schrodinger.application.peptide_workflow.monte module

class schrodinger.application.peptide_workflow.monte.MonteOptions(CACHE_SIZE: int = 10, SWAP_INTERVAL: int = 1000, LOCAL_MINIMIZATION_INTERVAL: int = 100, NO_IMPROVE_STOP_STEP: int = 300000, NO_IMPROVE_HEAT_INTERVAL: int = 700, DEFAULT_MOVE_AMPLITUDE: float = 0.2, TEMP_KELVIN: float = 298.0, CHECKPOINT_INTERVAL: int = 10000)

Bases: object

Options for monte so that args are not passed directly.

CACHE_SIZE: int = 10
SWAP_INTERVAL: int = 1000
LOCAL_MINIMIZATION_INTERVAL: int = 100
NO_IMPROVE_STOP_STEP: int = 300000
NO_IMPROVE_HEAT_INTERVAL: int = 700
DEFAULT_MOVE_AMPLITUDE: float = 0.2
TEMP_KELVIN: float = 298.0
CHECKPOINT_INTERVAL: int = 10000
classmethod fromArgs(args)

Creates an instance from arguments.

Parameters:

args (argparse.Namespace) – job settings

__init__(CACHE_SIZE: int = 10, SWAP_INTERVAL: int = 1000, LOCAL_MINIMIZATION_INTERVAL: int = 100, NO_IMPROVE_STOP_STEP: int = 300000, NO_IMPROVE_HEAT_INTERVAL: int = 700, DEFAULT_MOVE_AMPLITUDE: float = 0.2, TEMP_KELVIN: float = 298.0, CHECKPOINT_INTERVAL: int = 10000) → None
schrodinger.application.peptide_workflow.monte.update_peptide_cache(peptide, cache_list, cache_size, cluster_method)

Update the clustered cache_list if a move is accepted :param peptide: incoming peptide :type peptide: Peptide :param cache_list: the clustered cached peptides in the run :type cache_list: [Peptide] :param cache_size: size of the cache list :type cache_size: int :param cluster_method: method used to cluster the peptide :type cluster_method: BasicCluster :return: Whether the cache is updated :rtype: bool

class schrodinger.application.peptide_workflow.monte.StepCounters(step: int = 0, last_update: int = 0, last_best: int = 0, last_heat: int = 0, last_checkpoint: int = 0)

Bases: object

Step indices persisted in the checkpoint for exact state recovery.

step: int = 0
last_update: int = 0
last_best: int = 0
last_heat: int = 0
last_checkpoint: int = 0
__init__(step: int = 0, last_update: int = 0, last_best: int = 0, last_heat: int = 0, last_checkpoint: int = 0) → None
schrodinger.application.peptide_workflow.monte.save_checkpoint(cache_list, checkpoint_file, counters)

Atomically write the cache pool to a checkpoint file.

Each cached peptide’s structure is written with its energy and original title stored as structure properties so they can be restored on load. Step counters are stored on the first structure so the simulation can resume with the exact same state.

Parameters:

  • cache_list (list[Peptide]) – the cached peptides from the MC run

  • checkpoint_file (str) – path to write the checkpoint

  • counters (StepCounters) – step counters to persist

schrodinger.application.peptide_workflow.monte.load_checkpoint(checkpoint_file)

Restore a cache pool from a checkpoint file.

Parameters:

checkpoint_file (str) – path to read the checkpoint from

Return type:

tuple[list[Peptide], StepCounters]

Returns:

reconstructed cache list and step counters

schrodinger.application.peptide_workflow.monte.monte(peptide, mover, minimizer, cluster_method, random_seed, monte_options, maxsteps=500000, checkpoint_file=None)

Run MC with input mover and minimizer.

Parameters:

  • peptide (Peptide) – input peptide

  • mover (PeptideMovements) – movement sampler to be used

  • cluster_method (BasicCluster) – method to cluster the poses

  • minimizer (PeptideMinimizer) – minimizer to be used

  • random_seed (int) – random seed to create random generator

  • monte_options (monte options class obj) – contains constants for monte

  • maxsteps (int) – maximum steps for the simulation

  • checkpoint_file (str or None) – path for checkpoint save/restore; when provided the cache pool is periodically written here and restored on restart

schrodinger.application.peptide_workflow.monte.simulated_annealing(curr_temperature, curr_step, last_heat_step, temperature, no_improve_heat_interval)

Set the appropriate temperature given the current step and temperature

Parameters:

  • curr_temperature (float) – Current temperature of the simulation

  • curr_step (int) – Current step of the simulation

  • last_heat_step (int) – Last time we reset or heat the temperature

  • temperature (float) – Baseline simulation temperature

  • no_improve_heat_interval (int) – interval to increase temperature

schrodinger.application.peptide_workflow.monte.sort_write_to_output(cache_list, writer)

Sort the clustered results and write to the output

Parameters:

  • cache_list ([Peptide]) – the clustered cached peptides in the run

  • writer (StructureWriter) – structure writer

schrodinger.application.peptide_workflow.monte.metropolis(new_energy, old_energy, temp, random_generator)

Metropolis MC

Parameters:

  • new_energy (float) – the energy after the move

  • old_energy (float) – the energy before the move

  • temp (float) – the current simulation temperature

  • random_generator (numpy.random.default_rng object) – random number generator object