scikit-chem: simple cheminformatics for Python¶

Submodules¶

skchem.core.atom module¶

## skchem.core.atom

Defining atoms in scikit-chem.

class skchem.core.atom.Atom[source]¶

Bases: rdkit.Chem.rdchem.Atom, skchem.core.base.ChemicalObject

Object representing an Atom in scikit-chem.

atomic_mass¶

float – the atomic mass of the atom in u.

atomic_number¶

int – the atomic number of the atom.

bonds¶

tuple<skchem.Bonds> – the bonds to this Atom.

cahn_ingold_prelog¶

The Cahn Ingold Prelog chirality indicator.

chiral_tag¶

int – the chiral tag.

covalent_radius¶

float – the covalent radius in angstroms.

degree¶

int – the degree of the atom.

depleted_degree¶

int – the degree of the atom in the h depleted molecular graph.

electron_affinity¶

float – the first electron affinity in eV.

explicit_valence¶

int – the explicit valence.

formal_charge¶

int – the formal charge.

full_degree¶

int – the full degree of the atom in the h full molecular graph.

hexcode¶

The hexcode to use as a color for the atom.

hybridization_state¶

str – the hybridization state.

implicit_valence¶

int – the implicit valence.

index¶

int – the index of the atom.

intrinsic_state¶

float – the intrinsic state of the atom.

ionisation_energy¶

float – the first ionisation energy in eV.

is_aromatic¶

bool – whether the atom is aromatic.

is_in_ring¶

bool – whether the atom is in a ring.

is_terminal¶

bool – whether the atom is terminal.

kier_hall_alpha_contrib¶

float – the covalent radius in angstroms.

kier_hall_electronegativity¶

float – the hall-keir electronegativity.

mcgowan_parameter¶

float – the mcgowan volume parameter

n_explicit_hs¶

int – the number of explicit hydrogens.

n_hs¶

int – the instanced, implicit and explicit number of hydrogens

n_implicit_hs¶

int – the number of implicit hydrogens.

n_instanced_hs¶

int – The number of instanced hydrogens.

n_lone_pairs¶

int – the number of lone pairs.

n_pi_electrons¶

int – the number of pi electrons.

n_total_hs¶

int – the total number of hydrogens (according to rdkit).

n_val_electrons¶

int – the number of valence electrons.

neighbours()[source]¶

tuple<Atom>: the neighbours of the atom.

owner¶

skchem.Mol – the owning molecule.

Warning

This will seg fault if the atom is created manually.

pauling_electronegativity¶

float – the pauling electronegativity on Pauling scale.

polarisability¶

float – the atomic polarisability in 10^{-20} m^3.

principal_quantum_number¶

int – the principle quantum number.

props¶

PropertyView – rdkit properties of the atom.

sanderson_electronegativity¶

float – the sanderson electronegativity on Pauling scale.

symbol¶

str – the element symbol of the atom.

valence¶

int – the valence.

valence_degree¶

int – the valence degree.

$$ delta_i^v = Z_i^v - h_i $$

Where $ Z_i^v $ is the number of valence electrons and $ h_i $ is the number of hydrogens.

van_der_waals_radius¶

float – the Van der Waals radius in angstroms.

van_der_waals_volume¶

float –

the van der waals volume in angstroms^3.

$

rac{4}{3} pi r_v^3 $

class skchem.core.atom.AtomView(owner)[source]¶

Bases: skchem.core.base.ChemicalObjectView

adjacency_matrix(bond_orders=False, force=True)[source]¶

The vertex adjacency matrix.

Parameters:	bond_orders (bool) – Whether to use bond orders. force (bool) – Whether to recalculate or used rdkit cached value.
Returns:	np.array[int]

atomic_mass¶

np.array<float> – the atomic mass of the atoms in view

atomic_number¶

np.array<int> – the atomic number of the atoms in view

cahn_ingold_prelog¶

np.array<str> – the CIP string representation of atoms in view.

chiral_tag¶

np.array<str> – the chiral tag of the atoms in view.

covalent_radius¶

np.array<float> – the covalent radius of the atoms in the view.

degree¶

np.array<int> – the degree of the atoms in view, according to rdkit.

depleted_degree¶

np.array<int> – the degree of the atoms in the view in the h-depleted molecular graph.

distance_matrix(bond_orders=False, force=True)[source]¶

The vertex distance matrix.

Parameters:	bond_orders (bool) – Whether to use bond orders. force (bool) – Whether to recalculate or used rdkit cached value.
Returns:	np.array[int]

electron_affinity¶

np.array<float> – the electron affinity of the atoms in the view.

explicit_valence¶

np.array<int> – the explicit valence of the atoms in view..

formal_charge¶

np.array<int> – the formal charge on the atoms in view

full_degree¶

np.array<int> – the degree of the atoms in the view in the h-filled molecular graph.

hexcode¶

The hexcode to use as a color for the atoms in the view.

hybridization_state¶

np.array<str> – the hybridization state of the atoms in view.

