schrodinger.application.desmond.mapper_msj_generator module

class schrodinger.application.desmond.mapper_msj_generator.BaseMsjGenerator(jobname: str, cd_params: Dict[str, object], **kwargs)

Bases: object

Base class.

__init__(jobname: str, cd_params: Dict[str, object], **kwargs)
Parameters:
  • jobname – The jobname.
  • cd_params – A dictionary, with the keys gpus, set to True for GPU jobs, and cpus, set to the number of cpus/gpus to use.
  • forcefield (str) – The name of the forcefield to use.
  • sim_time (int) – The simulation time for the production stage in ps.
  • sim_time_complex (int) – The simulation time for the complex leg in ps
  • sim_time_solvent (int) – The simulation time for the solvent leg in ps
  • rand_seed (int) – The random seed.
  • ensemble (str) – The ensemble, NPT or NVT.
  • buffer_width (float) – The buffer width in Angstrom determines how much solvent is added to the solute. This is only used if it is larger than the default buffer width.
  • lambda_windows (int) – Number of lambda replicas to use for the FEP stages.
  • custom_charge_mode (CUSTOM_CHARGE_MODE) – Set to CUSTOM_CHARGE_MODE.ASSIGN to assign custom charges. Set to CUSTOM_CHARGE_MODE.CLEAR to clear custom charges if present, without reassigning. Set to CUSTOM_CHARGE_MODE.KEEP to keep existing custom charges if present.
  • h_mass (bool) – Set to True to enable hydrogen mass repartitioning and False to disable it. Default is True.
  • concatenate (bool) – Set to True to concatenate the equilibration FEP stages. Default is True.
__class__

alias of builtins.type

__delattr__

Implement delattr(self, name).

__dict__ = mappingproxy({'__module__': 'schrodinger.application.desmond.mapper_msj_generator', '__doc__': '\n Base class.\n\n ', '__init__': <function BaseMsjGenerator.__init__>, '_check_sim_params': <function BaseMsjGenerator._check_sim_params>, '_find_production_stages': <function BaseMsjGenerator._find_production_stages>, '_set_water_model': <function BaseMsjGenerator._set_water_model>, '_set_hmr': <function BaseMsjGenerator._set_hmr>, '_set_buffer_width': <function BaseMsjGenerator._set_buffer_width>, '_set_scale_solvent_vdw': <function BaseMsjGenerator._set_scale_solvent_vdw>, '_set_extract_structures': <function BaseMsjGenerator._set_extract_structures>, '_set_production_parameters': <function BaseMsjGenerator._set_production_parameters>, '_set_ff': <function BaseMsjGenerator._set_ff>, '_set_lambda_windows': <function BaseMsjGenerator._set_lambda_windows>, '_set_assign_custom_charge': <function BaseMsjGenerator._set_assign_custom_charge>, '_set_gpu': <function BaseMsjGenerator._set_gpu>, '_set_job_num_cpus': <function BaseMsjGenerator._set_job_num_cpus>, '__dict__': <attribute '__dict__' of 'BaseMsjGenerator' objects>, '__weakref__': <attribute '__weakref__' of 'BaseMsjGenerator' objects>})
__dir__() → list

default dir() implementation

__eq__

Return self==value.

__format__()

default object formatter

__ge__

Return self>=value.

__getattribute__

Return getattr(self, name).

__gt__

Return self>value.

__hash__

Return hash(self).

__init_subclass__()

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__

Return self<=value.

__lt__

Return self<value.

__module__ = 'schrodinger.application.desmond.mapper_msj_generator'
__ne__

Return self!=value.

__new__()

Create and return a new object. See help(type) for accurate signature.

__reduce__()

helper for pickle

__reduce_ex__()

helper for pickle

__repr__

Return repr(self).

__setattr__

Implement setattr(self, name, value).

__sizeof__() → int

size of object in memory, in bytes

__str__

Return str(self).

__subclasshook__()

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

__weakref__

list of weak references to the object (if defined)

class schrodinger.application.desmond.mapper_msj_generator.MapperMsjGenerator(jobname, cd_params, **kwargs)

Bases: schrodinger.application.desmond.mapper_msj_generator.BaseMsjGenerator

__init__(jobname, cd_params, **kwargs)

In addition to the parameters passed to BaseMsjGenerator, the MapperMsjGenerator supports the following.

