oddt.scoring.functions package¶

Submodules¶

oddt.scoring.functions.NNScore module¶

class oddt.scoring.functions.NNScore.nnscore(protein=None, n_jobs=-1)[source]¶

Bases: oddt.scoring.scorer

Methods

`fit`(ligands, target, args, *kwargs)	Trains model on supplied ligands and target values
`gen_training_data`(pdbbind_dir[, …])
`load`([filename, pdbbind_version])
`predict`(ligands, args, *kwargs)	Predicts values (eg.
`predict_ligand`(ligand)	Local method to score one ligand and update it’s scores.
`predict_ligands`(ligands)	Method to score ligands lazily
`save`(filename)	Saves scoring function to a pickle file.
`score`(ligands, target, args, *kwargs)	Methods estimates the quality of prediction using model’s default
`set_protein`(protein)	Proxy method to update protein in all relevant places.
`train`([home_dir, sf_pickle, pdbbind_version])

fit(ligands, target, *args, **kwargs)¶

Trains model on supplied ligands and target values

Parameters:

ligands: array-like of ligands

Molecules to featurize and feed into the model

target: array-like of shape = [n_samples] or [n_samples, n_outputs]

Ground truth (correct) target values.

gen_training_data(pdbbind_dir, pdbbind_versions=(2007, 2012, 2013, 2014, 2015, 2016), home_dir=None)[source]¶

classmethod load(filename=None, pdbbind_version=2016)[source]¶

predict(ligands, *args, **kwargs)¶

Predicts values (eg. affinity) for supplied ligands.

Parameters:

ligands: array-like of ligands

Molecules to featurize and feed into the model

Returns:

predicted: np.array or array of np.arrays of shape = [n_ligands]

Predicted scores for ligands

predict_ligand(ligand)¶

Local method to score one ligand and update it’s scores.

Parameters:

ligand: oddt.toolkit.Molecule object

Ligand to be scored

Returns:

ligand: oddt.toolkit.Molecule object

Scored ligand with updated scores

predict_ligands(ligands)¶

Method to score ligands lazily

Parameters:

ligands: iterable of oddt.toolkit.Molecule objects

Ligands to be scored

Returns:

ligand: iterator of oddt.toolkit.Molecule objects

Scored ligands with updated scores

save(filename)¶

Saves scoring function to a pickle file.

Parameters:

filename: string

Pickle filename

score(ligands, target, *args, **kwargs)¶

Methods estimates the quality of prediction using model’s default score (accuracy for classification or R^2 for regression)

Parameters:

ligands: array-like of ligands

Molecules to featurize and feed into the model

target: array-like of shape = [n_samples] or [n_samples, n_outputs]

Ground truth (correct) target values.

Returns:

s: float

Quality score (accuracy or R^2) for prediction

set_protein(protein)¶

Proxy method to update protein in all relevant places.

Parameters:

protein: oddt.toolkit.Molecule object

New default protein

train(home_dir=None, sf_pickle=None, pdbbind_version=2016)[source]¶

oddt.scoring.functions.RFScore module¶

class oddt.scoring.functions.RFScore.rfscore(protein=None, n_jobs=-1, version=1, spr=0, **kwargs)[source]¶

Bases: oddt.scoring.scorer

Methods

`fit`(ligands, target, args, *kwargs)	Trains model on supplied ligands and target values
`gen_training_data`(pdbbind_dir[, …])
`load`([filename, version, pdbbind_version])
`predict`(ligands, args, *kwargs)	Predicts values (eg.
`predict_ligand`(ligand)	Local method to score one ligand and update it’s scores.
`predict_ligands`(ligands)	Method to score ligands lazily
`save`(filename)	Saves scoring function to a pickle file.
`score`(ligands, target, args, *kwargs)	Methods estimates the quality of prediction using model’s default
`set_protein`(protein)	Proxy method to update protein in all relevant places.
`train`([home_dir, sf_pickle, pdbbind_version])

fit(ligands, target, *args, **kwargs)¶

Trains model on supplied ligands and target values

Parameters:

ligands: array-like of ligands

Molecules to featurize and feed into the model

target: array-like of shape = [n_samples] or [n_samples, n_outputs]

