Solvent accessible surface area approximations for rapid and accurate protein structure prediction

By Elizabeth Durham, Brent M. Dorr, Nils Woetzel, René Staritzbichler, Jens Meiler. Journal of Molecular Modeling, 2009

432 citations recorded by the source corpus.

The burial of hydrophobic amino acids in the protein core is a driving force in protein folding. The extent to which an amino acid interacts with the solvent and the protein core is naturally proportional to the surface area exposed to these environments. However, an accurate calculation of the solvent-accessible surface area (SASA), a geometric measure of this exposure, is numerically demanding as it is not pair-wise decomposable. Furthermore, it depends on a full-atom representation of the molecule. This manuscript introduces a series of four SASA approximations of increasing computational complexity and accuracy as well as knowledge-based environment free energy potentials based on these SASA approximations. Their ability to distinguish correctly from incorrectly folded protein models is assessed to balance speed and accuracy for protein structure prediction. We find the newly developed “Neighbor Vector” algorithm provides the most optimal balance of accurate yet rapid exposure measures.

Subfields: Materials Chemistry, Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/2d8f95f32f4978d12c2ad02fe17fcdadef4f39c8

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Citations in the corpus

Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design (2018, methodology): “The original implementation of HBNet used solvent-accessible surface area (SASA) 31,32 calculations with an increased probe radius 26 .”