RustSASA: A Rust Crate for Accelerated Solvent Accessible Surface Area Calculations

Solvent accessible surface area (SASA) calculations are fundamental for understanding protein structure, function, and dynamics in computational biology, providing insights into protein folding, stability, and intermolecular interactions.The Shrake-Rupley algorithm has served as the standard method since 1973, but existing implementations often become computational bottlenecks when analyzing large protein datasets or molecular dynamics trajectories.As structural biology databases continue to expand, exemplified by AlphaFold's hundreds of millions of predicted structures, the need for efficient SASA calculation tools has increased dramatically.RustSASA addresses this challenge through a high-performance implementation written in Rust, leveraging efficient parallelization abstractions and SIMD instructions.Benchmarking demonstrates a 5× speed improvement over FreeSASA for proteome-scale calculations and a 20× improvement for molecular dynamics trajectory analysis.Validation against FreeSASA yields Pearson correlation coefficients exceeding 0.99 on both the predicted E. coli proteome and the FreeSASA evaluation dataset, confirming calculation accuracy.RustSASA provides interfaces for multiple programming languages (Rust and Python), a command-line interface, and integration with the MDAnalysis framework (Gowers et al., 2016;Michaud-Agrawal et al., 2011), ensuring broad accessibility across the computational biology community.