Parameters:
  • atom_mapping – The SMARTS string used to determine the core for atom mapping. Default is to determine the atom mapping automatically.
  • align_core_only – Do not adjust the non-core atoms when aligning the core atoms. Default is False.
  • ats – (deprecated) Set to True to enable automated torsion scaling. Default is False.
  • charged_lambda_windows – Set the number of lambda windows used for charged perturbations. Default is 24.
  • core_hopping_lambda_windows – Set the number of lambda windows used for core-hopping perturbations. Default is 16.
  • fep_convergence – (deprecated) Adaptive sampling, tolerance value for statistical error on dG. Default is 0.0, which means no adaptive sampling.
  • membrane – Set to the filename containing the membrane structures. Default is None, there is no membrane.
  • salt_concentration – Concentration of ions to add in M. Default is 0.15 M.
  • gcmc – Set to True to enable the GCMC production stage. Default is False.
  • solvate – Set to True to enable the Solvate Pocket stage. Default is False.
  • modify_dihe – Set to True to modify retained dihedral angle interactions for customized core. Default is False.
  • minimize_volume – Set to True to turn on volume minimization during the system_builder or build_geometry stages. Default is False.
patch_ensemble()

A context manager to temporarily change the ensemble and subjob_msj template for this instance to ‘NVT’ if the ensemble is ‘NPT’ and this is a GCMC simulation. NOTE: This is useful to allow the complex and solvent legs to have different ensembles, but in the future this should be replaced with code that natively supports different ensembles for the complex and solvent leg.

generate_master_msj()
generate_complex_msj(net_charge, ch=False)
generate_solvent_msj(net_charge, ch=False)
generate_subjob_msj(buffer_width, is_complex_leg=False, net_charge=False, ch=False, treat_solvent_like_complex=False)
write_master_msj()
write_complex_msj()
write_solvent_msj()
modify_fep_launcher_stage(raw)
modify_graph_stage(raw)
__class__

alias of builtins.type

__delattr__

Implement delattr(self, name).

__dict__ = mappingproxy({'__module__': 'schrodinger.application.desmond.mapper_msj_generator', '__doc__': '\n ', '__init__': <function MapperMsjGenerator.__init__>, 'patch_ensemble': <function MapperMsjGenerator.patch_ensemble>, 'generate_master_msj': <function MapperMsjGenerator.generate_master_msj>, 'generate_complex_msj': <function MapperMsjGenerator.generate_complex_msj>, 'generate_solvent_msj': <function MapperMsjGenerator.generate_solvent_msj>, 'generate_subjob_msj': <function MapperMsjGenerator.generate_subjob_msj>, 'write_master_msj': <function MapperMsjGenerator.write_master_msj>, 'write_complex_msj': <function MapperMsjGenerator.write_complex_msj>, 'write_solvent_msj': <function MapperMsjGenerator.write_solvent_msj>, 'modify_fep_launcher_stage': <function MapperMsjGenerator.modify_fep_launcher_stage>, 'modify_graph_stage': <function MapperMsjGenerator.modify_graph_stage>, '_set_subjob_msj': <function MapperMsjGenerator._set_subjob_msj>, '_set_net_charge_box': <function MapperMsjGenerator._set_net_charge_box>, '_set_lambda_hopping': <function MapperMsjGenerator._set_lambda_hopping>, '_set_modify_dihedral': <function MapperMsjGenerator._set_modify_dihedral>, '_set_minimize_volume': <function MapperMsjGenerator._set_minimize_volume>, '_set_membrane_parameters': <function MapperMsjGenerator._set_membrane_parameters>, '_set_solvate': <function MapperMsjGenerator._set_solvate>, '_set_gcmc_stage_params': <function MapperMsjGenerator._set_gcmc_stage_params>, '_find_solvate_pocket_stage': <function MapperMsjGenerator._find_solvate_pocket_stage>, '_set_gcmc': <function MapperMsjGenerator._set_gcmc>, '_set_fep_type': <function MapperMsjGenerator._set_fep_type>})
__dir__() → list

default dir() implementation

__eq__

Return self==value.

__format__()

default object formatter

__ge__

Return self>=value.

__getattribute__

Return getattr(self, name).

__gt__

Return self>value.

__hash__

Return hash(self).

__init_subclass__()

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__

Return self<=value.

__lt__

Return self<value.

__module__ = 'schrodinger.application.desmond.mapper_msj_generator'
__ne__

Return self!=value.

__new__()

Create and return a new object. See help(type) for accurate signature.

__reduce__()

helper for pickle

__reduce_ex__()

helper for pickle

__repr__

Return repr(self).

