mdfptools package

Submodules

mdfptools.Composer module

class mdfptools.Composer.MDFP(mdfp_dict)[source]

Bases: object

A MDFP object contains a set of features for a molecule, obtaining from a simulation or a set of simulations.

Methods

get_mdfp(self)

returns
__init__(self, mdfp_dict)[source]
Parameters

fp_dict (dict) –

Keys are each of the type features a given Extractor obtains, e.g. “2d_count” are the 2D topological features obtained from molecule SMILES, “intra_lj” are the intra-molecular LJ energies obtained from simulation.

Values are the corresponding set of numerics, stored as lists.

get_mdfp(self)[source]
Returns

Return type

a list of floating values, i.e. the mdfp feature vector

class mdfptools.Composer.BaseComposer[source]

Bases: object

The BaseComposer class containing functions that can be used by different composers for different types of simulations

Methods

run(smiles)

param smiles

SMILES string of the solute molecule
classmethod run(smiles)[source]
Parameters

smiles (str) – SMILES string of the solute molecule

classmethod _get_relevant_properties()[source]

Where the set of features to be included in the final MDFP are defined

classmethod _get_2d_descriptors()[source]

Obtain those 2D topological features as described in the original publication.

classmethod _get_statistical_moments(property_extractor, statistical_moments=[<function mean at 0x7f3b88a77730>, <function std at 0x7f3b88a778c8>, <function median at 0x7f3b8892d950>], **kwargs)[source]

Performs statistical weighting of the numerical properties (e.g. LJ and electrostatics energies) obtained from each frame of simulation.

Parameters

  • property_extractor (mdfptools.Extractor) – The particular type of Extractor methodclass used to obtain the various properties from simulation.

  • statistical_moments (list) – The list of statistical weighting to be performed to each properties from all the frames. Default list of weighting are the mean, standard deviation and median.

__init__(self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

class mdfptools.Composer.SolutionComposer[source]

Bases: mdfptools.Composer.BaseComposer

Composer used to extract features from solution simulations, namely one copy of solute in water solvent. This generates fingerprint most akin to that from the original publication.

Methods

run(mdtraj_obj, parmed_obj[, smiles])

param mdtraj_obj

The simulated trajectory
classmethod run(mdtraj_obj, parmed_obj, smiles=None, **kwargs)[source]
Parameters

  • mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • smiles (str) – SMILES string of the solute. If mdfptools.Parameteriser was used during parameterisation, then smiles is automatically obtained from the parmed_obj.

classmethod _get_relevant_properties()[source]

Where the set of features to be included in the final MDFP are defined

__init__(self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

classmethod _get_2d_descriptors()

Obtain those 2D topological features as described in the original publication.

classmethod _get_statistical_moments(property_extractor, statistical_moments=[<function mean at 0x7f3b88a77730>, <function std at 0x7f3b88a778c8>, <function median at 0x7f3b8892d950>], **kwargs)

Performs statistical weighting of the numerical properties (e.g. LJ and electrostatics energies) obtained from each frame of simulation.

Parameters

  • property_extractor (mdfptools.Extractor) – The particular type of Extractor methodclass used to obtain the various properties from simulation.

  • statistical_moments (list) – The list of statistical weighting to be performed to each properties from all the frames. Default list of weighting are the mean, standard deviation and median.

class mdfptools.Composer.LiquidComposer[source]

Bases: mdfptools.Composer.BaseComposer

Composer used to extract features from liquid simulations, namely a box containing replicates of the same molecule.

Methods

run(mdtraj_obj, parmed_obj[, smiles])

param mdtraj_obj

The simulated trajectory
classmethod run(mdtraj_obj, parmed_obj, smiles=None, **kwargs)[source]
Parameters

  • mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • smiles (str) – SMILES string of one copy of the solute. If mdfptools.Parameteriser was used during parameterisation, then smiles is automatically obtained from the parmed_obj.

classmethod _get_relevant_properties()[source]

Where the set of features to be included in the final MDFP are defined

__init__(self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

classmethod _get_2d_descriptors()

Obtain those 2D topological features as described in the original publication.

classmethod _get_statistical_moments(property_extractor, statistical_moments=[<function mean at 0x7f3b88a77730>, <function std at 0x7f3b88a778c8>, <function median at 0x7f3b8892d950>], **kwargs)

Performs statistical weighting of the numerical properties (e.g. LJ and electrostatics energies) obtained from each frame of simulation.

Parameters

  • property_extractor (mdfptools.Extractor) – The particular type of Extractor methodclass used to obtain the various properties from simulation.

  • statistical_moments (list) – The list of statistical weighting to be performed to each properties from all the frames. Default list of weighting are the mean, standard deviation and median.

class mdfptools.Composer.SolutionLiquidComposer(solv_mdtraj_obj, solv_parmed_obj, liq_mdtraj_obj, liq_parmed_obj, smiles=None, **kwargs)[source]

Bases: mdfptools.Composer.BaseComposer

Composer used to extract features from pairs of solution and liquid simulations.

Methods

run(smiles)

param smiles

SMILES string of the solute molecule
classmethod __init__(solv_mdtraj_obj, solv_parmed_obj, liq_mdtraj_obj, liq_parmed_obj, smiles=None, **kwargs)[source]
Parameters

  • solv_mdtraj_obj (mdtraj.trajectory) – The simulated solution trajectory

  • solv_parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated solution system.

  • liq_mdtraj_obj (mdtraj.trajectory) – The simulated liquid trajectory

  • liq_parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated liquid system.

  • smiles (str) – SMILES string of one copy of the solute. If mdfptools.Parameteriser was used during parameterisation, then smiles is automatically obtained from the parmed_obj.

classmethod _get_2d_descriptors()

Obtain those 2D topological features as described in the original publication.

classmethod _get_statistical_moments(property_extractor, statistical_moments=[<function mean at 0x7f3b88a77730>, <function std at 0x7f3b88a778c8>, <function median at 0x7f3b8892d950>], **kwargs)

Performs statistical weighting of the numerical properties (e.g. LJ and electrostatics energies) obtained from each frame of simulation.

