Hotspot Calculation API

The hotspots.calculation handles the main Fragment Hotspot Maps algorithm. In addition, an alternative pocket burial method, Ghecom, is provided.

The main classes of the hotspots.calculation module are:

More information about the Fragment Hotspot Maps method is available from:

  • Radoux, C.J. et. al., Identifying the Interactions that Determine Fragment Binding at Protein Hotspots J. Med. Chem. 2016, 59 (9), 4314-4325 [dx.doi.org/10.1021/acs.jmedchem.5b01980]

More information about the Ghecom method is available from:

  • Kawabata T, Go N. Detection of pockets on protein surfaces using small and large probe spheres to find putative ligand binding sites. Proteins 2007; 68: 516-529

class hotspots.calculation.Runner(settings=None)[source]

Bases: object

A class for running the Fragment Hotspot Map calculation

class Settings(nrotations=3000, apolar_translation_threshold=15, polar_translation_threshold=15, polar_contributions=False, return_probes=False, sphere_maps=False)[source]

Bases: object

adjusts the default settings for the calculation

Parameters

  • nrotations (int) – number of rotations (keep it below 10**6)

  • apolar_translation_threshold (float) – translate probe to grid points above this threshold. Give lower values for greater sampling. Default 15

  • polar_translation_threshold (float) – translate probe to grid points above this threshold. Give lower values for greater sampling. Default 15

  • polar_contributions (bool) – allow carbon atoms of probes with polar atoms to contribute to the apolar output map.

  • return_probes (bool) – Generate a sorted list of molecule objects, corresponding to probe poses

  • sphere_maps (bool) – When setting the probe score on the output maps, set it for a sphere (radius 1.5) instead of a single point.

from_pdb(pdb_code, charged_probes=False, probe_size=7, buriedness_method='ghecom', nprocesses=3, cavities=False, settings=None, clear_tmp=False)[source]

generates a result from a pdb code

Parameters

  • pdb_code (str) – PDB code

  • charged_probes (bool) – If True include positive and negative probes

  • probe_size (int) – Size of probe in number of heavy atoms (3-8 atoms)

  • buriedness_method (str) – Either ‘ghecom’ or ‘ligsite’

  • nprocesses (int) – number of CPU’s used

  • settings (hotspots.calculation.Runner.Settings) – holds the calculation settings

Returns

a hotspots.result.Result instance

>>> from hotspots.calculation import Runner

>>> runner = Runner()
>>> runner.from_pdb("1hcl")
Result()
from_protein(protein, charged_probes=False, probe_size=7, buriedness_method='ghecom', cavities=None, nprocesses=1, settings=None, buriedness_grid=None, clear_tmp=False)[source]

generates a result from a protein

Parameters

  • protein – a ccdc.protein.Protein instance

  • charged_probes (bool) – If True include positive and negative probes

  • probe_size (int) – Size of probe in number of heavy atoms (3-8 atoms)

  • buriedness_method (str) – Either ‘ghecom’ or ‘ligsite’

  • cavities – Coordinate or ccdc.cavity.Cavity or ccdc.molecule.Molecule or list specifying the cavity or cavities on which the calculation should be run

  • nprocesses (int) – number of CPU’s used

  • settings (hotspots.calculation.Runner.Settings) – holds the sampler settings

  • buriedness_grid (ccdc.utilities.Grid) – pre-calculated buriedness grid

Returns

a hotspots.result.Results instance

>>> from ccdc.protein import Protein
>>> from hotspots.calculation import Runner

>>> protein = Protein.from_file(<path_to_protein>)

>>> runner = Runner()
>>> settings = Runner.Settings()
>>> settings.nrotations = 1000  # fewer rotations increase speed at the expense of accuracy
>>> runner.from_protein(protein, nprocesses=3, settings=settings)
Result()
from_superstar(protein, superstar_grids, buriedness, charged_probes=False, probe_size=7, settings=None, clear_tmp=False)[source]

calculate hotspot maps from precalculated superstar maps. This enables more effective parallelisation and reuse of object such as the Buriedness grids

Parameters

  • protein – a ccdc.protein.Protein instance

  • superstar_grids – a hotspots.atomic_hotspot_calculation._AtomicHotspotResult instance

  • buriedness – a hotspots.grid_extension.Grid instance

  • charged_probes (bool) – If True, include positive and negative probes

  • probe_size (int) – Size of probe in number of heavy atoms (3-8 atoms)

  • settings – hotspots.calculation.Runner.Settings settings: holds the sampler settings

  • clear_tmp (bool) – If True, clear the temporary directory

Returns