#!/usr/bin/env python
# =============================================================================================
# MODULE DOCSTRING
# =============================================================================================
"""
Class definitions to represent a molecular system and its chemical components
.. todo::
* Create MoleculeImage, ParticleImage, AtomImage, VirtualSiteImage here. (Or ``MoleculeInstance``?)
* Create ``MoleculeGraph`` to represent fozen set of atom elements and bonds that can used as a key for compression
* Add hierarchical way of traversing Topology (chains, residues)
* Make all classes hashable and serializable.
* JSON/BSON representations of objects?
* Use `attrs <http://www.attrs.org/>`_ for object setter boilerplate?
"""
# =============================================================================================
# GLOBAL IMPORTS
# =============================================================================================
import itertools
from collections import OrderedDict
from collections.abc import MutableMapping
import numpy as np
from simtk import unit
from simtk.openmm import app
from openforcefield.typing.chemistry import ChemicalEnvironment
from openforcefield.utils import MessageException
from openforcefield.utils.serialization import Serializable
from openforcefield.utils.toolkits import (
ALLOWED_AROMATICITY_MODELS,
ALLOWED_CHARGE_MODELS,
ALLOWED_FRACTIONAL_BOND_ORDER_MODELS,
DEFAULT_AROMATICITY_MODEL,
GLOBAL_TOOLKIT_REGISTRY,
)
# =============================================================================================
# Exceptions
# =============================================================================================
class DuplicateUniqueMoleculeError(MessageException):
"""
Exception for when the user provides indistinguishable unique molecules when trying to identify atoms from a PDB
"""
pass
class NotBondedError(MessageException):
"""
Exception for when a function requires a bond between two atoms, but none is present
"""
pass
class InvalidBoxVectorsError(MessageException):
"""
Exception for setting invalid box vectors
"""
# =============================================================================================
# PRIVATE SUBROUTINES
# =============================================================================================
class _TransformedDict(MutableMapping):
"""A dictionary that transform and sort keys.
The function __keytransform__ can be inherited to apply an arbitrary
key-altering function before accessing the keys.
The function __sortfunc__ can be inherited to specify a particular
order over which to iterate over the dictionary.
"""
def __init__(self, *args, **kwargs):
self.store = OrderedDict()
self.update(dict(*args, **kwargs)) # use the free update to set keys
def __getitem__(self, key):
return self.store[self.__keytransform__(key)]
def __setitem__(self, key, value):
self.store[self.__keytransform__(key)] = value
def __delitem__(self, key):
del self.store[self.__keytransform__(key)]
def __iter__(self):
return iter(sorted(self.store, key=self.__sortfunc__))
def __len__(self):
return len(self.store)
def __keytransform__(self, key):
return key
@staticmethod
def __sortfunc__(key):
return key
# TODO: Encapsulate this atom ordering logic directly into Atom/Bond/Angle/Torsion classes?
[docs]class ValenceDict(_TransformedDict):
"""Enforce uniqueness in atom indices."""
[docs] @staticmethod
def index_of(key, possible=None):
"""
Generates a canonical ordering of the equivalent permutations of ``key`` (equivalent rearrangements of indices)
and identifies which of those possible orderings this particular ordering is. This method is useful when
multiple SMARTS patterns might match the same atoms, but local molecular symmetry or the use of
wildcards in the SMARTS could make the matches occur in arbitrary order.
This method can be restricted to a subset of the canonical orderings, by providing
the optional ``possible`` keyword argument. If provided, the index returned by this method will be
the index of the element in ``possible`` after undergoing the same canonical sorting as above.
Parameters
----------
key : iterable of int
A valid key for ValenceDict
possible : iterable of iterable of int, optional. default=``None``
A subset of the possible orderings that this match might take.
