Rapid approximation to molecular surface area via the use of Boolean logic and look‐up tables

By Scott M. Le Grand, Kenneth M. Merz Jr.. 1993

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Protein sequence design with a learned potential (2020, methodology): “[93] c) Number of buried unsatisfied polar backbone (BB) atoms.”
Frequent substructure-based approaches for classifying chemical compounds (2003, methodology): “SASA [52], the remaining attributes were computed using Hyperchem software.”
Computational Protein Design with Explicit Consideration of Surface Hydrophobic Patches (2011, background): “30 When a rotamer substitution is considered, only the dot coverage counts for atoms which have overlapping SASA radii with either the previous rotamer or the new rotamer are updated.”
Frequent sub-structure-based approaches for classifying chemical compounds (2005, methodology): “A brief description of these properties is shown in Table 6. We used two programs to compute these attributes; the geometric attributes like solvent accessible area, total accessible area/vol, total Van der Waal’s accessible area/vol were computed using the programs SASA [ 52 ], the remaining attrib”
Solvent accessible surface area approximations for rapid and accurate protein structure prediction (2009, methodology): “Many SASA approximations have been developed including spline approximations [39] and approximations that take advantage of boolean logic and look-up tables [ 40 ].”