One of ‘SP’, ‘SP2’, ‘SP3’, ‘SP3D’, ‘SP3D2’, ‘UNSPECIFIED’, ‘OTHER’

implicit_valence¶

np.array<int> – the explicit valence of the atoms in view.

index¶

pd.Index – an index for the atoms in the view.

intrinsic_state¶

np.ndarray<float> – the intrinsic state of the atoms in the view.

ionisation_energy¶

np.array<float> – the first ionisation energy of the atoms in the view.

is_aromatic¶

np.array<bool> – whether the atoms in the view are aromatic.

is_in_ring¶

np.array<bool> – whether the atoms in the view are in a ring.

is_terminal¶

np.array<bool> – whether the atoms in the view are terminal.

kier_hall_alpha_contrib¶

np.array<float> – the contribution to the kier hall alpha for each atom in the view.

kier_hall_electronegativity¶

np.array<float> – the hall kier electronegativity of the atoms in the view.

mcgowan_parameter¶

np.array<float> – the mcgowan parameter of the atoms in the iew.

n_explicit_hs¶

np.array<int> – the number of explicit hydrogens bonded to atoms in view, according to rdkit.

n_hs¶

np.array<int> – the number of hydrogens bonded to atoms in view.

n_implicit_hs¶

np.array<int> – the number of implicit hydrogens bonded to atoms in view, according to rdkit.

n_instanced_hs¶

np.array<int> – the number of instanced hydrogens bonded to atoms in view.

In this case, instanced means the number hs explicitly initialized as atoms.

n_lone_pairs¶

np.array<int> – the number of lone pairs on atoms in view.

n_pi_electrons¶

np.array<int> – the number of pi electrons on atoms in view.

n_total_hs¶

np.array<int> – the number of total hydrogens bonded to atoms in view, according to rdkit.

n_val_electrons¶

np.array<int> – the number of valence electrons bonded to atoms in view.

pauling_electronegativity¶

np.array<float> – the pauling electronegativity of the atoms in the view.

polarisability¶

np.array<float> – the atomic polarisability of the atoms in the view.

principal_quantum_number¶

np.array<float> – the principal quantum number of the atoms in the view.

sanderson_electronegativity¶

np.array<float> – the sanderson electronegativity of the atoms in the view.

symbol¶

np.array<str> – the symbols of the atoms in view

valence¶

np.array<int> – the valence of the atoms in view.

valence_degree¶

np.array<int> – the valence degree of the atoms in the view.

van_der_waals_radius¶

np.array<float> – the Van der Waals radius of the atoms in the view.

van_der_waals_volume¶

np.array<float> – the Van der Waals volume of the atoms in the view.

skchem.core.base module¶

## skchem.core.base

Define base classes for scikit chem objects

class skchem.core.base.ChemicalObject[source]¶

Bases: object

A mixin for each chemical object in scikit-chem.

classmethod from_super(obj)[source]¶

Converts the class of an object to this class.

class skchem.core.base.ChemicalObjectIterator(view)[source]¶

Bases: object

Iterator for chemical object views.

next()¶

class skchem.core.base.ChemicalObjectView(owner)[source]¶

Bases: object

Abstract iterable view of chemical objects.

Concrete classes inheriting from it should implement __getitem__ and __len__.

props¶

Return a property view of the objects in the view.

to_list()[source]¶

Return a list of objects in the view.

class skchem.core.base.MolPropertyView(obj_view)[source]¶

Bases: skchem.core.base.View

Mol property wrapper.

This provides properties for the atom and bond views.

get(key, default=None)[source]¶

keys()[source]¶

The available property keys on the object.

to_dict()[source]¶

Return a dict of the properties of the view’s objects.

to_frame()[source]¶

Return a DataFrame of the properties of the view’s objects.

class skchem.core.base.PropertyView(owner)[source]¶

Bases: skchem.core.base.View

Property object wrapper.

This provides properties for rdkit objects.

keys()[source]¶

The available property keys on the object.

class skchem.core.base.View[source]¶

Bases: object

View wrapper interface. Conforms to the dictionary interface.