Ground truth (correct) target values.

gen_training_data(pdbbind_dir, pdbbind_versions=(2007, 2012, 2013, 2014, 2015, 2016), home_dir=None)[source]¶

classmethod load(filename=None, version=1, pdbbind_version=2016)[source]¶

predict(ligands, *args, **kwargs)¶

Predicts values (eg. affinity) for supplied ligands.

Parameters:

ligands: array-like of ligands

Molecules to featurize and feed into the model

Returns:

predicted: np.array or array of np.arrays of shape = [n_ligands]

Predicted scores for ligands

predict_ligand(ligand)¶

Local method to score one ligand and update it’s scores.

Parameters:

ligand: oddt.toolkit.Molecule object

Ligand to be scored

Returns:

ligand: oddt.toolkit.Molecule object

Scored ligand with updated scores

predict_ligands(ligands)¶

Method to score ligands lazily

Parameters:

ligands: iterable of oddt.toolkit.Molecule objects

Ligands to be scored

Returns:

ligand: iterator of oddt.toolkit.Molecule objects

Scored ligands with updated scores

save(filename)¶

Saves scoring function to a pickle file.

Parameters:

filename: string

Pickle filename

score(ligands, target, *args, **kwargs)¶

Methods estimates the quality of prediction using model’s default score (accuracy for classification or R^2 for regression)

Parameters:

ligands: array-like of ligands

Molecules to featurize and feed into the model

target: array-like of shape = [n_samples] or [n_samples, n_outputs]

Ground truth (correct) target values.

Returns:

s: float

Quality score (accuracy or R^2) for prediction

set_protein(protein)¶

Proxy method to update protein in all relevant places.

Parameters:

protein: oddt.toolkit.Molecule object

New default protein

train(home_dir=None, sf_pickle=None, pdbbind_version=2016)[source]¶

Module contents¶

class oddt.scoring.functions.rfscore(protein=None, n_jobs=-1, version=1, spr=0, **kwargs)[source]¶

Bases: oddt.scoring.scorer

Methods

`fit`(ligands, target, args, *kwargs)	Trains model on supplied ligands and target values
`gen_training_data`(pdbbind_dir[, …])
`load`([filename, version, pdbbind_version])
`predict`(ligands, args, *kwargs)	Predicts values (eg.
`predict_ligand`(ligand)	Local method to score one ligand and update it’s scores.
`predict_ligands`(ligands)	Method to score ligands lazily
`save`(filename)	Saves scoring function to a pickle file.
`score`(ligands, target, args, *kwargs)	Methods estimates the quality of prediction using model’s default
`set_protein`(protein)	Proxy method to update protein in all relevant places.
`train`([home_dir, sf_pickle, pdbbind_version])

fit(ligands, target, *args, **kwargs)¶

Trains model on supplied ligands and target values

Parameters:

ligands: array-like of ligands

Molecules to featurize and feed into the model

target: array-like of shape = [n_samples] or [n_samples, n_outputs]

Ground truth (correct) target values.

gen_training_data(pdbbind_dir, pdbbind_versions=(2007, 2012, 2013, 2014, 2015, 2016), home_dir=None)[source]¶

classmethod load(filename=None, version=1, pdbbind_version=2016)[source]¶

predict(ligands, *args, **kwargs)¶

Predicts values (eg. affinity) for supplied ligands.

Parameters:

ligands: array-like of ligands

Molecules to featurize and feed into the model

Returns:

predicted: np.array or array of np.arrays of shape = [n_ligands]

Predicted scores for ligands

predict_ligand(ligand)¶

Local method to score one ligand and update it’s scores.

