mkt.databases.sasa.CrossValidationConfig

class mkt.databases.sasa.CrossValidationConfig(*, bool_biopython: bool = True, bool_pymol: bool = True, bool_include_hydrogens: bool = False, bool_relative: bool = True, probe_radius: float = 1.4, n_points: int = 960, dot_density: int = 4)[source]

Bases: BaseSASAConfig

Heavy-atom SASA from both backends with matched probe/sampling.

__init__(*, bool_biopython: bool = True, bool_pymol: bool = True, bool_include_hydrogens: bool = False, bool_relative: bool = True, probe_radius: float = 1.4, n_points: int = 960, dot_density: int = 4) → None

Methods

`__eq__`(other)	Return self==value.
`__init__`(*[, bool_biopython, bool_pymol, ...])

Attributes

`__dataclass_fields__`
`__dataclass_params__`
`__match_args__`
`bool_biopython`	Compute SASA with the Bio.PDB Shrake-Rupley backend.
`bool_include_hydrogens`	Keep explicit hydrogens; False gives conventional heavy-atom SASA.
`bool_pymol`	Compute SASA with the PyMOL `dot_solvent` backend.
`bool_relative`	Add relative SASA (rSASA); requires heavy-atom SASA (no explicit H).
`dot_density`	PyMOL surface point density 1-4 (PyMOL only).
`n_points`	Shrake-Rupley sphere points per atom (Bio.PDB only); default 100 is unlikely to be converged for per-residue SASA (presets use ~960).
`probe_radius`	Solvent/probe radius (Å), shared by both backends.

__init__(*, bool_biopython: bool = True, bool_pymol: bool = True, bool_include_hydrogens: bool = False, bool_relative: bool = True, probe_radius: float = 1.4, n_points: int = 960, dot_density: int = 4) → None

bool_biopython: bool = True: Compute SASA with the Bio.PDB Shrake-Rupley backend.

bool_pymol: bool = True: Compute SASA with the PyMOL dot_solvent backend.

dot_density: int = 4: PyMOL surface point density 1-4 (PyMOL only).

n_points: int = 960: Shrake-Rupley sphere points per atom (Bio.PDB only); default 100 is unlikely to be converged for per-residue SASA (presets use ~960).