Returns
-------
index : int
"""
assert len(key) < 4
refkey = __class__.key_transform(key)
if len(key) == 2:
permutations = OrderedDict(
{(refkey[0], refkey[1]): 0, (refkey[1], refkey[0]): 1}
)
elif len(key) == 3:
permutations = OrderedDict(
{
(refkey[0], refkey[1], refkey[2]): 0,
(refkey[2], refkey[1], refkey[0]): 1,
}
)
else:
# For a proper, only forward/backward makes sense
permutations = OrderedDict(
{
(refkey[0], refkey[1], refkey[2], refkey[3]): 0,
(refkey[3], refkey[1], refkey[2], refkey[0]): 1,
}
)
if possible is not None:
i = 0
# If the possible permutations were provided, ensure that `possible` is a SUBSET of `permutations`
assert all([p in permutations for p in possible]), (
"Possible permutations " + str(possible) + " is impossible!"
)
# TODO: Double-check whether this will generalize. It seems like this would fail if ``key``
# were in ``permutations``, but not ``possible``
for k in permutations:
if all([x == y for x, y in zip(key, k)]):
return i
if k in possible:
i += 1
else:
# If the possible permutations were NOT provided, then return the unique index of this permutation.
return permutations[key]
def __keytransform__(self, key):
return __class__.key_transform(key)
class SortedDict(_TransformedDict):
"""Enforce uniqueness of atom index tuples, without any restrictions on atom reordering."""
def __keytransform__(self, key):
"""Sort tuple from lowest to highest."""
# Ensure key is a tuple.
key = tuple(sorted(key))
# Reverse the key if the first element is bigger than the last.
return key
[docs]class ImproperDict(_TransformedDict):
"""Symmetrize improper torsions."""
[docs] @staticmethod
def index_of(key, possible=None):
"""
Generates a canonical ordering of the equivalent permutations of ``key`` (equivalent rearrangements of indices)
and identifies which of those possible orderings this particular ordering is. This method is useful when
multiple SMARTS patterns might match the same atoms, but local molecular symmetry or the use of
wildcards in the SMARTS could make the matches occur in arbitrary order.
This method can be restricted to a subset of the canonical orderings, by providing
the optional ``possible`` keyword argument. If provided, the index returned by this method will be
the index of the element in ``possible`` after undergoing the same canonical sorting as above.
Parameters
----------
key : iterable of int
A valid key for ValenceDict
possible : iterable of iterable of int, optional. default=``None``
A subset of the possible orderings that this match might take.
Returns
-------
index : int
"""
assert len(key) == 4
refkey = __class__.key_transform(key)
permutations = OrderedDict(
{
(refkey[0], refkey[1], refkey[2], refkey[3]): 0,
(refkey[0], refkey[1], refkey[3], refkey[2]): 1,
(refkey[2], refkey[1], refkey[0], refkey[3]): 2,
(refkey[2], refkey[1], refkey[3], refkey[0]): 3,
(refkey[3], refkey[1], refkey[0], refkey[2]): 4,
(refkey[3], refkey[1], refkey[2], refkey[0]): 5,
}
)
if possible is not None:
assert all(
[p in permutations for p in possible]
), "Possible permuation is impossible!"
i = 0
for k in permutations:
if all([x == y for x, y in zip(key, k)]):
return i
if k in possible:
i += 1
else:
return permutations[key]
def __keytransform__(self, key):
return __class__.key_transform(key)
# =============================================================================================
# TOPOLOGY OBJECTS
# =============================================================================================
# =============================================================================================
# TopologyAtom
# =============================================================================================
[docs]class TopologyAtom(Serializable):
"""
A TopologyAtom is a lightweight data structure that represents a single openforcefield.topology.molecule.Atom in
a Topology. A TopologyAtom consists of two references -- One to its fully detailed "atom", an
openforcefield.topology.molecule.Atom, and another to its parent "topology_molecule", which occupies a spot in
the parent Topology's TopologyMolecule list.
As some systems can be very large, there is no always-existing representation of a TopologyAtom. They are created on
demand as the user requests them.
.. warning :: This API is experimental and subject to change.
"""
[docs] def __init__(self, atom, topology_molecule):
"""
Create a new TopologyAtom.