Parameters

  • property_extractor (mdfptools.Extractor) – The particular type of Extractor methodclass used to obtain the various properties from simulation.

  • statistical_moments (list) – The list of statistical weighting to be performed to each properties from all the frames. Default list of weighting are the mean, standard deviation and median.

classmethod run(smiles)
Parameters

smiles (str) – SMILES string of the solute molecule

classmethod _get_relevant_properties()[source]

Where the set of features to be included in the final MDFP are defined

mdfptools.Extractor module

class mdfptools.Extractor.BaseExtractor[source]

Bases: object

Warning

The base class should not be used directly

Methods

extract_energies(mdtraj_obj, parmed_obj[, …])

Extracting the various energetic components described in the original publication from each frame of simulation.

extract_rgyr(mdtraj_obj, \*\*kwargs)

Extracting radius of gyration from each frame of simulation.

extract_sasa(mdtraj_obj, \*\*kwargs)

Extracting solvent accessible surface area from each frame of simulation.
string_identifier = '!Should_Call_From_Inherited_Class'
classmethod _solute_solvent_split(topology)[source]

Abstract method

classmethod _get_all_exception_atom_pairs(system, topology)[source]

Abstract method

classmethod _extract_energies_helper(mdtraj_obj, parmed_obj, platform='CPU', **kwargs)[source]

Helper function for extracting the various energetic components described in the original publication from each frame of simulation. OpenMM.CustomNonbondedForces are used. Specifically, the reaction field defintion is taken from GROMOS96 manual.

Parameters

  • mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • platform (str) – The computing architecture to do the calculation, default to CPU, CUDA, OpenCL is also possible.

Returns

  • context (Openmm.Context)

  • integrator (Openmm.Integrator)

classmethod extract_energies(mdtraj_obj, parmed_obj, platform='CPU', **kwargs)[source]

Extracting the various energetic components described in the original publication from each frame of simulation.

Parameters

  • mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • platform (str) – The computing architecture to do the calculation, default to CPU, CUDA, OpenCL is also possible.

Returns

df – Keys are each of the energetic type features. e.g. “intra_lj” are the intra-molecular LJ energies obtained from simulation.

Values are the corresponding set of numerics, stored as lists.

Return type

dict

classmethod extract_rgyr(mdtraj_obj, **kwargs)[source]

Extracting radius of gyration from each frame of simulation. Assumes the first residue in the system is the solute.

Parameters

mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

Returns

df – Key is prefix_rgyr, where prefix changes depending on the type of Extractor class used. Values are the corresponding set of numerics, stored as lists.

Return type

dict

classmethod extract_sasa(mdtraj_obj, **kwargs)[source]

Extracting solvent accessible surface area from each frame of simulation. Assumes the first residue in the system is the solute.

Parameters

mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

Returns

df – Key is prefix_sasa, where prefix changes depending on the type of Extractor class used. Values are the corresponding set of numerics, stored as lists.

Return type

dict

__init__(self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

class mdfptools.Extractor.SolutionExtractor[source]

Bases: mdfptools.Extractor.BaseExtractor

Extraction from condensed phase simulation where the system is composed of one solute molecule surronded by solvents

Parameters

string_identifier (str) – The string identifier tagged as prefix to all values extracted in this class.

Methods

extract_dipole(mdtraj_obj, parmed_obj, …)

Extracting dipole moment from each frame of simulation.

extract_energies(mdtraj_obj, parmed_obj[, …])

Extracting the various energetic components described in the original publication from each frame of simulation.

extract_rgyr(mdtraj_obj, \*\*kwargs)

Extracting radius of gyration from each frame of simulation.

extract_sasa(mdtraj_obj, \*\*kwargs)

Extracting solvent accessible surface area from each frame of simulation.
string_identifier = 'solution'
classmethod _solute_solvent_split(topology)[source]

Distinguish solutes from solvents, used in _extract_energies_helper()

The following is assumed:

  • there are only two type of residues

  • the residue that is lesser in number is the solute

Parameters

topology (parmed.topology) –

Returns

  • solute_atoms (set) – set of solute_atoms indices

  • solvent_atoms (set) – set of solvent_atoms indices

classmethod _get_all_exception_atom_pairs(system, topology)[source]

Using the parametersied system to obtain the exception and exclusion pairs, used in _extract_energies_helper(). This is inferred purely from the parameterised system and connectivity.

Parameters

  • system (OpenMM.System) –

  • topology (parmed.topology) –

Returns

  • solute_1_4_pairs (set)

  • solvent_1_4_pairs (set)

  • solute_excluded_pairs (set)

  • solvent_excluded_pairs (set)

  • solute_self_pairs (set)

  • solvent_self_pairs (set)

classmethod extract_dipole(mdtraj_obj, parmed_obj, **kwargs)[source]

Extracting dipole moment from each frame of simulation. Assumes the first residue in the system is the solute.

Parameters

  • mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

Returns

df – Key is prefix_dipole_postfix, where prefix changes depending on the type of Extractor class used, postfix can be {x,y,z,magnitude}. Values are the corresponding set of numerics, stored as lists.

Return type

dict

__init__(self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

classmethod _extract_energies_helper(mdtraj_obj, parmed_obj, platform='CPU', **kwargs)

Helper function for extracting the various energetic components described in the original publication from each frame of simulation. OpenMM.CustomNonbondedForces are used. Specifically, the reaction field defintion is taken from GROMOS96 manual.

Parameters

  • mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • platform (str) – The computing architecture to do the calculation, default to CPU, CUDA, OpenCL is also possible.

Returns

  • context (Openmm.Context)

  • integrator (Openmm.Integrator)

classmethod extract_energies(mdtraj_obj, parmed_obj, platform='CPU', **kwargs)

Extracting the various energetic components described in the original publication from each frame of simulation.

Parameters

  • mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • platform (str) – The computing architecture to do the calculation, default to CPU, CUDA, OpenCL is also possible.

Returns

df – Keys are each of the energetic type features. e.g. “intra_lj” are the intra-molecular LJ energies obtained from simulation.