__setattr__

Implement setattr(self, name, value).

__sizeof__() → int

size of object in memory, in bytes

__str__

Return str(self).

__subclasshook__()

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

__weakref__

list of weak references to the object (if defined)

class schrodinger.application.desmond.mapper_msj_generator.VacuumMsjGenerator(jobname, cd_params, **kwargs)

Bases: schrodinger.application.desmond.mapper_msj_generator.MapperMsjGenerator

__init__(jobname, cd_params, **kwargs)

See MapperMsjGenerator for a description of the input parameters.

generate_vacuum_msj(net_charge=False, core_hopping=False)
write_vacuum_msj(concatenate=False)
modify_fep_launcher_stage(raw)
modify_graph_stage(raw)
__class__

alias of builtins.type

__delattr__

Implement delattr(self, name).

__dict__ = mappingproxy({'__module__': 'schrodinger.application.desmond.mapper_msj_generator', '__doc__': '\n ', '__init__': <function VacuumMsjGenerator.__init__>, 'generate_vacuum_msj': <function VacuumMsjGenerator.generate_vacuum_msj>, 'write_vacuum_msj': <function VacuumMsjGenerator.write_vacuum_msj>, 'modify_fep_launcher_stage': <function VacuumMsjGenerator.modify_fep_launcher_stage>, 'modify_graph_stage': <function VacuumMsjGenerator.modify_graph_stage>, '_set_subjob_msj': <function VacuumMsjGenerator._set_subjob_msj>})
__dir__() → list

default dir() implementation

__eq__

Return self==value.

__format__()

default object formatter

__ge__

Return self>=value.

__getattribute__

Return getattr(self, name).

__gt__

Return self>value.

__hash__

Return hash(self).

__init_subclass__()

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__

Return self<=value.

__lt__

Return self<value.

__module__ = 'schrodinger.application.desmond.mapper_msj_generator'
__ne__

Return self!=value.

__new__()

Create and return a new object. See help(type) for accurate signature.

__reduce__()

helper for pickle

__reduce_ex__()

helper for pickle

__repr__

Return repr(self).

__setattr__

Implement setattr(self, name, value).

__sizeof__() → int

size of object in memory, in bytes

__str__

Return str(self).

__subclasshook__()

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

__weakref__

list of weak references to the object (if defined)

generate_complex_msj(net_charge, ch=False)
generate_master_msj()
generate_solvent_msj(net_charge, ch=False)
generate_subjob_msj(buffer_width, is_complex_leg=False, net_charge=False, ch=False, treat_solvent_like_complex=False)
patch_ensemble()

A context manager to temporarily change the ensemble and subjob_msj template for this instance to ‘NVT’ if the ensemble is ‘NPT’ and this is a GCMC simulation. NOTE: This is useful to allow the complex and solvent legs to have different ensembles, but in the future this should be replaced with code that natively supports different ensembles for the complex and solvent leg.

write_complex_msj()
write_master_msj()
write_solvent_msj()
class schrodinger.application.desmond.mapper_msj_generator.CovalentMsjGenerator(jobname: str, cd_params: Dict[str, object], fmp_fname: str, **kwargs)

Bases: schrodinger.application.desmond.mapper_msj_generator.MapperMsjGenerator

__init__(jobname: str, cd_params: Dict[str, object], fmp_fname: str, **kwargs)

See MapperMsjGenerator for a description of the input parameters.

In addition to these parameters, the following are supported.

Parameters:fmp_fname – Name of the fmp file to use for covalent fep.
generate_subjob_msj(buffer_width, is_complex_leg=False, net_charge=False, ch=False, treat_solvent_like_complex=False)
modify_graph_stage(raw)

Not support custom .pkl file for now

__class__

alias of builtins.type

__delattr__

Implement delattr(self, name).

__dict__ = mappingproxy({'__module__': 'schrodinger.application.desmond.mapper_msj_generator', '__doc__': '\n ', '__init__': <function CovalentMsjGenerator.__init__>, 'generate_subjob_msj': <function CovalentMsjGenerator.generate_subjob_msj>, 'modify_graph_stage': <function CovalentMsjGenerator.modify_graph_stage>})
__dir__() → list

default dir() implementation

__eq__

Return self==value.

__format__()

default object formatter

__ge__

Return self>=value.

__getattribute__

Return getattr(self, name).

__gt__

Return self>value.

__hash__

Return hash(self).

__init_subclass__()

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__

Return self<=value.