Parameters
----------
atom : An openforcefield.topology.molecule.Atom
The reference atom
topology_molecule : An openforcefield.topology.TopologyMolecule
The TopologyMolecule that this TopologyAtom belongs to
"""
# TODO: Type checks
self._atom = atom
self._topology_molecule = topology_molecule
@property
def atom(self):
"""
Get the reference Atom for this TopologyAtom.
Returns
-------
an openforcefield.topology.molecule.Atom
"""
return self._atom
@property
def atomic_number(self):
"""
Get the atomic number of this atom
Returns
-------
int
"""
return self._atom.atomic_number
@property
def topology_molecule(self):
"""
Get the TopologyMolecule that this TopologyAtom belongs to.
Returns
-------
openforcefield.topology.TopologyMolecule
"""
return self._topology_molecule
@property
def molecule(self):
"""
Get the reference Molecule that this TopologyAtom belongs to.
Returns
-------
openforcefield.topology.molecule.Molecule
"""
return self._topology_molecule.molecule
@property
def topology_atom_index(self):
"""
Get the index of this atom in its parent Topology.
Returns
-------
int
The index of this atom in its parent topology.
"""
mapped_molecule_atom_index = self._topology_molecule._ref_to_top_index[
self._atom.molecule_atom_index
]
return (
self._topology_molecule.atom_start_topology_index
+ mapped_molecule_atom_index
)
@property
def topology_particle_index(self):
"""
Get the index of this particle in its parent Topology.
Returns
-------
int
The index of this atom in its parent topology.
"""
# This assumes that the particles in a topology are listed with all atoms from all TopologyMolecules
# first, followed by all VirtualSites from all TopologyMolecules second
return self.topology_atom_index
@property
def topology_bonds(self):
"""
Get the TopologyBonds connected to this TopologyAtom.
Returns
-------
iterator of openforcefield.topology.TopologyBonds
"""
for bond in self._atom.bonds:
reference_mol_bond_index = bond.molecule_bond_index
yield self._topology_molecule.bond(reference_mol_bond_index)
def __eq__(self, other):
return (self._atom == other._atom) and (
self._topology_molecule == other._topology_molecule
)
def __repr__(self):
return "TopologyAtom {} with reference atom {} and parent TopologyMolecule {}".format(
self.topology_atom_index, self._atom, self._topology_molecule
)
[docs] def to_dict(self):
"""Convert to dictionary representation."""
# Implement abstract method Serializable.to_dict()
raise NotImplementedError() # TODO
[docs] @classmethod
def from_dict(cls, d):
"""Static constructor from dictionary representation."""
# Implement abstract method Serializable.to_dict()
raise NotImplementedError() # TODO
# @property
# def bonds(self):
# """
# Get the Bonds connected to this TopologyAtom.
#
# Returns
# -------
# iterator of openforcefield.topology.molecule.Bonds
# """
# for bond in self._atom.bonds:
# yield bond
# TODO: Add all atom properties here? Or just make people use TopologyAtom.atom for that?
# =============================================================================================
# TopologyBond
# =============================================================================================
[docs]class TopologyBond(Serializable):
"""
A TopologyBond is a lightweight data structure that represents a single openforcefield.topology.molecule.Bond in
a Topology. A TopologyBond consists of two references -- One to its fully detailed "bond", an
openforcefield.topology.molecule.Bond, and another to its parent "topology_molecule", which occupies a spot in
the parent Topology's TopologyMolecule list.
As some systems can be very large, there is no always-existing representation of a TopologyBond. They are created on
demand as the user requests them.
.. warning :: This API is experimental and subject to change.
"""
[docs] def __init__(self, bond, topology_molecule):
"""
Parameters
----------
bond : An openforcefield.topology.molecule.Bond
The reference bond.
topology_molecule : An openforcefield.topology.TopologyMolecule
The TopologyMolecule that this TopologyBond belongs to.
"""
# TODO: Type checks
self._bond = bond
self._topology_molecule = topology_molecule
@property
def bond(self):
"""
Get the reference Bond for this TopologyBond.