Values are the corresponding set of numerics, stored as lists.

Return type

dict

classmethod extract_rgyr(mdtraj_obj, **kwargs)

Extracting radius of gyration from each frame of simulation. Assumes the first residue in the system is the solute.

Parameters

mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

Returns

df – Key is prefix_rgyr, where prefix changes depending on the type of Extractor class used. Values are the corresponding set of numerics, stored as lists.

Return type

dict

classmethod extract_sasa(mdtraj_obj, **kwargs)

Extracting solvent accessible surface area from each frame of simulation. Assumes the first residue in the system is the solute.

Parameters

mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

Returns

df – Key is prefix_sasa, where prefix changes depending on the type of Extractor class used. Values are the corresponding set of numerics, stored as lists.

Return type

dict

class mdfptools.Extractor.TrialSolutionExtractor[source]

Bases: mdfptools.Extractor.SolutionExtractor

Methods

extract_dipole(mdtraj_obj, parmed_obj, …)

Extracting dipole moment from each frame of simulation.

extract_energies(mdtraj_obj, parmed_obj[, …])

Extracting the various energetic components described in the original publication from each frame of simulation.

extract_rgyr(mdtraj_obj, \*\*kwargs)

Extracting radius of gyration from each frame of simulation.

extract_sasa(mdtraj_obj, \*\*kwargs)

Extracting solvent accessible surface area from each frame of simulation.
string_identifier = 'TrialSolution'
classmethod extract_energies(mdtraj_obj, parmed_obj, platform='CPU', **kwargs)[source]

Extracting the various energetic components described in the original publication from each frame of simulation.

Parameters

  • mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • platform (str) – The computing architecture to do the calculation, default to CPU, CUDA, OpenCL is also possible.

Returns

df – Keys are each of the energetic type features. e.g. “intra_lj” are the intra-molecular LJ energies obtained from simulation.

Values are the corresponding set of numerics, stored as lists.

Return type

dict

__init__(self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

classmethod _extract_energies_helper(mdtraj_obj, parmed_obj, platform='CPU', **kwargs)

Helper function for extracting the various energetic components described in the original publication from each frame of simulation. OpenMM.CustomNonbondedForces are used. Specifically, the reaction field defintion is taken from GROMOS96 manual.

Parameters

  • mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • platform (str) – The computing architecture to do the calculation, default to CPU, CUDA, OpenCL is also possible.

Returns

  • context (Openmm.Context)

  • integrator (Openmm.Integrator)

classmethod _get_all_exception_atom_pairs(system, topology)

Using the parametersied system to obtain the exception and exclusion pairs, used in _extract_energies_helper(). This is inferred purely from the parameterised system and connectivity.

Parameters

  • system (OpenMM.System) –

  • topology (parmed.topology) –

Returns

  • solute_1_4_pairs (set)

  • solvent_1_4_pairs (set)

  • solute_excluded_pairs (set)

  • solvent_excluded_pairs (set)

  • solute_self_pairs (set)

  • solvent_self_pairs (set)

classmethod _solute_solvent_split(topology)

Distinguish solutes from solvents, used in _extract_energies_helper()

The following is assumed:

  • there are only two type of residues

  • the residue that is lesser in number is the solute

Parameters

topology (parmed.topology) –

Returns

  • solute_atoms (set) – set of solute_atoms indices

  • solvent_atoms (set) – set of solvent_atoms indices

classmethod extract_dipole(mdtraj_obj, parmed_obj, **kwargs)

Extracting dipole moment from each frame of simulation. Assumes the first residue in the system is the solute.

Parameters

  • mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

Returns

df – Key is prefix_dipole_postfix, where prefix changes depending on the type of Extractor class used, postfix can be {x,y,z,magnitude}. Values are the corresponding set of numerics, stored as lists.

Return type

dict

classmethod extract_rgyr(mdtraj_obj, **kwargs)

Extracting radius of gyration from each frame of simulation. Assumes the first residue in the system is the solute.

Parameters

mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

Returns

df – Key is prefix_rgyr, where prefix changes depending on the type of Extractor class used. Values are the corresponding set of numerics, stored as lists.

Return type

dict

classmethod extract_sasa(mdtraj_obj, **kwargs)

Extracting solvent accessible surface area from each frame of simulation. Assumes the first residue in the system is the solute.

Parameters

mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

Returns

df – Key is prefix_sasa, where prefix changes depending on the type of Extractor class used. Values are the corresponding set of numerics, stored as lists.

Return type

dict

class mdfptools.Extractor.WaterExtractor[source]

Bases: mdfptools.Extractor.SolutionExtractor

Synonyms class as SolutionExtractor

Parameters

string_identifier (str) – The string identifier tagged as prefix to all values extracted in this class.

Methods

extract_dipole(mdtraj_obj, parmed_obj, …)

Extracting dipole moment from each frame of simulation.

extract_energies(mdtraj_obj, parmed_obj[, …])

Extracting the various energetic components described in the original publication from each frame of simulation.

extract_rgyr(mdtraj_obj, \*\*kwargs)

Extracting radius of gyration from each frame of simulation.

extract_sasa(mdtraj_obj, \*\*kwargs)

Extracting solvent accessible surface area from each frame of simulation.
string_identifier = 'water'
__init__(self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

classmethod _extract_energies_helper(mdtraj_obj, parmed_obj, platform='CPU', **kwargs)

Helper function for extracting the various energetic components described in the original publication from each frame of simulation. OpenMM.CustomNonbondedForces are used. Specifically, the reaction field defintion is taken from GROMOS96 manual.

Parameters

  • mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • platform (str) – The computing architecture to do the calculation, default to CPU, CUDA, OpenCL is also possible.

Returns

  • context (Openmm.Context)

  • integrator (Openmm.Integrator)

classmethod _get_all_exception_atom_pairs(system, topology)

Using the parametersied system to obtain the exception and exclusion pairs, used in _extract_energies_helper(). This is inferred purely from the parameterised system and connectivity.