Objects inheriting from this should implement the keys, getitem, setitem and delitem methods.

clear()[source]¶

Remove all properties from the object.

get(index, default=None)[source]¶

items()[source]¶

Return an iterable of key, value pairs.

keys()[source]¶

pop(index, default=None)[source]¶

remove(key)[source]¶

Remove a property from the object.

to_dict()[source]¶

Return a dict of the properties on the object.

to_series()[source]¶

Return a pd.Series of the properties on the object.

skchem.core.bond module¶

## skchem.core.bond

Defining chemical bonds in scikit-chem.

class skchem.core.bond.Atom[source]¶

Bases: rdkit.Chem.rdchem.Atom, skchem.core.base.ChemicalObject

Object representing an Atom in scikit-chem.

atomic_mass¶

float – the atomic mass of the atom in u.

atomic_number¶

int – the atomic number of the atom.

bonds¶

tuple<skchem.Bonds> – the bonds to this Atom.

cahn_ingold_prelog¶

The Cahn Ingold Prelog chirality indicator.

chiral_tag¶

int – the chiral tag.

covalent_radius¶

float – the covalent radius in angstroms.

degree¶

int – the degree of the atom.

depleted_degree¶

int – the degree of the atom in the h depleted molecular graph.

electron_affinity¶

float – the first electron affinity in eV.

explicit_valence¶

int – the explicit valence.

formal_charge¶

int – the formal charge.

full_degree¶

int – the full degree of the atom in the h full molecular graph.

hexcode¶

The hexcode to use as a color for the atom.

hybridization_state¶

str – the hybridization state.

implicit_valence¶

int – the implicit valence.

index¶

int – the index of the atom.

intrinsic_state¶

float – the intrinsic state of the atom.

ionisation_energy¶

float – the first ionisation energy in eV.

is_aromatic¶

bool – whether the atom is aromatic.

is_in_ring¶

bool – whether the atom is in a ring.

is_terminal¶

bool – whether the atom is terminal.

kier_hall_alpha_contrib¶

float – the covalent radius in angstroms.

kier_hall_electronegativity¶

float – the hall-keir electronegativity.

mcgowan_parameter¶

float – the mcgowan volume parameter

n_explicit_hs¶

int – the number of explicit hydrogens.

n_hs¶

int – the instanced, implicit and explicit number of hydrogens

n_implicit_hs¶

int – the number of implicit hydrogens.

n_instanced_hs¶

int – The number of instanced hydrogens.

n_lone_pairs¶

int – the number of lone pairs.

n_pi_electrons¶

int – the number of pi electrons.

n_total_hs¶

int – the total number of hydrogens (according to rdkit).

n_val_electrons¶

int – the number of valence electrons.

neighbours()[source]¶

tuple<Atom>: the neighbours of the atom.

owner¶

skchem.Mol – the owning molecule.

Warning

This will seg fault if the atom is created manually.

pauling_electronegativity¶

float – the pauling electronegativity on Pauling scale.

polarisability¶

float – the atomic polarisability in 10^{-20} m^3.

principal_quantum_number¶

int – the principle quantum number.

props¶

PropertyView – rdkit properties of the atom.

sanderson_electronegativity¶

float – the sanderson electronegativity on Pauling scale.

symbol¶

str – the element symbol of the atom.

valence¶

int – the valence.

valence_degree¶

int – the valence degree.

$$ delta_i^v = Z_i^v - h_i $$

Where $ Z_i^v $ is the number of valence electrons and $ h_i $ is the number of hydrogens.

van_der_waals_radius¶

float – the Van der Waals radius in angstroms.

van_der_waals_volume¶

float –

the van der waals volume in angstroms^3.

$

rac{4}{3} pi r_v^3 $

skchem.core.conformer module¶

## skchem.core.conformer

Defining conformers in scikit-chem.

class skchem.core.conformer.Conformer[source]¶

Bases: rdkit.Chem.rdchem.Conformer, skchem.core.base.ChemicalObject

Class representing a Conformer in scikit-chem.

align_with_principal_axes()[source]¶

Align the reference frame with the principal axes of inertia.

canonicalize()[source]¶

Center the reference frame at the centre of mass and

centre_of_mass¶

np.array – the centre of mass of the comformer.

centre_representation(centre_of_mass=True)[source]¶

Centre representation to the center of mass.

Parameters:	centre_of_mass (bool) – Whether to use the masses of atoms to calculate the centre of mass, or just use the mean position coordinate.
Returns:	Conformer

geometric_centre¶

np.array – the geometric centre of the conformer.

id¶

The ID of the conformer.

is_3d¶

bool – whether the conformer is three dimensional.

owner¶

skchem.Mol – the owning molecule.

positions¶

np.ndarray – the atom positions in the conformer.

Note

This is a copy of the data, not the data itself. You cannot allocate to a slice of this.

class skchem.core.conformer.ConformerIterator(view)[source]¶

Bases: object

Iterator for chemical object views.

next()¶

class skchem.core.conformer.ConformerView(owner)[source]¶

Bases: skchem.core.base.ChemicalObjectView

append(value)[source]¶

append_2d(**kwargs)[source]¶

Append a 2D conformer.

append_3d(n_conformers=1, **kwargs)[source]¶

Append (a) 3D conformer(s), roughly embedded but not optimized.