Returns
-------
an openforcefield.topology.molecule.Bond
"""
return self._bond
@property
def topology_molecule(self):
"""
Get the TopologyMolecule that this TopologyBond belongs to.
Returns
-------
openforcefield.topology.TopologyMolecule
"""
return self._topology_molecule
@property
def topology_bond_index(self):
"""
Get the index of this bond in its parent Topology.
Returns
-------
int
The index of this bond in its parent topology.
"""
return (
self._topology_molecule.bond_start_topology_index
+ self._bond.molecule_bond_index
)
@property
def molecule(self):
"""
Get the reference Molecule that this TopologyBond belongs to.
Returns
-------
openforcefield.topology.molecule.Molecule
"""
return self._topology_molecule.molecule
@property
def bond_order(self):
"""
Get the order of this TopologyBond.
Returns
-------
int : bond order
"""
return self._bond.bond_order
@property
def atoms(self):
"""
Get the TopologyAtoms connected to this TopologyBond.
Returns
-------
iterator of openforcefield.topology.TopologyAtom
"""
for ref_atom in self._bond.atoms:
yield TopologyAtom(ref_atom, self._topology_molecule)
[docs] def to_dict(self):
"""Convert to dictionary representation."""
# Implement abstract method Serializable.to_dict()
raise NotImplementedError() # TODO
[docs] @classmethod
def from_dict(cls, d):
"""Static constructor from dictionary representation."""
# Implement abstract method Serializable.to_dict()
raise NotImplementedError() # TODO
# =============================================================================================
# TopologyVirtualSite
# =============================================================================================
[docs]class TopologyVirtualSite(Serializable):
"""
A TopologyVirtualSite is a lightweight data structure that represents a single
openforcefield.topology.molecule.VirtualSite in a Topology. A TopologyVirtualSite consists of two references --
One to its fully detailed "VirtualSite", an openforcefield.topology.molecule.VirtualSite, and another to its parent
"topology_molecule", which occupies a spot in the parent Topology's TopologyMolecule list.
As some systems can be very large, there is no always-existing representation of a TopologyVirtualSite. They are
created on demand as the user requests them.
.. warning :: This API is experimental and subject to change.
"""
[docs] def __init__(self, virtual_site, topology_molecule):
"""
Parameters
----------
virtual_site : An openforcefield.topology.molecule.VirtualSite
The reference virtual site
topology_molecule : An openforcefield.topology.TopologyMolecule
The TopologyMolecule that this TopologyVirtualSite belongs to
"""
# TODO: Type checks
self._virtual_site = virtual_site
self._topology_molecule = topology_molecule
self._topology_virtual_particle_start_index = None
def invalidate_cached_data(self):
self._topology_virtual_particle_start_index = None
[docs] def atom(self, index):
"""
Get the atom at a specific index in this TopologyVirtualSite
Parameters
----------
index : int
The index of the atom in the reference VirtualSite to retrieve
Returns
-------
TopologyAtom
"""
return TopologyAtom(self._virtual_site.atoms[index], self.topology_molecule)
@property
def atoms(self):
"""
Get the TopologyAtoms involved in this TopologyVirtualSite.
Returns
-------
iterator of openforcefield.topology.TopologyAtom
"""
for ref_atom in self._virtual_site.atoms:
yield TopologyAtom(ref_atom, self._topology_molecule)
@property
def virtual_site(self):
"""
Get the reference VirtualSite for this TopologyVirtualSite.
Returns
-------
an openforcefield.topology.molecule.VirtualSite
"""
return self._virtual_site
@property
def topology_molecule(self):
"""
Get the TopologyMolecule that this TopologyVirtualSite belongs to.
Returns
-------
openforcefield.topology.TopologyMolecule
"""
return self._topology_molecule
@property
def topology_virtual_site_index(self):
"""
Get the index of this virtual site in its parent Topology.
Returns
-------
int
The index of this virtual site in its parent topology.