Parameters

  • system (OpenMM.System) –

  • topology (parmed.topology) –

Returns

  • solute_1_4_pairs (set)

  • solvent_1_4_pairs (set)

  • solute_excluded_pairs (set)

  • solvent_excluded_pairs (set)

  • solute_self_pairs (set)

  • solvent_self_pairs (set)

classmethod _solute_solvent_split(topology)

Distinguish solutes from solvents, used in _extract_energies_helper()

The following is assumed:

  • there are only two type of residues

  • the residue that is lesser in number is the solute

Parameters

topology (parmed.topology) –

Returns

  • solute_atoms (set) – set of solute_atoms indices

  • solvent_atoms (set) – set of solvent_atoms indices

classmethod extract_dipole(mdtraj_obj, parmed_obj, **kwargs)

Extracting dipole moment from each frame of simulation. Assumes the first residue in the system is the solute.

Parameters

  • mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

Returns

df – Key is prefix_dipole_postfix, where prefix changes depending on the type of Extractor class used, postfix can be {x,y,z,magnitude}. Values are the corresponding set of numerics, stored as lists.

Return type

dict

classmethod extract_energies(mdtraj_obj, parmed_obj, platform='CPU', **kwargs)

Extracting the various energetic components described in the original publication from each frame of simulation.

Parameters

  • mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • platform (str) – The computing architecture to do the calculation, default to CPU, CUDA, OpenCL is also possible.

Returns

df – Keys are each of the energetic type features. e.g. “intra_lj” are the intra-molecular LJ energies obtained from simulation.

Values are the corresponding set of numerics, stored as lists.

Return type

dict

classmethod extract_rgyr(mdtraj_obj, **kwargs)

Extracting radius of gyration from each frame of simulation. Assumes the first residue in the system is the solute.

Parameters

mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

Returns

df – Key is prefix_rgyr, where prefix changes depending on the type of Extractor class used. Values are the corresponding set of numerics, stored as lists.

Return type

dict

classmethod extract_sasa(mdtraj_obj, **kwargs)

Extracting solvent accessible surface area from each frame of simulation. Assumes the first residue in the system is the solute.

Parameters

mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

Returns

df – Key is prefix_sasa, where prefix changes depending on the type of Extractor class used. Values are the corresponding set of numerics, stored as lists.

Return type

dict

class mdfptools.Extractor.LiquidExtractor[source]

Bases: mdfptools.Extractor.BaseExtractor

Extraction from condensed phase simulation where the system is composed of one kind of molecule only.

Parameters

string_identifier (str) – The string identifier tagged as prefix to all values extracted in this class.

Methods

extract_dipole_magnitude(mdtraj_obj, …)

Extracting dipole moment magnitude from each frame of simulation.

extract_energies(mdtraj_obj, parmed_obj[, …])

Extracting the various energetic components described in the original publication from each frame of simulation.

extract_h_bonds(mdtraj_obj, \*\*kwargs)

http://mdtraj.org/1.8.0/api/generated/mdtraj.baker_hubbard.html#mdtraj.baker_hubbar

extract_rgyr(mdtraj_obj, \*\*kwargs)

Extracting radius of gyration from each frame of simulation.

extract_sasa(mdtraj_obj, \*\*kwargs)

Extracting solvent accessible surface area from each frame of simulation.
string_identifier = 'liquid'
classmethod extract_h_bonds(mdtraj_obj, **kwargs)[source]

http://mdtraj.org/1.8.0/api/generated/mdtraj.baker_hubbard.html#mdtraj.baker_hubbar

classmethod extract_dipole_magnitude(mdtraj_obj, parmed_obj, **kwargs)[source]

Extracting dipole moment magnitude from each frame of simulation. Assumes the first residue in the system is the solute.

Parameters

  • mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

Returns

df – Key is prefix_dipole_magnitude, where prefix changes depending on the type of Extractor class used. Values are the corresponding set of numerics, stored as lists.

Return type

dict

__init__(self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

classmethod _extract_energies_helper(mdtraj_obj, parmed_obj, platform='CPU', **kwargs)

Helper function for extracting the various energetic components described in the original publication from each frame of simulation. OpenMM.CustomNonbondedForces are used. Specifically, the reaction field defintion is taken from GROMOS96 manual.

Parameters

  • mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • platform (str) – The computing architecture to do the calculation, default to CPU, CUDA, OpenCL is also possible.

Returns

  • context (Openmm.Context)

  • integrator (Openmm.Integrator)

classmethod _solute_solvent_split(topology)[source]

Distinguish solutes from solvents, used in _extract_energies_helper()

The following is assumed:

  • the first residue is the ‘solute’ , else ‘solvent’

Parameters

topology (parmed.topology) –

Returns

  • solute_atoms (set) – set of solute_atoms indices

  • solvent_atoms (set) – set of solvent_atoms indices

classmethod extract_energies(mdtraj_obj, parmed_obj, platform='CPU', **kwargs)

Extracting the various energetic components described in the original publication from each frame of simulation.

Parameters

  • mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • platform (str) – The computing architecture to do the calculation, default to CPU, CUDA, OpenCL is also possible.

Returns

df – Keys are each of the energetic type features. e.g. “intra_lj” are the intra-molecular LJ energies obtained from simulation.

Values are the corresponding set of numerics, stored as lists.

Return type

dict

classmethod extract_rgyr(mdtraj_obj, **kwargs)

Extracting radius of gyration from each frame of simulation. Assumes the first residue in the system is the solute.

Parameters

mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

Returns

df – Key is prefix_rgyr, where prefix changes depending on the type of Extractor class used. Values are the corresponding set of numerics, stored as lists.

Return type

dict

classmethod extract_sasa(mdtraj_obj, **kwargs)

Extracting solvent accessible surface area from each frame of simulation. Assumes the first residue in the system is the solute.

Parameters

mdtraj_obj (mdtraj.trajectory) – The simulated trajectory

Returns

df – Key is prefix_sasa, where prefix changes depending on the type of Extractor class used. Values are the corresponding set of numerics, stored as lists.