Parameters:	n_conformers (int) – The number of conformers to append. kwargs are passed to EmbedMultipleConfs. (Further) –

id¶

is_3d¶

positions¶

skchem.core.mol module¶

## skchem.core.mol

Defining molecules in scikit-chem.

class skchem.core.mol.Mol(*args, **kwargs)[source]¶

Bases: rdkit.Chem.rdchem.Mol, skchem.core.base.ChemicalObject

Class representing a Molecule in scikit-chem.

Mol objects inherit directly from rdkit Mol objects. Therefore, they contain atom and bond information, and may also include properties and atom bookmarks.

Example

Constructors are implemented as class methods with the from_ prefix.

>>> import skchem
>>> m = skchem.Mol.from_smiles('CC(=O)Cl'); m 
<Mol name="None" formula="C2H3ClO" at ...>

This is an rdkit Mol:

>>> from rdkit.Chem import Mol as RDKMol
>>> isinstance(m, RDKMol)
True

A name can be given at initialization: >>> m = skchem.Mol.from_smiles(‘CC(=O)Cl’, name=’acetyl chloride’); m # doctest: +ELLIPSIS <Mol name=”acetyl chloride” formula=”C2H3ClO” at ...>

>>> m.name
'acetyl chloride'

Serializers are implemented as instance methods with the to_ prefix.

>>> m.to_smiles()
'CC(=O)Cl'

>>> m.to_inchi()
'InChI=1S/C2H3ClO/c1-2(3)4/h1H3'

>>> m.to_inchi_key()
'WETWJCDKMRHUPV-UHFFFAOYSA-N'

RDKit properties are accessible through the props property:

>>> m.SetProp('example_key', 'example_value') # set prop with rdkit directly
>>> m.props['example_key']
'example_value'

>>> m.SetIntProp('float_key', 42) # set int prop with rdkit directly
>>> m.props['float_key']
42

They can be set too:

>>> m.props['example_set'] = 'set_value'
>>> m.GetProp('example_set') # getting with rdkit directly
'set_value'

We can export the properties into a dict or a pandas series:

>>> m.props.to_series()
example_key    example_value
example_set        set_value
float_key                 42
dtype: object

Atoms and bonds are provided in views:

>>> m.atoms 
<AtomView values="['C', 'C', 'O', 'Cl']" at ...>

>>> m.bonds 
<BondView values="['C-C', 'C=O', 'C-Cl']" at ...>

These are iterable: >>> [a.symbol for a in m.atoms] [‘C’, ‘C’, ‘O’, ‘Cl’]

The view provides shorthands for some attributes to get these:

>>> m.atoms.symbol  
array(['C', 'C', 'O', 'Cl'], dtype=...)

Atom and bond props can also be set:

>>> m.atoms[0].props['atom_key'] = 'atom_value'
>>> m.atoms[0].props['atom_key']
'atom_value'

The properties for atoms on the whole molecule can be accessed like so:

>>> m.atoms.props 
<MolPropertyView values="{'atom_key': ['atom_value', None, None, None]}" at ...>

The properties can be exported as a pandas dataframe >>> m.atoms.props.to_frame()

atom_key

atom_idx 0 atom_value 1 None 2 None 3 None

add_hs(inplace=False, add_coords=True, explicit_only=False, only_on_atoms=False)[source]¶

Add hydrogens to self.

Parameters:	inplace (bool) – Whether to add Hs to Mol, or return a new Mol. add_coords (bool) – Whether to set 3D coordinate for added Hs. explicit_only (bool) – Whether to add only explicit Hs, or also implicit ones. only_on_atoms (iterable<bool>) – An iterable specifying the atoms to add Hs.
Returns:	Mol with Hs added.
Return type:	skchem.Mol

atoms¶

List[skchem.Atom] – An iterable over the atoms of the molecule.

bonds¶

List[skchem.Bond] – An iterable over the bonds of the molecule.

conformers¶

List[Conformer] – conformers of the molecule.

copy()[source]¶

Return a copy of the molecule.

classmethod from_binary(binary)[source]¶

Decode a molecule from a binary serialization.

Parameters:	binary – The bytes string to decode.
Returns:	The molecule encoded in the binary.
Return type:	skchem.Mol

classmethod from_inchi(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_mol2block(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_mol2file(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_molblock(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_molfile(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_pdbblock(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_pdbfile(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_smarts(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_smiles(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_tplblock(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_tplfile(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

mass¶

float – the mass of the molecule.

name¶

str – The name of the molecule.

Raises:	KeyError

props¶

PropertyView – A dictionary of the properties of the molecule.

remove_hs(inplace=False, sanitize=True, update_explicit=False, implicit_only=False)[source]¶

Remove hydrogens from self.