"""
return (
self._topology_molecule.virtual_site_start_topology_index
+ self._virtual_site.molecule_virtual_site_index
)
@property
def n_particles(self):
"""
Get the number of particles represented by this VirtualSite
Returns
-------
int : The number of particles
"""
return self._virtual_site.n_particles
@property
def topology_virtual_particle_start_index(self):
"""
Get the index of the first virtual site particle in its parent Topology.
Returns
-------
int
The index of this particle in its parent topology.
"""
# This assumes that the particles in a topology are listed with all
# atoms from all TopologyMolecules first, followed by all VirtualSites
# from all TopologyMolecules second
# If the cached value is not available, generate it
if self._topology_virtual_particle_start_index is None:
virtual_particle_start_topology_index = (
self.topology_molecule.topology.n_topology_atoms
)
for (
topology_molecule
) in self._topology_molecule._topology.topology_molecules:
for tvsite in topology_molecule.virtual_sites:
if self == tvsite:
break
virtual_particle_start_topology_index += tvsite.n_particles
if self._topology_molecule == topology_molecule:
break
# else:
# virtual_particle_start_topology_index += tvsite.n_particles
# virtual_particle_start_topology_index += topology_molecule.n_particles
self._topology_virtual_particle_start_index = (
virtual_particle_start_topology_index
)
# Return cached value
# print(self._topology_virtual_particle_start_index)
return self._topology_virtual_particle_start_index
@property
def particles(self):
"""
Get an iterator to the reference particles that this TopologyVirtualSite
contains.
Returns
-------
iterator of TopologyVirtualParticles
"""
for vptl in self.virtual_site.particles:
yield TopologyVirtualParticle(
self._virtual_site, vptl, self._topology_molecule
)
@property
def molecule(self):
"""
Get the reference Molecule that this TopologyVirtualSite belongs to.
Returns
-------
openforcefield.topology.molecule.Molecule
"""
return self._topology_molecule.molecule
@property
def type(self):
"""
Get the type of this virtual site
Returns
-------
str : The class name of this virtual site
"""
return self._virtual_site.type
def __eq__(self, other):
return (self._virtual_site == other._virtual_site) and (
self._topology_molecule == other._topology_molecule
)
[docs] def to_dict(self):
"""Convert to dictionary representation."""
# Implement abstract method Serializable.to_dict()
raise NotImplementedError() # TODO
[docs] @classmethod
def from_dict(cls, d):
"""Static constructor from dictionary representation."""
# Implement abstract method Serializable.to_dict()
raise NotImplementedError() # TODO
# =============================================================================================
# TopologyVirtualParticle
# =============================================================================================
[docs]class TopologyVirtualParticle(TopologyVirtualSite):
[docs] def __init__(self, virtual_site, virtual_particle, topology_molecule):
self._virtual_site = virtual_site
self._virtual_particle = virtual_particle
self._topology_molecule = topology_molecule
def __eq__(self, other):
if type(other) != type(self):
return False
same_vsite = super() == super(TopologyVirtualParticle, other)
if not same_vsite:
return False
same_ptl = self.topology_particle_index == other.topology_particle_index
return same_ptl
@property
def topology_particle_index(self):
"""
Get the index of this particle in its parent Topology.
Returns
-------
idx : int
The index of this particle in its parent topology.
"""
# This assumes that the particles in a topology are listed with all atoms from all TopologyMolecules
# first, followed by all VirtualSites from all TopologyMolecules second
orientation_key = self._virtual_particle.orientation
offset = 0
# vsite is a topology vsite, which has a regular vsite
for i, ornt in enumerate(self._virtual_site._virtual_site.orientations):
if ornt == orientation_key:
offset = i
break
return offset + self._virtual_site.topology_virtual_particle_start_index
# =============================================================================================
# TopologyMolecule
# =============================================================================================
[docs]class TopologyMolecule:
"""
TopologyMolecules are built to be an efficient way to store large numbers of copies of the same molecule for
parameterization and system preparation.