__lt__

Return self<value.

__module__ = 'schrodinger.application.desmond.mapper_msj_generator'
__ne__

Return self!=value.

__new__()

Create and return a new object. See help(type) for accurate signature.

__reduce__()

helper for pickle

__reduce_ex__()

helper for pickle

__repr__

Return repr(self).

__setattr__

Implement setattr(self, name, value).

__sizeof__() → int

size of object in memory, in bytes

__str__

Return str(self).

__subclasshook__()

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

__weakref__

list of weak references to the object (if defined)

generate_complex_msj(net_charge, ch=False)
generate_master_msj()
generate_solvent_msj(net_charge, ch=False)
modify_fep_launcher_stage(raw)
patch_ensemble()

A context manager to temporarily change the ensemble and subjob_msj template for this instance to ‘NVT’ if the ensemble is ‘NPT’ and this is a GCMC simulation. NOTE: This is useful to allow the complex and solvent legs to have different ensembles, but in the future this should be replaced with code that natively supports different ensembles for the complex and solvent leg.

write_complex_msj()
write_master_msj()
write_solvent_msj()
class schrodinger.application.desmond.mapper_msj_generator.MetalMsjGenerator(jobname: str, cd_params: Dict[str, object], mp: List[str], **kwargs)

Bases: schrodinger.application.desmond.mapper_msj_generator.MapperMsjGenerator

__init__(jobname: str, cd_params: Dict[str, object], mp: List[str], **kwargs)

See MapperMsjGenerator for a description of the input parameters.

In addition to these parameters, the following are supported.

Parameters:mp – List of metalloprotein ct properties.
generate_subjob_msj(buffer_width, is_complex_leg=False, net_charge=False, ch=False, treat_solvent_like_complex=False)
modify_graph_stage(raw)
__class__

alias of builtins.type

__delattr__

Implement delattr(self, name).

__dict__ = mappingproxy({'__module__': 'schrodinger.application.desmond.mapper_msj_generator', '__doc__': '\n ', '__init__': <function MetalMsjGenerator.__init__>, 'generate_subjob_msj': <function MetalMsjGenerator.generate_subjob_msj>, 'modify_graph_stage': <function MetalMsjGenerator.modify_graph_stage>})
__dir__() → list

default dir() implementation

__eq__

Return self==value.

__format__()

default object formatter

__ge__

Return self>=value.

__getattribute__

Return getattr(self, name).

__gt__

Return self>value.

__hash__

Return hash(self).

__init_subclass__()

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__

Return self<=value.

__lt__

Return self<value.

__module__ = 'schrodinger.application.desmond.mapper_msj_generator'
__ne__

Return self!=value.

__new__()

Create and return a new object. See help(type) for accurate signature.

__reduce__()

helper for pickle

__reduce_ex__()

helper for pickle

__repr__

Return repr(self).

__setattr__

Implement setattr(self, name, value).

__sizeof__() → int

size of object in memory, in bytes

__str__

Return str(self).

__subclasshook__()

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

__weakref__

list of weak references to the object (if defined)

generate_complex_msj(net_charge, ch=False)
generate_master_msj()
generate_solvent_msj(net_charge, ch=False)
modify_fep_launcher_stage(raw)
patch_ensemble()

A context manager to temporarily change the ensemble and subjob_msj template for this instance to ‘NVT’ if the ensemble is ‘NPT’ and this is a GCMC simulation. NOTE: This is useful to allow the complex and solvent legs to have different ensembles, but in the future this should be replaced with code that natively supports different ensembles for the complex and solvent leg.

write_complex_msj()
write_master_msj()
write_solvent_msj()
class schrodinger.application.desmond.mapper_msj_generator.ProteinMapperMsjGenerator(jobname: str, cd_params: Dict[str, object], fep_type: str, solvent_asl: Union[str, NoneType] = None, mutation_filename: str = 'mutations.txt', residue_file: str = '', neighbor: Union[int, NoneType] = None, **kwargs)

Bases: schrodinger.application.desmond.mapper_msj_generator.CovalentMsjGenerator

__init__(jobname: str, cd_params: Dict[str, object], fep_type: str, solvent_asl: Union[str, NoneType] = None, mutation_filename: str = 'mutations.txt', residue_file: str = '', neighbor: Union[int, NoneType] = None, **kwargs)

See MapperMsjGenerator for a description of the input parameters.

In addition to these parameters, the following are supported.