Return type

dict

classmethod _get_all_exception_atom_pairs(system, topology)[source]

Using the parametersied system to obtain the exception and exclusion pairs, used in _extract_energies_helper(). This is inferred purely from the parameterised system and connectivity.

Parameters

  • system (OpenMM.System) –

  • topology (parmed.topology) –

Returns

  • solute_1_4_pairs (set)

  • solvent_1_4_pairs (set)

  • solute_excluded_pairs (set)

  • solvent_excluded_pairs (set)

  • solute_self_pairs (set)

  • solvent_self_pairs (set)

mdfptools.Parameteriser module

class mdfptools.Parameteriser.BaseParameteriser[source]

Bases: object

Warning

The base class should not be used directly

Attributes
system_pmd

Methods

load_ddec_models([epsilon])

Charging molecule using machine learned charge instead of the default AM1-BCC method.

pmd_generator()

Abstract method

run()

Abstract method

save(file_name[, file_path])

Save to file the parameterised system.

unload_ddec_models(\*\*kwargs)

Unload the machine-learned charge model, which takes over 1 GB of memory.

via_openeye()

Abstract method

via_rdkit()

Abstract method
system_pmd = None
classmethod via_openeye()[source]

Abstract method

classmethod via_rdkit()[source]

Abstract method

classmethod pmd_generator()[source]

Abstract method

classmethod _rdkit_setter(smiles, **kwargs)[source]

Prepares an rdkit molecule with 3D coordinates.

Parameters

smiles (str) – SMILES string of the solute moleulce

Returns

mol

Return type

rdkit.Chem.Mol

classmethod _rdkit_parameteriser(mol, **kwargs)[source]
classmethod load_ddec_models(epsilon=4, **kwargs)[source]

Charging molecule using machine learned charge instead of the default AM1-BCC method.

Requires first installing the mlddec(https://github.com/rinikerlab/mlddec) package. Parameters are availible for elements : {H,C,N,O,Cl,Br,F}.

Parameters

epsilon (int) – Dielectric constant to be used, polarity of the resulting molecule varies, possible values are {4,78}.

classmethod unload_ddec_models(**kwargs)[source]

Unload the machine-learned charge model, which takes over 1 GB of memory.

classmethod _openeye_setter(smiles, **kwargs)[source]

Prepares an openeye molecule with 3D coordinates.

Parameters

smiles (str) – SMILES string of the solute moleulce

Returns

mol

Return type

oechem.OEMol

classmethod _openeye_parameteriser(mol, **kwargs)[source]

Creates a parameterised system from openeye molecule

Parameters

mol (oechem.OEMol) –

classmethod save(file_name, file_path='./', **kwargs)[source]

Save to file the parameterised system.

Parameters

  • file_name (str) – No file type postfix is necessary

  • file_path (str) – Default to current directory

Returns

path – The absolute path where the trajectory is written to.

Return type

str

classmethod run()

Abstract method

__init__(self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

class mdfptools.Parameteriser.LiquidParameteriser[source]

Bases: mdfptools.Parameteriser.BaseParameteriser

Parameterisation of liquid box, i.e. multiple replicates of the same molecule

Attributes
system_pmd

Methods

load_ddec_models([epsilon])

Charging molecule using machine learned charge instead of the default AM1-BCC method.

pmd_generator()

Abstract method

run(smiles, density[, …])

Parameterisation perfromed via openeye toolkit.

save(file_name[, file_path])

Save to file the parameterised system.

unload_ddec_models(\*\*kwargs)

Unload the machine-learned charge model, which takes over 1 GB of memory.

via_openeye(smiles, density[, …])

Parameterisation perfromed via openeye toolkit.

via_rdkit(smiles, density[, …])

Parameterisation perfromed via rdkit.
classmethod via_openeye(smiles, density, allow_undefined_stereo=False, num_lig=100, **kwargs)[source]

Parameterisation perfromed via openeye toolkit.

Parameters

  • smiles (str) – SMILES string of the molecule to be parametersied

  • density (simtk.unit) – Density of liquid box

  • allow_undefined_stereo (bool) – Flag passed to OpenForceField Molecule object during parameterisation. When set to False an error is returned if SMILES have no/ambiguous steroechemistry. Default to False here as a sanity check for user.

  • num_lig (int) – Number of replicates of the molecule

Returns

system_pmd – The parameterised system as parmed object

Return type

parmed.structure

classmethod via_rdkit(smiles, density, allow_undefined_stereo=False, num_lig=100, **kwargs)[source]

Parameterisation perfromed via rdkit.

Parameters

  • smiles (str) – SMILES string of the molecule to be parametersied

  • density (simtk.unit) – Density of liquid box

  • allow_undefined_stereo (bool) – Flag passed to OpenForceField Molecule object during parameterisation. When set to False an error is returned if SMILES have no/ambiguous steroechemistry. Default to False here as a sanity check for user.

  • num_lig (int) – Number of replicates of the molecule

Returns

system_pmd – The parameterised system as parmed object

Return type

parmed.structure

classmethod _via_helper(density, num_lig, **kwargs)[source]

Helper function for via_rdkit or via_openeye

Parameters

  • density (simtk.unit) – Density of liquid box

  • num_lig (int) – Number of replicates of the molecule

Returns

system_pmd – The parameterised system as parmed object

Return type

parmed.structure

classmethod run(smiles, density, allow_undefined_stereo=False, num_lig=100, **kwargs)

Parameterisation perfromed via openeye toolkit.

Parameters

  • smiles (str) – SMILES string of the molecule to be parametersied

  • density (simtk.unit) – Density of liquid box

  • allow_undefined_stereo (bool) – Flag passed to OpenForceField Molecule object during parameterisation. When set to False an error is returned if SMILES have no/ambiguous steroechemistry. Default to False here as a sanity check for user.

  • num_lig (int) – Number of replicates of the molecule

Returns

system_pmd – The parameterised system as parmed object

Return type

parmed.structure

__init__(self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

classmethod _openeye_parameteriser(mol, **kwargs)

Creates a parameterised system from openeye molecule

Parameters

mol (oechem.OEMol) –

classmethod _openeye_setter(smiles, **kwargs)

Prepares an openeye molecule with 3D coordinates.

