessible microenvironments in compact systems and smooth convergence toward Shrake-Rupley and Lee-Richards values at macromolecular scales, with quantitative agreement emerging within the expected resolution of classical tessellation-based methods. Because the exclusion metric depends explicitly on geometric parameters, the formulation naturally adapts to bond-length variations arising from temperature, pressure, or conformational change, making it well suited for dynamic simulations and high-throughput workflows. By uniting analytical efficiency, physical interpretability, and asymptotic consistency with classical methods, the Exclusion-Zone SASA model provides a computationally efficient, physically interpretable approximation for solvent accessibility estimation in molecular modeling and biomolecular simulation.