Gdock sampling module

Submodules

haddock.modules.sampling.gdock.gdock module

Module contents

gdock integration sampling module.

class haddock.modules.sampling.gdock.HaddockModule(order: int, path: Path, *ignore: Any, initial_params: str | Path = PosixPath('/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/haddock/modules/sampling/gdock/defaults.yaml'), **everything: Any)[source]

Bases: BaseHaddockModule

HADDOCK3 gdock module.

classmethod confirm_installation() → None[source]: Confirm if the module is ready to use.

name: str = 'gdock'

Default Parameters

Easy

ambig_fname

default: ‘’
type: file
title: Ambiguous distance restraints filename
short description: Filename of the ambiguous distance restraints file
long description: Filename of the ambiguous distance restraints file. Restraints between the receptor and ligand chains are converted to residue pairs and used by gdock to bias the genetic algorithm search.
group: distance restraints
explevel: easy

max_generations

default: 250
type: integer
title: Maximum number of generations
min: 1
max: 100000
short description: Maximum number of genetic algorithm generations.
long description: Maximum number of genetic algorithm generations run by gdock.
group: sampling
explevel: easy

number_of_individuals

default: 150
type: integer
title: Number of individuals
min: 1
max: 100000
short description: Number of individuals in the GA population.
long description: Number of individuals (chromosomes) in each generation of gdock’s genetic algorithm. Larger populations explore the conformational space more broadly but increase runtime proportionally.
group: sampling
explevel: easy

sampling

default: 1000
type: integer
title: Number of maximum models to generate
min: 1
max: 500000
short description: Maximum number of unique conformations gdock collects per input model.
long description: Controls gdock’s Hall-of-Fame capacity. gdock accumulates up to this many unique conformations during the genetic algorithm run and returns them all sorted by fitness.
group: sampling
explevel: easy

seed

default: 42
type: integer
title: Random seed
min: 0
max: 999999999
short description: Random seed used by gdock’s genetic algorithm.
long description: Random seed used by gdock’s genetic algorithm, for reproducibility.
group: sampling
explevel: easy

Expert

crossdock

default: True
type: boolean
title: Cross docking of starting ensembles
short description: If true, all combinations of input models are docked; if false, models are paired by index.
long description: Controls how starting model ensembles are combined. When true (default), gdock docks all combinations of receptor x ligand models (same as rigidbody crossdock=true). When false, the first receptor model is paired with the first ligand model, etc.; this requires both ensembles to have the same number of models.
group: sampling
explevel: expert