Parameters:	inplace (bool) – Whether to add Hs to Mol, or return a new Mol. sanitize (bool) – Whether to sanitize after Hs are removed. update_explicit (bool) – Whether to update explicit count after the removal. implicit_only (bool) – Whether to remove explict and implicit Hs, or Hs only.
Returns:	Mol with Hs removed.
Return type:	skchem.Mol

to_binary()[source]¶

Serialize the molecule to binary encoding.

Returns:	the molecule in bytes.
Return type:	bytes

Notes

Due to limitations in RDKit, not all data is serialized. Notably, properties are not, so e.g. compound names are not saved.

to_dict(kind='chemdoodle', conformer_id=-1)[source]¶

A dictionary representation of the molecule.

Parameters:	kind (str) – The type of representation to use. Only chemdoodle is currently supported.
Returns:	dictionary representation of the molecule.
Return type:	dict

to_formula()[source]¶

str: the chemical formula of the molecule.

Raises:	RuntimeError

to_inchi(*args, **kwargs)¶

The serializer to be bound.

to_inchi_key()[source]¶

The InChI key of the molecule.

Returns:	the InChI key.
Return type:	str
Raises:	RuntimeError

to_json(kind='chemdoodle')[source]¶

Serialize a molecule using JSON.

Parameters:	kind (str) – The type of serialization to use. Only chemdoodle is currently supported.
Returns:	the json string.
Return type:	str

to_molblock(*args, **kwargs)¶

The serializer to be bound.

to_molfile(*args, **kwargs)¶

The serializer to be bound.

to_pdbblock(*args, **kwargs)¶

The serializer to be bound.

to_smarts(*args, **kwargs)¶

The serializer to be bound.

to_smiles(*args, **kwargs)¶

The serializer to be bound.

to_tplblock(*args, **kwargs)¶

The serializer to be bound.

to_tplfile(*args, **kwargs)¶

The serializer to be bound.

skchem.core.mol.bind_constructor(constructor_name, name_to_bind=None)[source]¶

Bind an (rdkit) constructor to the class

skchem.core.mol.bind_serializer(serializer_name, name_to_bind=None)[source]¶

Bind an (rdkit) serializer to the class

skchem.core.point module¶

Module contents¶

## skchem.core

Module defining chemical types used in scikit-chem.

class skchem.core.Atom[source]¶

Bases: rdkit.Chem.rdchem.Atom, skchem.core.base.ChemicalObject

Object representing an Atom in scikit-chem.

atomic_mass¶

float – the atomic mass of the atom in u.

atomic_number¶

int – the atomic number of the atom.

bonds¶

tuple<skchem.Bonds> – the bonds to this Atom.

cahn_ingold_prelog¶

The Cahn Ingold Prelog chirality indicator.

chiral_tag¶

int – the chiral tag.

covalent_radius¶

float – the covalent radius in angstroms.

degree¶

int – the degree of the atom.

depleted_degree¶

int – the degree of the atom in the h depleted molecular graph.

electron_affinity¶

float – the first electron affinity in eV.

explicit_valence¶

int – the explicit valence.

formal_charge¶

int – the formal charge.

full_degree¶

int – the full degree of the atom in the h full molecular graph.

hexcode¶

The hexcode to use as a color for the atom.

hybridization_state¶

str – the hybridization state.

implicit_valence¶

int – the implicit valence.

index¶

int – the index of the atom.

intrinsic_state¶

float – the intrinsic state of the atom.

ionisation_energy¶

float – the first ionisation energy in eV.

is_aromatic¶

bool – whether the atom is aromatic.

is_in_ring¶

bool – whether the atom is in a ring.

is_terminal¶

bool – whether the atom is terminal.

kier_hall_alpha_contrib¶

float – the covalent radius in angstroms.

kier_hall_electronegativity¶

float – the hall-keir electronegativity.

mcgowan_parameter¶

float – the mcgowan volume parameter

n_explicit_hs¶

int – the number of explicit hydrogens.

n_hs¶

int – the instanced, implicit and explicit number of hydrogens

n_implicit_hs¶

int – the number of implicit hydrogens.

n_instanced_hs¶

int – The number of instanced hydrogens.

n_lone_pairs¶

int – the number of lone pairs.

n_pi_electrons¶

int – the number of pi electrons.

n_total_hs¶

int – the total number of hydrogens (according to rdkit).

n_val_electrons¶

int – the number of valence electrons.

neighbours()[source]¶

tuple<Atom>: the neighbours of the atom.

owner¶

skchem.Mol – the owning molecule.