Parameters:

ligand: oddt.toolkit.Molecule object

Ligand to be scored

Returns:

ligand: oddt.toolkit.Molecule object

Scored ligand with updated scores

predict_ligands(ligands)¶

Method to score ligands lazily

Parameters:

ligands: iterable of oddt.toolkit.Molecule objects

Ligands to be scored

Returns:

ligand: iterator of oddt.toolkit.Molecule objects

Scored ligands with updated scores

save(filename)¶

Saves scoring function to a pickle file.

Parameters:

filename: string

Pickle filename

score(ligands, target, *args, **kwargs)¶

Methods estimates the quality of prediction using model’s default score (accuracy for classification or R^2 for regression)

Parameters:

ligands: array-like of ligands

Molecules to featurize and feed into the model

target: array-like of shape = [n_samples] or [n_samples, n_outputs]

Ground truth (correct) target values.

Returns:

s: float

Quality score (accuracy or R^2) for prediction

set_protein(protein)¶

Proxy method to update protein in all relevant places.

Parameters:

protein: oddt.toolkit.Molecule object

New default protein

train(home_dir=None, sf_pickle=None, pdbbind_version=2016)[source]¶

class oddt.scoring.functions.nnscore(protein=None, n_jobs=-1)[source]¶

Bases: oddt.scoring.scorer

Methods

`fit`(ligands, target, args, *kwargs)	Trains model on supplied ligands and target values
`gen_training_data`(pdbbind_dir[, …])
`load`([filename, pdbbind_version])
`predict`(ligands, args, *kwargs)	Predicts values (eg.
`predict_ligand`(ligand)	Local method to score one ligand and update it’s scores.
`predict_ligands`(ligands)	Method to score ligands lazily
`save`(filename)	Saves scoring function to a pickle file.
`score`(ligands, target, args, *kwargs)	Methods estimates the quality of prediction using model’s default
`set_protein`(protein)	Proxy method to update protein in all relevant places.
`train`([home_dir, sf_pickle, pdbbind_version])

fit(ligands, target, *args, **kwargs)¶

Trains model on supplied ligands and target values

Parameters:

ligands: array-like of ligands

Molecules to featurize and feed into the model

target: array-like of shape = [n_samples] or [n_samples, n_outputs]

Ground truth (correct) target values.

gen_training_data(pdbbind_dir, pdbbind_versions=(2007, 2012, 2013, 2014, 2015, 2016), home_dir=None)[source]¶

classmethod load(filename=None, pdbbind_version=2016)[source]¶

predict(ligands, *args, **kwargs)¶

Predicts values (eg. affinity) for supplied ligands.

Parameters:

ligands: array-like of ligands

Molecules to featurize and feed into the model

Returns:

predicted: np.array or array of np.arrays of shape = [n_ligands]

Predicted scores for ligands

predict_ligand(ligand)¶

Local method to score one ligand and update it’s scores.

Parameters:

ligand: oddt.toolkit.Molecule object

Ligand to be scored

Returns:

ligand: oddt.toolkit.Molecule object

Scored ligand with updated scores

predict_ligands(ligands)¶

Method to score ligands lazily

Parameters:

ligands: iterable of oddt.toolkit.Molecule objects

Ligands to be scored

Returns:

ligand: iterator of oddt.toolkit.Molecule objects

Scored ligands with updated scores

save(filename)¶

Saves scoring function to a pickle file.

Parameters:

filename: string

Pickle filename

score(ligands, target, *args, **kwargs)¶

Methods estimates the quality of prediction using model’s default score (accuracy for classification or R^2 for regression)

Parameters:

ligands: array-like of ligands

Molecules to featurize and feed into the model

target: array-like of shape = [n_samples] or [n_samples, n_outputs]

Ground truth (correct) target values.

Returns:

s: float

Quality score (accuracy or R^2) for prediction

set_protein(protein)¶

Proxy method to update protein in all relevant places.

Parameters:

protein: oddt.toolkit.Molecule object

New default protein

train(home_dir=None, sf_pickle=None, pdbbind_version=2016)[source]¶