Parameters:
  • fep_type – Type of protein fep.
  • neighbor – Number of residues to flank the mutated residue when creating the mutant peptides. Its default value will be set based on fep_type.
  • solvent_asl – Specify ASL to put in solvent leg for protein residue mutation.
  • mutation_filename – Filename containing the list of mutations.
  • residue_file – Mae filename which contains the non-standard amino-acids structures.
generate_solvent_msj(net_charge, ch=False)
generate_subjob_msj(buffer_width, is_complex_leg=False, net_charge=False, ch=False)

For protein or ligand selectivity, the subjob msj file will be the same as small molecule workflow; For protein stability, the subjob msj file will be the same as covalent bond workflow.

modify_graph_stage(raw)
__class__

alias of builtins.type

__delattr__

Implement delattr(self, name).

__dict__ = mappingproxy({'__module__': 'schrodinger.application.desmond.mapper_msj_generator', '__doc__': '\n ', '__init__': <function ProteinMapperMsjGenerator.__init__>, 'generate_solvent_msj': <function ProteinMapperMsjGenerator.generate_solvent_msj>, 'generate_subjob_msj': <function ProteinMapperMsjGenerator.generate_subjob_msj>, 'modify_graph_stage': <function ProteinMapperMsjGenerator.modify_graph_stage>})
__dir__() → list

default dir() implementation

__eq__

Return self==value.

__format__()

default object formatter

__ge__

Return self>=value.

__getattribute__

Return getattr(self, name).

__gt__

Return self>value.

__hash__

Return hash(self).

__init_subclass__()

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__

Return self<=value.

__lt__

Return self<value.

__module__ = 'schrodinger.application.desmond.mapper_msj_generator'
__ne__

Return self!=value.

__new__()

Create and return a new object. See help(type) for accurate signature.

__reduce__()

helper for pickle

__reduce_ex__()

helper for pickle

__repr__

Return repr(self).

__setattr__

Implement setattr(self, name, value).

__sizeof__() → int

size of object in memory, in bytes

__str__

Return str(self).

__subclasshook__()

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

__weakref__

list of weak references to the object (if defined)

generate_complex_msj(net_charge, ch=False)
generate_master_msj()
modify_fep_launcher_stage(raw)
patch_ensemble()

A context manager to temporarily change the ensemble and subjob_msj template for this instance to ‘NVT’ if the ensemble is ‘NPT’ and this is a GCMC simulation. NOTE: This is useful to allow the complex and solvent legs to have different ensembles, but in the future this should be replaced with code that natively supports different ensembles for the complex and solvent leg.

write_complex_msj()
write_master_msj()
write_solvent_msj()
class schrodinger.application.desmond.mapper_msj_generator.SolubilityMsjGenerator(jobname: str, cd_params: Dict[str, object], **kwargs)

Bases: schrodinger.application.desmond.mapper_msj_generator.BaseMsjGenerator

Generates the msj files needed to run the Solubility FEP workflow.

__init__(jobname: str, cd_params: Dict[str, object], **kwargs)

See BaseMsjGenerator for a description of the input parameters.

In addition to these parameters, the following are supported.

Parameters:
  • hydration_fep_sim_time – The simulation time for the Hydration FEP production stage.
  • sublimation_fep_sim_time – The simulation time for the Sublimation FEP production stage.
generate_master_msj() → schrodinger.utils.sea.Map

Generate the master msj.

generate_subjob_msj(is_fep: bool = True, hydration: bool = False) → schrodinger.utils.sea.Map

Generate the fep msj and return as a sea.Map.

Parameters:
  • is_fep – Set to True for FEP subjob, False for MD.
  • hydration – Set to True to for hydration FEP and False for sublimation FEP. Ignored if not FEP.
write_master_msj() → str

Write out the master msj and return the filename.

write_md_msj() → str

Write out the md msj and return the filename.

write_fep_msj() → None

Write out the fep msj files.

__class__

alias of builtins.type

__delattr__

Implement delattr(self, name).

__dict__ = mappingproxy({'__module__': 'schrodinger.application.desmond.mapper_msj_generator', '__doc__': '\n Generates the msj files needed to run the Solubility FEP workflow.\n\n ', '__init__': <function SolubilityMsjGenerator.__init__>, 'generate_master_msj': <function SolubilityMsjGenerator.generate_master_msj>, 'generate_subjob_msj': <function SolubilityMsjGenerator.generate_subjob_msj>, 'write_master_msj': <function SolubilityMsjGenerator.write_master_msj>, 'write_md_msj': <function SolubilityMsjGenerator.write_md_msj>, 'write_fep_msj': <function SolubilityMsjGenerator.write_fep_msj>})
__dir__() → list

default dir() implementation

__eq__

Return self==value.