.. warning :: This API is experimental and subject to change.
"""
[docs] def __init__(
self, reference_molecule, topology, local_topology_to_reference_index=None
):
"""
Create a new TopologyMolecule.
Parameters
----------
reference_molecule : an openforcefield.topology.molecule.Molecule
The reference molecule, with details like formal charges, partial charges, bond orders, partial bond orders,
and atomic symbols.
topology : an openforcefield.topology.Topology
The topology that this TopologyMolecule belongs to
local_topology_to_reference_index : dict, optional, default=None
Dictionary of {TopologyMolecule_atom_index : Molecule_atom_index} for the TopologyMolecule that will be built
"""
# TODO: Type checks
self._reference_molecule = reference_molecule
self._topology = topology
if local_topology_to_reference_index is None:
local_topology_to_reference_index = dict(
[(i, i) for i in range(reference_molecule.n_atoms)]
)
self._top_to_ref_index = local_topology_to_reference_index
self._ref_to_top_index = dict(
(k, j) for j, k in local_topology_to_reference_index.items()
)
# Initialize cached data
self._atom_start_topology_index = None
self._particle_start_topology_index = None
self._bond_start_topology_index = None
self._virtual_site_start_topology_index = None
self._virtual_particle_start_topology_index = None
def _invalidate_cached_data(self):
"""Unset all cached data, in response to an appropriate change"""
self._atom_start_topology_index = None
self._particle_start_topology_index = None
self._bond_start_topology_index = None
self._virtual_site_start_topology_index = None
self._virtual_particle_start_topology_index = None
for vsite in self.virtual_sites:
vsite.invalidate_cached_data()
@property
def topology(self):
"""
Get the topology that this TopologyMolecule belongs to
Returns
-------
an openforcefield.topology.Topology
"""
return self._topology
@property
def reference_molecule(self):
"""
Get the reference molecule for this TopologyMolecule
Returns
-------
an openforcefield.topology.molecule.Molecule
"""
return self._reference_molecule
@property
def n_atoms(self):
"""
The number of atoms in this topology.
Returns
-------
int
"""
return self._reference_molecule.n_atoms
[docs] def atom(self, index):
"""
Get the TopologyAtom with a given topology atom index in this TopologyMolecule.
Parameters
----------
index : int
Index of the TopologyAtom within this TopologyMolecule to retrieve
Returns
-------
an openforcefield.topology.TopologyAtom
"""
ref_mol_atom_index = self._top_to_ref_index[index]
return TopologyAtom(self._reference_molecule.atoms[ref_mol_atom_index], self)
@property
def atoms(self):
"""
Return an iterator of all the TopologyAtoms in this TopologyMolecule
Returns
-------
an iterator of openforcefield.topology.TopologyAtoms
"""
iterate_order = list(self._top_to_ref_index.items())
# Sort by topology index
iterate_order.sort(key=lambda x: x[0])
for top_index, ref_index in iterate_order:
# self._reference_molecule.atoms:
yield TopologyAtom(self._reference_molecule.atoms[ref_index], self)
@property
def atom_start_topology_index(self):
"""
Get the topology index of the first atom in this TopologyMolecule
"""
# If cached value is not available, generate it.
if self._atom_start_topology_index is None:
atom_start_topology_index = 0
for topology_molecule in self._topology.topology_molecules:
if self == topology_molecule:
self._atom_start_topology_index = atom_start_topology_index
break
atom_start_topology_index += topology_molecule.n_atoms
# Return cached value
return self._atom_start_topology_index
@property
def virtual_particle_start_topology_index(self):
"""
Get the topology index of the first virtual particle in this TopologyMolecule
"""