Parameters

smiles (str) – SMILES string of the solute moleulce

Returns

mol

Return type

oechem.OEMol

classmethod _rdkit_parameteriser(mol, **kwargs)
classmethod _rdkit_setter(smiles, **kwargs)

Prepares an rdkit molecule with 3D coordinates.

Parameters

smiles (str) – SMILES string of the solute moleulce

Returns

mol

Return type

rdkit.Chem.Mol

classmethod load_ddec_models(epsilon=4, **kwargs)

Charging molecule using machine learned charge instead of the default AM1-BCC method.

Requires first installing the mlddec(https://github.com/rinikerlab/mlddec) package. Parameters are availible for elements : {H,C,N,O,Cl,Br,F}.

Parameters

epsilon (int) – Dielectric constant to be used, polarity of the resulting molecule varies, possible values are {4,78}.

classmethod pmd_generator()

Abstract method

classmethod save(file_name, file_path='./', **kwargs)

Save to file the parameterised system.

Parameters

  • file_name (str) – No file type postfix is necessary

  • file_path (str) – Default to current directory

Returns

path – The absolute path where the trajectory is written to.

Return type

str

system_pmd = None
classmethod unload_ddec_models(**kwargs)

Unload the machine-learned charge model, which takes over 1 GB of memory.

class mdfptools.Parameteriser.SolutionParameteriser[source]

Bases: mdfptools.Parameteriser.BaseParameteriser

Parameterisation of solution box, i.e. one copy of solute molecule surronded by water.

Parameters

solvent_pmd (parmed.structure) – Parameterised tip3p water as parmed object

Attributes
system_pmd

Methods

load_ddec_models([epsilon])

Charging molecule using machine learned charge instead of the default AM1-BCC method.

pmd_generator()

Abstract method

run(smiles[, allow_undefined_stereo, …])

Parameterisation perfromed via openeye.

save(file_name[, file_path])

Save to file the parameterised system.

unload_ddec_models(\*\*kwargs)

Unload the machine-learned charge model, which takes over 1 GB of memory.

via_openeye(smiles[, …])

Parameterisation perfromed via openeye.

via_rdkit(smiles[, allow_undefined_stereo, …])

Parameterisation perfromed via openeye.
classmethod via_openeye(smiles, allow_undefined_stereo=False, default_padding=Quantity(value=1.25, unit=nanometer), **kwargs)[source]

Parameterisation perfromed via openeye.

Parameters

  • smiles (str) – SMILES string of the solute molecule

  • allow_undefined_stereo (bool) – Flag passed to OpenForceField Molecule object during parameterisation. When set to False an error is returned if SMILES have no/ambiguous steroechemistry. Default to False here as a sanity check for user.

  • default_padding (simtk.unit) – Dictates amount of water surronding the solute. Default is 1.25 nanometers

Returns

system_pmd – The parameterised system as parmed object

Return type

parmed.structure

classmethod via_rdkit(smiles, allow_undefined_stereo=False, default_padding=Quantity(value=1.25, unit=nanometer), **kwargs)[source]

Parameterisation perfromed via openeye.

Parameters

  • smiles (str) – SMILES string of the solute molecule

  • allow_undefined_stereo (bool) – Flag passed to OpenForceField Molecule object during parameterisation. When set to False an error is returned if SMILES have no/ambiguous steroechemistry. Default to False here as a sanity check for user.

  • default_padding (simtk.unit) – Dictates amount of water surronding the solute. Default is 1.25 nanometers

Returns

system_pmd – The parameterised system as parmed object

Return type

parmed.structure

classmethod _via_helper(**kwargs)[source]

Helper function for via_rdkit or via_openeye

Returns

system_pmd – The parameterised system as parmed object

Return type

parmed.structure

classmethod run(smiles, allow_undefined_stereo=False, default_padding=Quantity(value=1.25, unit=nanometer), **kwargs)

Parameterisation perfromed via openeye.

Parameters

  • smiles (str) – SMILES string of the solute molecule

  • allow_undefined_stereo (bool) – Flag passed to OpenForceField Molecule object during parameterisation. When set to False an error is returned if SMILES have no/ambiguous steroechemistry. Default to False here as a sanity check for user.

  • default_padding (simtk.unit) – Dictates amount of water surronding the solute. Default is 1.25 nanometers

Returns

system_pmd – The parameterised system as parmed object

Return type

parmed.structure

__init__(self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

classmethod _openeye_parameteriser(mol, **kwargs)

Creates a parameterised system from openeye molecule

Parameters

mol (oechem.OEMol) –

classmethod _openeye_setter(smiles, **kwargs)

Prepares an openeye molecule with 3D coordinates.

Parameters

smiles (str) – SMILES string of the solute moleulce

Returns

mol

Return type

oechem.OEMol

classmethod _rdkit_parameteriser(mol, **kwargs)
classmethod _rdkit_setter(smiles, **kwargs)

Prepares an rdkit molecule with 3D coordinates.

Parameters

smiles (str) – SMILES string of the solute moleulce

Returns

mol

Return type

rdkit.Chem.Mol

classmethod load_ddec_models(epsilon=4, **kwargs)

Charging molecule using machine learned charge instead of the default AM1-BCC method.

Requires first installing the mlddec(https://github.com/rinikerlab/mlddec) package. Parameters are availible for elements : {H,C,N,O,Cl,Br,F}.

Parameters

epsilon (int) – Dielectric constant to be used, polarity of the resulting molecule varies, possible values are {4,78}.

classmethod pmd_generator()

Abstract method

classmethod save(file_name, file_path='./', **kwargs)

Save to file the parameterised system.

Parameters

  • file_name (str) – No file type postfix is necessary

  • file_path (str) – Default to current directory

Returns

path – The absolute path where the trajectory is written to.