__format__()

default object formatter

__ge__

Return self>=value.

__getattribute__

Return getattr(self, name).

__gt__

Return self>value.

__hash__

Return hash(self).

__init_subclass__()

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__

Return self<=value.

__lt__

Return self<value.

__module__ = 'schrodinger.application.desmond.mapper_msj_generator'
__ne__

Return self!=value.

__new__()

Create and return a new object. See help(type) for accurate signature.

__reduce__()

helper for pickle

__reduce_ex__()

helper for pickle

__repr__

Return repr(self).

__setattr__

Implement setattr(self, name, value).

__sizeof__() → int

size of object in memory, in bytes

__str__

Return str(self).

__subclasshook__()

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

__weakref__

list of weak references to the object (if defined)

class schrodinger.application.desmond.mapper_msj_generator.MixedSolventMsjGenerator(jobname: str, cd_params: Dict[str, object], builder_params: Dict[str, object], **kwargs)

Bases: schrodinger.application.desmond.mapper_msj_generator.BaseMsjGenerator

__init__(jobname: str, cd_params: Dict[str, object], builder_params: Dict[str, object], **kwargs)
Parameters:
  • jobname – The jobname.
  • cd_params – A dictionary, with the keys gpus, set to True for GPU jobs, and cpus, set to the number of cpus/gpus to use.
  • forcefield (str) – The name of the forcefield to use.
  • sim_time (int) – The simulation time for the production stage in ps.
  • sim_time_complex (int) – The simulation time for the complex leg in ps
  • sim_time_solvent (int) – The simulation time for the solvent leg in ps
  • rand_seed (int) – The random seed.
  • ensemble (str) – The ensemble, NPT or NVT.
  • buffer_width (float) – The buffer width in Angstrom determines how much solvent is added to the solute. This is only used if it is larger than the default buffer width.
  • lambda_windows (int) – Number of lambda replicas to use for the FEP stages.
  • custom_charge_mode (CUSTOM_CHARGE_MODE) – Set to CUSTOM_CHARGE_MODE.ASSIGN to assign custom charges. Set to CUSTOM_CHARGE_MODE.CLEAR to clear custom charges if present, without reassigning. Set to CUSTOM_CHARGE_MODE.KEEP to keep existing custom charges if present.
  • h_mass (bool) – Set to True to enable hydrogen mass repartitioning and False to disable it. Default is True.
  • concatenate (bool) – Set to True to concatenate the equilibration FEP stages. Default is True.
write_master_msj() → str
write_md_msj() → str
generate_master_msj() → List[schrodinger.utils.sea.Map]
generate_subjob_msj() → List[schrodinger.utils.sea.Map]
__class__

alias of builtins.type

__delattr__

Implement delattr(self, name).

__dict__ = mappingproxy({'__module__': 'schrodinger.application.desmond.mapper_msj_generator', '__init__': <function MixedSolventMsjGenerator.__init__>, 'write_master_msj': <function MixedSolventMsjGenerator.write_master_msj>, 'write_md_msj': <function MixedSolventMsjGenerator.write_md_msj>, 'generate_master_msj': <function MixedSolventMsjGenerator.generate_master_msj>, 'generate_subjob_msj': <function MixedSolventMsjGenerator.generate_subjob_msj>, '_set_time': <function MixedSolventMsjGenerator._set_time>, '_set_system_builder_params': <function MixedSolventMsjGenerator._set_system_builder_params>, '__doc__': None})
__dir__() → list

default dir() implementation

__eq__

Return self==value.

__format__()

default object formatter

__ge__

Return self>=value.

__getattribute__

Return getattr(self, name).

__gt__

Return self>value.

__hash__

Return hash(self).

__init_subclass__()

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__

Return self<=value.

__lt__

Return self<value.

__module__ = 'schrodinger.application.desmond.mapper_msj_generator'
__ne__

Return self!=value.

__new__()

Create and return a new object. See help(type) for accurate signature.

__reduce__()

helper for pickle

__reduce_ex__()

helper for pickle

__repr__

Return repr(self).

__setattr__

Implement setattr(self, name, value).

__sizeof__() → int

size of object in memory, in bytes

__str__

Return str(self).

__subclasshook__()

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

__weakref__

list of weak references to the object (if defined)