ArticleJournal of chemical theory and computation2024
Exact Analytical Algorithm for the Solvent-Accessible Surface Area and Derivatives in Implicit Solvent Molecular Simulations on GPUs.
Article in Journal of chemical theory and computation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- Article
- Article
- In silico analysis of PERK interactions with engineered alpha lactalbumin peptides using molecular dynamics simulations.Scientific reports · 2026Article
- Residue burial encodes a protein's fold.bioRxiv : the preprint server for biology · 2026Article
- Multiscale mechanistic insights into sonochemical energy coupling and flavor evolution in Pu‑erh tea.Ultrasonics sonochemistry · 2026Article
- Dihydroalterperylenol from endophytic fungusMolecular medicine reports · 2026Article
- In silico pharmacological analysis of Tinospora cordifolia compounds targeting African swine fever virus B175L.PloS one · 2026Article
- Exploring the Nutritional and Antimicrobial Properties of Wild Fruit,Scientifica · 2025Article
- sesA: A Program for the Analytic Computation of Solvent-Excluded Surface Areas.ChemistryOpen · 2024Article
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Abstract
In this paper, we present differentiable solvent-accessible surface area (dSASA), an exact geometric method to calculate SASA analytically along with atomic derivatives on GPUs. The atoms in a molecule are first assigned to tetrahedra in groups of four atoms by Delaunay tetrahedralization adapted for efficient GPU implementation, and the SASA values for atoms and molecules are calculated based on the tetrahedralization information and inclusion-exclusion method. The SASA values from the numerical icosahedral-based method can be reproduced with >98% accuracy for both proteins and RNAs. Having been implemented on GPUs and incorporated into AMBER, we can apply dSASA to implicit solvent molecular dynamics simulations with the inclusion of this nonpolar term. The current GPU version of GB/SA simulations has been accelerated up to nearly 20-fold compared to the CPU version, outperforming LCPO, a commonly used, fast algorithm for calculating SASA, as the system size increases. While we focus on the accuracy of the SASA calculations for proteins and nucleic acids, we also demonstrate stable GB/SA MD mini-protein simulations.
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