Warning

This will seg fault if the atom is created manually.

pauling_electronegativity¶

float – the pauling electronegativity on Pauling scale.

polarisability¶

float – the atomic polarisability in 10^{-20} m^3.

principal_quantum_number¶

int – the principle quantum number.

props¶

PropertyView – rdkit properties of the atom.

sanderson_electronegativity¶

float – the sanderson electronegativity on Pauling scale.

symbol¶

str – the element symbol of the atom.

valence¶

int – the valence.

valence_degree¶

int – the valence degree.

$$ delta_i^v = Z_i^v - h_i $$

Where $ Z_i^v $ is the number of valence electrons and $ h_i $ is the number of hydrogens.

van_der_waals_radius¶

float – the Van der Waals radius in angstroms.

van_der_waals_volume¶

float –

the van der waals volume in angstroms^3.

$

rac{4}{3} pi r_v^3 $

class skchem.core.Bond[source]¶

Bases: rdkit.Chem.rdchem.Bond, skchem.core.base.ChemicalObject

Class representing a chemical bond in scikit-chem.

atom_idxs¶

tuple[int] – list of atom indexes involved in the bond.

atoms¶

tuple[Atom] – list of atoms involved in the bond.

draw()[source]¶

str: Draw the bond in ascii.

index¶

int – the index of the bond in the atom.

is_aromatic¶

bool – whether the bond is aromatic.

is_conjugated¶

bool – whether the bond is conjugated.

is_in_ring¶

bool – whether the bond is in a ring.

order¶

int – the order of the bond.

owner¶

skchem.Mol – the molecule this bond is a part of.

props¶

PropertyView – rdkit properties of the atom.

stereo_symbol¶

str – the stereo label of the bond (‘Z’, ‘E’, ‘ANY’, ‘NONE’)

to_dict()[source]¶

dict: Convert to a dictionary representation.

class skchem.core.Conformer[source]¶

Bases: rdkit.Chem.rdchem.Conformer, skchem.core.base.ChemicalObject

Class representing a Conformer in scikit-chem.

align_with_principal_axes()[source]¶

Align the reference frame with the principal axes of inertia.

canonicalize()[source]¶

Center the reference frame at the centre of mass and

centre_of_mass¶

np.array – the centre of mass of the comformer.

centre_representation(centre_of_mass=True)[source]¶

Centre representation to the center of mass.

Parameters:	centre_of_mass (bool) – Whether to use the masses of atoms to calculate the centre of mass, or just use the mean position coordinate.
Returns:	Conformer

geometric_centre¶

np.array – the geometric centre of the conformer.

id¶

The ID of the conformer.

is_3d¶

bool – whether the conformer is three dimensional.

owner¶

skchem.Mol – the owning molecule.

positions¶

np.ndarray – the atom positions in the conformer.

Note

This is a copy of the data, not the data itself. You cannot allocate to a slice of this.

class skchem.core.Mol(*args, **kwargs)[source]¶

Bases: rdkit.Chem.rdchem.Mol, skchem.core.base.ChemicalObject

Class representing a Molecule in scikit-chem.

Mol objects inherit directly from rdkit Mol objects. Therefore, they contain atom and bond information, and may also include properties and atom bookmarks.

Example

Constructors are implemented as class methods with the from_ prefix.

>>> import skchem
>>> m = skchem.Mol.from_smiles('CC(=O)Cl'); m 
<Mol name="None" formula="C2H3ClO" at ...>

This is an rdkit Mol:

>>> from rdkit.Chem import Mol as RDKMol
>>> isinstance(m, RDKMol)
True

A name can be given at initialization: >>> m = skchem.Mol.from_smiles(‘CC(=O)Cl’, name=’acetyl chloride’); m # doctest: +ELLIPSIS <Mol name=”acetyl chloride” formula=”C2H3ClO” at ...>

>>> m.name
'acetyl chloride'

Serializers are implemented as instance methods with the to_ prefix.

>>> m.to_smiles()
'CC(=O)Cl'

>>> m.to_inchi()
'InChI=1S/C2H3ClO/c1-2(3)4/h1H3'

>>> m.to_inchi_key()
'WETWJCDKMRHUPV-UHFFFAOYSA-N'

RDKit properties are accessible through the props property:

>>> m.SetProp('example_key', 'example_value') # set prop with rdkit directly
>>> m.props['example_key']
'example_value'

>>> m.SetIntProp('float_key', 42) # set int prop with rdkit directly
>>> m.props['float_key']
42

They can be set too:

>>> m.props['example_set'] = 'set_value'
>>> m.GetProp('example_set') # getting with rdkit directly
'set_value'

We can export the properties into a dict or a pandas series:

>>> m.props.to_series()
example_key    example_value
example_set        set_value
float_key                 42
dtype: object

Atoms and bonds are provided in views:

>>> m.atoms 
<AtomView values="['C', 'C', 'O', 'Cl']" at ...>

>>> m.bonds 
<BondView values="['C-C', 'C=O', 'C-Cl']" at ...>

These are iterable: >>> [a.symbol for a in m.atoms] [‘C’, ‘C’, ‘O’, ‘Cl’]

The view provides shorthands for some attributes to get these:

>>> m.atoms.symbol  
array(['C', 'C', 'O', 'Cl'], dtype=...)