Return type

str

system_pmd = None
classmethod unload_ddec_models(**kwargs)

Unload the machine-learned charge model, which takes over 1 GB of memory.

class mdfptools.Parameteriser.VaccumParameteriser[source]

Bases: mdfptools.Parameteriser.BaseParameteriser

Attributes
system_pmd

Methods

load_ddec_models([epsilon])

Charging molecule using machine learned charge instead of the default AM1-BCC method.

pmd_generator()

Abstract method

run(smiles[, allow_undefined_stereo])

Parameterisation perfromed via openeye toolkit.

save(file_name[, file_path])

Save to file the parameterised system.

unload_ddec_models(\*\*kwargs)

Unload the machine-learned charge model, which takes over 1 GB of memory.

via_openeye(smiles[, allow_undefined_stereo])

Parameterisation perfromed via openeye toolkit.

via_rdkit(smiles[, allow_undefined_stereo])

Parameterisation perfromed via rdkit toolkit.
classmethod via_openeye(smiles, allow_undefined_stereo=False, **kwargs)[source]

Parameterisation perfromed via openeye toolkit.

Parameters

  • smiles (str) – SMILES string of the molecule to be parametersied

  • allow_undefined_stereo (bool) – Flag passed to OpenForceField Molecule object during parameterisation. When set to False an error is returned if SMILES have no/ambiguous steroechemistry. Default to False here as a sanity check for user.

Returns

system_pmd – The parameterised system as parmed object

Return type

parmed.structure

classmethod via_rdkit(smiles, allow_undefined_stereo=False, **kwargs)[source]

Parameterisation perfromed via rdkit toolkit.

Parameters

  • smiles (str) – SMILES string of the molecule to be parametersied

  • allow_undefined_stereo (bool) – Flag passed to OpenForceField Molecule object during parameterisation. When set to False an error is returned if SMILES have no/ambiguous steroechemistry. Default to False here as a sanity check for user.

Returns

system_pmd – The parameterised system as parmed object

Return type

parmed.structure

__init__(self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

classmethod _openeye_parameteriser(mol, **kwargs)

Creates a parameterised system from openeye molecule

Parameters

mol (oechem.OEMol) –

classmethod _openeye_setter(smiles, **kwargs)

Prepares an openeye molecule with 3D coordinates.

Parameters

smiles (str) – SMILES string of the solute moleulce

Returns

mol

Return type

oechem.OEMol

classmethod _rdkit_parameteriser(mol, **kwargs)
classmethod _rdkit_setter(smiles, **kwargs)

Prepares an rdkit molecule with 3D coordinates.

Parameters

smiles (str) – SMILES string of the solute moleulce

Returns

mol

Return type

rdkit.Chem.Mol

classmethod load_ddec_models(epsilon=4, **kwargs)

Charging molecule using machine learned charge instead of the default AM1-BCC method.

Requires first installing the mlddec(https://github.com/rinikerlab/mlddec) package. Parameters are availible for elements : {H,C,N,O,Cl,Br,F}.

Parameters

epsilon (int) – Dielectric constant to be used, polarity of the resulting molecule varies, possible values are {4,78}.

classmethod pmd_generator()

Abstract method

classmethod run(smiles, allow_undefined_stereo=False, **kwargs)

Parameterisation perfromed via openeye toolkit.

Parameters

  • smiles (str) – SMILES string of the molecule to be parametersied

  • allow_undefined_stereo (bool) – Flag passed to OpenForceField Molecule object during parameterisation. When set to False an error is returned if SMILES have no/ambiguous steroechemistry. Default to False here as a sanity check for user.

Returns

system_pmd – The parameterised system as parmed object

Return type

parmed.structure

classmethod save(file_name, file_path='./', **kwargs)

Save to file the parameterised system.

Parameters

  • file_name (str) – No file type postfix is necessary

  • file_path (str) – Default to current directory

Returns

path – The absolute path where the trajectory is written to.

Return type

str

system_pmd = None
classmethod unload_ddec_models(**kwargs)

Unload the machine-learned charge model, which takes over 1 GB of memory.

mdfptools.Simulator module

class mdfptools.Simulator.BaseSimulator[source]

Bases: object

Warning

The base class should not be used directly

Parameters

  • temperature (simtk.unit) – default 298.15 K

  • pressure (simtk.unit) – default 1.013 bar

  • time_step (simtk.unit) – default 2 fs

Methods

run(parmed_obj, file_name[, file_path, …])

Runs simulation using OpenMM.

via_gromacs()

Simulation via GROMACS will be added in the future.

via_openmm(parmed_obj, file_name[, …])

Runs simulation using OpenMM.
temperature = Quantity(value=298.15, unit=kelvin)
pressure = Quantity(value=1.013, unit=bar)
time_step = Quantity(value=0.002, unit=picosecond)
equil_steps = 50000
classmethod via_openmm(parmed_obj, file_name, file_path='./', platform='CUDA', num_steps=2500000, write_out_freq=5000, **kwargs)[source]

Runs simulation using OpenMM.

Parameters

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • file_name (str) – No file type postfix is necessary

  • file_path (str) – Default to current directory

  • platform (str) – The computing architecture to do the calculation, default to CUDA, CPU, OpenCL is also possible.

  • num_steps (int) – Number of production simulation to run, default 2,500,000 steps, i.e. 5 ns.

  • write_out_freq (int) – Write out every nth frame of simulated trajectory, default to every 5000 frame write out one, i.e. 10 ps per frame.

Returns

path – The absolute path where the trajectory is written to.

Return type

str

classmethod via_gromacs()[source]

Simulation via GROMACS will be added in the future.

classmethod run(parmed_obj, file_name, file_path='./', platform='CUDA', num_steps=2500000, write_out_freq=5000, **kwargs)

Runs simulation using OpenMM.

Parameters

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • file_name (str) – No file type postfix is necessary

  • file_path (str) – Default to current directory

  • platform (str) – The computing architecture to do the calculation, default to CUDA, CPU, OpenCL is also possible.

  • num_steps (int) – Number of production simulation to run, default 2,500,000 steps, i.e. 5 ns.

  • write_out_freq (int) – Write out every nth frame of simulated trajectory, default to every 5000 frame write out one, i.e. 10 ps per frame.