# If cached value is not available, generate it.
if self._virtual_particle_start_topology_index is None:
particle_start_topology_index = self.topology.n_atoms
for topology_molecule in self._topology.topology_molecules:
if self == topology_molecule:
self._particle_start_topology_index = particle_start_topology_index
break
offset = sum(
[vsite.n_particles for vsite in topology_molecule.virtual_sites]
)
particle_start_topology_index += offset
self._virtual_particle_start_topology_index = particle_start_topology_index
# Return cached value
return self._virtual_particle_start_topology_index
[docs] def bond(self, index):
"""
Get the TopologyBond with a given reference molecule index in this TopologyMolecule
Parameters
----------
index : int
Index of the TopologyBond within this TopologyMolecule to retrieve
Returns
-------
an openforcefield.topology.TopologyBond
"""
return TopologyBond(self.reference_molecule.bonds[index], self)
@property
def bonds(self):
"""
Return an iterator of all the TopologyBonds in this TopologyMolecule
Returns
-------
an iterator of openforcefield.topology.TopologyBonds
"""
for bond in self._reference_molecule.bonds:
yield TopologyBond(bond, self)
@property
def n_bonds(self):
"""Get the number of bonds in this TopologyMolecule
Returns
-------
int : number of bonds
"""
return self._reference_molecule.n_bonds
@property
def bond_start_topology_index(self):
"""Get the topology index of the first bond in this TopologyMolecule"""
# If cached value is not available, generate it.
if self._bond_start_topology_index is None:
bond_start_topology_index = 0
for topology_molecule in self._topology.topology_molecules:
if self == topology_molecule:
self._bond_start_topology_index = bond_start_topology_index
break
bond_start_topology_index += topology_molecule.n_bonds
# Return cached value
return self._bond_start_topology_index
[docs] def particle(self, index):
"""
Get the TopologyParticle with a given reference molecule index in this TopologyMolecule
Parameters
----------
index : int
Index of the TopologyParticle within this TopologyMolecule to retrieve
Returns
-------
an openforcefield.topology.TopologyParticle
"""
return TopologyParticle(self.reference_molecule.particles[index], self)
@property
def particles(self):
"""
Return an iterator of all the TopologyParticles in this TopologyMolecules
Returns
-------
an iterator of openforcefield.topology.TopologyParticle
"""
# Note: This assumes that particles are all Atoms (in topology map order), and then virtualsites
yield_order = list(self._top_to_ref_index.items())
# Sort by topology atom index
yield_order.sort(key=lambda x: x[0])
for top_atom_index, ref_mol_atom_index in yield_order:
ref_atom = self._reference_molecule.atoms[ref_mol_atom_index]
yield TopologyAtom(ref_atom, self)
for vsite in self.reference_molecule.virtual_sites:
tvsite = TopologyVirtualSite(vsite, self)
for vptl in vsite.particles:
yield TopologyVirtualParticle(tvsite, vptl, self)
@property
def n_particles(self):
"""Get the number of particles in this TopologyMolecule
Returns
-------
int : The number of particles
"""
return self._reference_molecule.n_particles
[docs] def virtual_site(self, index):
"""
Get the TopologyVirtualSite with a given reference molecule index in this TopologyMolecule
Parameters
----------
index : int
Index of the TopologyVirtualSite within this TopologyMolecule to retrieve
Returns
-------
an openforcefield.topology.TopologyVirtualSite
"""
return TopologyVirtualSite(self.reference_molecule.virtual_sites[index], self)
@property
def virtual_sites(self):
"""
Return an iterator of all the TopologyVirtualSites in this TopologyMolecules
Returns
-------
an iterator of openforcefield.topology.TopologyVirtualSite
"""
for vsite in self._reference_molecule.virtual_sites:
yield TopologyVirtualSite(vsite, self)
@property
def n_virtual_sites(self):
"""Get the number of virtual sites in this TopologyMolecule
Returns
-------
int
"""
return self._reference_molecule.n_virtual_sites
@property
def angles(self):
"""Iterable of Tuple[TopologyAtom]: iterator over the angles in this Topology."""
return self._convert_to_topology_atom_tuples(self._reference_molecule.angles)
@property
def n_angles(self):
"""int: number of angles in this Topology."""
return self._reference_molecule.n_angles
@property
def propers(self):
"""Iterable of Tuple[TopologyAtom]: iterator over the proper torsions in this Topology."""