Atom and bond props can also be set:

>>> m.atoms[0].props['atom_key'] = 'atom_value'
>>> m.atoms[0].props['atom_key']
'atom_value'

The properties for atoms on the whole molecule can be accessed like so:

>>> m.atoms.props 
<MolPropertyView values="{'atom_key': ['atom_value', None, None, None]}" at ...>

The properties can be exported as a pandas dataframe >>> m.atoms.props.to_frame()

atom_key

atom_idx 0 atom_value 1 None 2 None 3 None

add_hs(inplace=False, add_coords=True, explicit_only=False, only_on_atoms=False)[source]¶

Add hydrogens to self.

Parameters:	inplace (bool) – Whether to add Hs to Mol, or return a new Mol. add_coords (bool) – Whether to set 3D coordinate for added Hs. explicit_only (bool) – Whether to add only explicit Hs, or also implicit ones. only_on_atoms (iterable<bool>) – An iterable specifying the atoms to add Hs.
Returns:	Mol with Hs added.
Return type:	skchem.Mol

atoms¶

List[skchem.Atom] – An iterable over the atoms of the molecule.

bonds¶

List[skchem.Bond] – An iterable over the bonds of the molecule.

conformers¶

List[Conformer] – conformers of the molecule.

copy()[source]¶

Return a copy of the molecule.

classmethod from_binary(binary)[source]¶

Decode a molecule from a binary serialization.

Parameters:	binary – The bytes string to decode.
Returns:	The molecule encoded in the binary.
Return type:	skchem.Mol

classmethod from_inchi(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_mol2block(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_mol2file(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_molblock(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_molfile(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_pdbblock(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_pdbfile(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_smarts(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_smiles(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_tplblock(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

classmethod from_tplfile(_, in_arg, name=None, *args, **kwargs)¶

The constructor to be bound.

mass¶

float – the mass of the molecule.

name¶

str – The name of the molecule.

Raises:	KeyError

props¶

PropertyView – A dictionary of the properties of the molecule.

remove_hs(inplace=False, sanitize=True, update_explicit=False, implicit_only=False)[source]¶

Remove hydrogens from self.

Parameters:	inplace (bool) – Whether to add Hs to Mol, or return a new Mol. sanitize (bool) – Whether to sanitize after Hs are removed. update_explicit (bool) – Whether to update explicit count after the removal. implicit_only (bool) – Whether to remove explict and implicit Hs, or Hs only.
Returns:	Mol with Hs removed.
Return type:	skchem.Mol

to_binary()[source]¶

Serialize the molecule to binary encoding.

Returns:	the molecule in bytes.
Return type:	bytes

Notes

Due to limitations in RDKit, not all data is serialized. Notably, properties are not, so e.g. compound names are not saved.

to_dict(kind='chemdoodle', conformer_id=-1)[source]¶

A dictionary representation of the molecule.

Parameters:	kind (str) – The type of representation to use. Only chemdoodle is currently supported.
Returns:	dictionary representation of the molecule.
Return type:	dict

to_formula()[source]¶

str: the chemical formula of the molecule.

Raises:	RuntimeError

to_inchi(*args, **kwargs)¶

The serializer to be bound.

to_inchi_key()[source]¶

The InChI key of the molecule.

Returns:	the InChI key.
Return type:	str
Raises:	RuntimeError

to_json(kind='chemdoodle')[source]¶

Serialize a molecule using JSON.

Parameters:	kind (str) – The type of serialization to use. Only chemdoodle is currently supported.
Returns:	the json string.
Return type:	str

to_molblock(*args, **kwargs)¶

The serializer to be bound.

to_molfile(*args, **kwargs)¶

The serializer to be bound.

to_pdbblock(*args, **kwargs)¶

The serializer to be bound.

to_smarts(*args, **kwargs)¶

The serializer to be bound.

to_smiles(*args, **kwargs)¶

The serializer to be bound.

to_tplblock(*args, **kwargs)¶

The serializer to be bound.

to_tplfile(*args, **kwargs)¶

The serializer to be bound.

Submodules¶

skchem.cross_validation.similarity_threshold module¶

## skchem.cross_validation.similarity_threshold

Similarity threshold dataset partitioning functionality.

class skchem.cross_validation.similarity_threshold.SimThresholdSplit(min_threshold=0.45, largest_cluster_fraction=0.1, fper='morgan', similarity_metric='jaccard', memory_optimized=True, n_jobs=1, block_width=1000, verbose=False)[source]¶

Bases: object

block_width¶

The width of the subsets of features.