Returns

path – The absolute path where the trajectory is written to.

Return type

str

__init__(self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

class mdfptools.Simulator.SolutionSimulator[source]

Bases: mdfptools.Simulator.BaseSimulator

Perform solution simulation, namely one copy of solute in water box. Currently identical to BaseSimulator

Parameters

equil_steps (int) – number of steps during equilibraion, default 50,000 steps, i.e. 100 ps

Methods

run(parmed_obj, file_name[, file_path, …])

Runs simulation using OpenMM.

via_gromacs()

Simulation via GROMACS will be added in the future.

via_openmm(parmed_obj, file_name[, …])

Runs simulation using OpenMM.
equil_steps = 50000
__init__(self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

pressure = Quantity(value=1.013, unit=bar)
classmethod run(parmed_obj, file_name, file_path='./', platform='CUDA', num_steps=2500000, write_out_freq=5000, **kwargs)

Runs simulation using OpenMM.

Parameters

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • file_name (str) – No file type postfix is necessary

  • file_path (str) – Default to current directory

  • platform (str) – The computing architecture to do the calculation, default to CUDA, CPU, OpenCL is also possible.

  • num_steps (int) – Number of production simulation to run, default 2,500,000 steps, i.e. 5 ns.

  • write_out_freq (int) – Write out every nth frame of simulated trajectory, default to every 5000 frame write out one, i.e. 10 ps per frame.

Returns

path – The absolute path where the trajectory is written to.

Return type

str

temperature = Quantity(value=298.15, unit=kelvin)
time_step = Quantity(value=0.002, unit=picosecond)
classmethod via_gromacs()

Simulation via GROMACS will be added in the future.

classmethod via_openmm(parmed_obj, file_name, file_path='./', platform='CUDA', num_steps=2500000, write_out_freq=5000, **kwargs)

Runs simulation using OpenMM.

Parameters

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • file_name (str) – No file type postfix is necessary

  • file_path (str) – Default to current directory

  • platform (str) – The computing architecture to do the calculation, default to CUDA, CPU, OpenCL is also possible.

  • num_steps (int) – Number of production simulation to run, default 2,500,000 steps, i.e. 5 ns.

  • write_out_freq (int) – Write out every nth frame of simulated trajectory, default to every 5000 frame write out one, i.e. 10 ps per frame.

Returns

path – The absolute path where the trajectory is written to.

Return type

str

class mdfptools.Simulator.LiquidSimulator[source]

Bases: mdfptools.Simulator.BaseSimulator

Perform liquid simulation, namely multiple copy of the same molecule.

Parameters

equil_steps (int) – number of steps during equilibraion, default 500,000 steps, i.e. 1 ns

Methods

run(parmed_obj, file_name[, file_path, …])

Runs simulation using OpenMM.

via_gromacs()

Simulation via GROMACS will be added in the future.

via_openmm(parmed_obj, file_name[, …])

Runs simulation using OpenMM.
__init__(self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

equil_steps = 500000
pressure = Quantity(value=1.013, unit=bar)
classmethod run(parmed_obj, file_name, file_path='./', platform='CUDA', num_steps=2500000, write_out_freq=5000, **kwargs)

Runs simulation using OpenMM.

Parameters

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • file_name (str) – No file type postfix is necessary

  • file_path (str) – Default to current directory

  • platform (str) – The computing architecture to do the calculation, default to CUDA, CPU, OpenCL is also possible.

  • num_steps (int) – Number of production simulation to run, default 2,500,000 steps, i.e. 5 ns.

  • write_out_freq (int) – Write out every nth frame of simulated trajectory, default to every 5000 frame write out one, i.e. 10 ps per frame.

Returns

path – The absolute path where the trajectory is written to.

Return type

str

temperature = Quantity(value=298.15, unit=kelvin)
time_step = Quantity(value=0.002, unit=picosecond)
classmethod via_gromacs()

Simulation via GROMACS will be added in the future.

classmethod via_openmm(parmed_obj, file_name, file_path='./', platform='CUDA', num_steps=2500000, write_out_freq=5000, **kwargs)

Runs simulation using OpenMM.

Parameters

  • parmed_obj (parmed.structure) – Parmed object of the fully parameterised simulated system.

  • file_name (str) – No file type postfix is necessary

  • file_path (str) – Default to current directory

  • platform (str) – The computing architecture to do the calculation, default to CUDA, CPU, OpenCL is also possible.

  • num_steps (int) – Number of production simulation to run, default 2,500,000 steps, i.e. 5 ns.

  • write_out_freq (int) – Write out every nth frame of simulated trajectory, default to every 5000 frame write out one, i.e. 10 ps per frame.

Returns

path – The absolute path where the trajectory is written to.

Return type

str

mdfptools.utils module

mdfptools.utils.get_data_filename(relative_path)[source]

Get the full path to one of the reference files in testsystems. In the source distribution, these files are in mdfptools/data/, but on installation, they’re moved to somewhere in the user’s python site-packages directory.

Parameters

name (str) – Name of the file to load (with respect to the repex folder).

Returns

fn – filename

Return type

str

mdfptools.utils.canonical_smiles_from_smiles(smiles, sanitize=True)[source]

Apply canonicalisation with rdkit

Parameters

  • smiles (str) –

  • sanitize (bool) – Wether to apply rdkit sanitisation, default yes.

Returns

canonical_smiles – Returns None if canonicalisation fails

Return type

str

mdfptools.utils.hashing(smiles)[source]

Converts a string to hexdecimal representation (length 32). Specifically, it is used in mdfptools to convert canonical smiles to hex so it can be used as filename when store to disk.

Parameters

smiles (str) –

Returns

hex_str – Hexdecimal representation

Return type

str

mdfptools.utils.screen_organic(smiles)[source]

Heuristic to determine if a input SMILES string is considered as only organic matter.

Parameters

smiles (str) –

Returns

is_organic

Return type

bool

Module contents

mdfptools python implementation of molecular dynamics fingerprints as delineated in https://pubs.acs.org/doi/10.1021/acs.jcim.6b00778