Note

Only used in parallelized.

fit(inp, pairs=None)[source]¶

Fit the cross validator to the data. :param inp:

• pd.Series of Mol instances
• pd.DataFrame with Mol instances as a structure row.
• pd.DataFrame of fingerprints if fper is None
• pd.DataFrame of sim matrix if similarity_metric is None
• np.array of sim matrix if similarity_metric is None

k_fold(n_folds)[source]¶

Returns k-fold cross-validated folds with thresholded similarity.

Parameters:	n_folds (int) – The number of folds to provide.
Returns:	generator[ – The splits in series.
Return type:	pd.Series, pd.Series

n_instances_¶

The number of instances that were used to fit the object.

n_jobs¶

The number of processes to use to calculate the distance matrix.

-1 for all available.

split(ratio)[source]¶

Return splits of the data with thresholded similarity according to a specified ratio.

Parameters:	ratio (tuple[ints]) – the ratio to use.
Returns:	Generator of boolean split masks for the reqested splits.
Return type:	generator[pd.Series]

Example

>>> ms = skchem.data.Diversity.read_frame('structure') 
>>> st = SimThresholdSplit(fper='morgan', 
...                        similarity_metric='jaccard')
>>> st.fit(ms) 
>>> train, valid, test = st.split(ratio=(70, 15, 15)) 

visualize_similarities(subsample=5000, ax=None)[source]¶

Plot a histogram of similarities, with the threshold plotted.

Parameters:	subsample (int) – For a large dataset, subsample the number of compounds to consider. ax (matplotlib.axis) – Axis to make the plot on.
Returns:	matplotlib.axes

visualize_space(dim_reducer='tsne', dim_red_kw=None, subsample=5000, ax=None, plt_kw=None)[source]¶

Plot chemical space using a transformer

Parameters:	dim_reducer (str or sklearn object) – Technique to use to reduce fingerprint space. dim_red_kw (dict) – Keyword args to pass to dim_reducer. subsample (int) – for a large dataset, subsample the number of compounds to consider. ax (matplotlib.axis) – Axis to make the plot on. plt_kw (dict) – Keyword args to pass to the plot.
Returns:	matplotlib.axes

skchem.cross_validation.similarity_threshold.returns_pairs(func)[source]¶

Wraps a function that returns a ((i, j), sim) list to return a dataframe.

Module contents¶

## skchem.cross_validation

Module implementing cross validation routines useful for chemical data.

class skchem.cross_validation.SimThresholdSplit(min_threshold=0.45, largest_cluster_fraction=0.1, fper='morgan', similarity_metric='jaccard', memory_optimized=True, n_jobs=1, block_width=1000, verbose=False)[source]¶

Bases: object

block_width¶

The width of the subsets of features.

Note

Only used in parallelized.

fit(inp, pairs=None)[source]¶

Fit the cross validator to the data. :param inp:

• pd.Series of Mol instances
• pd.DataFrame with Mol instances as a structure row.
• pd.DataFrame of fingerprints if fper is None
• pd.DataFrame of sim matrix if similarity_metric is None
• np.array of sim matrix if similarity_metric is None

k_fold(n_folds)[source]¶

Returns k-fold cross-validated folds with thresholded similarity.

Parameters:	n_folds (int) – The number of folds to provide.
Returns:	generator[ – The splits in series.
Return type:	pd.Series, pd.Series

n_instances_¶

The number of instances that were used to fit the object.

n_jobs¶

The number of processes to use to calculate the distance matrix.

-1 for all available.

split(ratio)[source]¶

Return splits of the data with thresholded similarity according to a specified ratio.

Parameters:	ratio (tuple[ints]) – the ratio to use.
Returns:	Generator of boolean split masks for the reqested splits.
Return type:	generator[pd.Series]

Example

>>> ms = skchem.data.Diversity.read_frame('structure') 
>>> st = SimThresholdSplit(fper='morgan', 
...                        similarity_metric='jaccard')
>>> st.fit(ms) 
>>> train, valid, test = st.split(ratio=(70, 15, 15)) 

visualize_similarities(subsample=5000, ax=None)[source]¶

Plot a histogram of similarities, with the threshold plotted.

Parameters:	subsample (int) – For a large dataset, subsample the number of compounds to consider. ax (matplotlib.axis) – Axis to make the plot on.
Returns:	matplotlib.axes

visualize_space(dim_reducer='tsne', dim_red_kw=None, subsample=5000, ax=None, plt_kw=None)[source]¶

Plot chemical space using a transformer

Parameters:	dim_reducer (str or sklearn object) – Technique to use to reduce fingerprint space. dim_red_kw (dict) – Keyword args to pass to dim_reducer. subsample (int) – for a large dataset, subsample the number of compounds to consider. ax (matplotlib.axis) – Axis to make the plot on. plt_kw (dict) – Keyword args to pass to the plot.
Returns:	matplotlib.axes

Subpackages¶