return self._convert_to_topology_atom_tuples(self._reference_molecule.propers)
@property
def n_propers(self):
"""int: number of proper torsions in this Topology."""
return self._reference_molecule.n_propers
@property
def impropers(self):
"""Iterable of Tuple[TopologyAtom]: iterator over the improper torsions in this Topology."""
return self._convert_to_topology_atom_tuples(self._reference_molecule.impropers)
@property
def n_impropers(self):
"""int: number of proper torsions in this Topology."""
return self._reference_molecule.n_impropers
@property
def virtual_site_start_topology_index(self):
"""Get the topology index of the first virtual site in this TopologyMolecule"""
# If the cached value is not available, generate it
if self._virtual_site_start_topology_index is None:
virtual_site_start_topology_index = 0
for topology_molecule in self._topology.topology_molecules:
if self == topology_molecule:
self._virtual_site_start_topology_index = (
virtual_site_start_topology_index
)
virtual_site_start_topology_index += topology_molecule.n_virtual_sites
# Return cached value
return self._virtual_site_start_topology_index
[docs] def to_dict(self):
"""Convert to dictionary representation."""
# Implement abstract method Serializable.to_dict()
raise NotImplementedError() # TODO
[docs] @classmethod
def from_dict(cls, d):
"""Static constructor from dictionary representation."""
# Implement abstract method Serializable.to_dict()
raise NotImplementedError() # TODO
def _convert_to_topology_atom_tuples(self, molecule_atom_tuples):
for atom_tuple in molecule_atom_tuples:
mol_atom_indices = (a.molecule_atom_index for a in atom_tuple)
top_mol_atom_indices = (
self._ref_to_top_index[mol_idx] for mol_idx in mol_atom_indices
)
yield tuple(self.atom(i) for i in top_mol_atom_indices)
# TODO: pick back up figuring out how we want TopologyMolecules to know their starting TopologyParticle indices
# =============================================================================================
# Topology
# =============================================================================================
# TODO: Revise documentation and remove chains
[docs]class Topology(Serializable):
"""
A Topology is a chemical representation of a system containing one or more molecules appearing in a specified order.
As of the 0.7.0 release, the Topology particle indexing system puts all atoms before all virtualsites.
This ensures that atoms keep the same Topology particle index value, even if the Topology
is modified during system creation by the addition of virtual sites.
.. warning :: This API is experimental and subject to change.
Examples
--------
Import some utilities
>>> from simtk.openmm import app
>>> from openforcefield.tests.utils import get_data_file_path, get_packmol_pdb_file_path
>>> pdb_filepath = get_packmol_pdb_file_path('cyclohexane_ethanol_0.4_0.6')
>>> monomer_names = ('cyclohexane', 'ethanol')
Create a Topology object from a PDB file and sdf files defining the molecular contents
>>> from openforcefield.topology import Molecule, Topology
>>> pdbfile = app.PDBFile(pdb_filepath)
>>> sdf_filepaths = [get_data_file_path(f'systems/monomers/{name}.sdf') for name in monomer_names]
>>> unique_molecules = [Molecule.from_file(sdf_filepath) for sdf_filepath in sdf_filepaths]
>>> topology = Topology.from_openmm(pdbfile.topology, unique_molecules=unique_molecules)
Create a Topology object from a PDB file and IUPAC names of the molecular contents
>>> pdbfile = app.PDBFile(pdb_filepath)
>>> unique_molecules = [Molecule.from_iupac(name) for name in monomer_names]
>>> topology = Topology.from_openmm(pdbfile.topology, unique_molecules=unique_molecules)
Create an empty Topology object and add a few copies of a single benzene molecule
>>> topology = Topology()
>>> molecule = Molecule.from_iupac('benzene')
>>> molecule_topology_indices = [topology.add_molecule(molecule) for index in range(10)]
"""
[docs] def __init__(self, other=None):
"""
Create a new Topology.
Parameters
----------
other : optional, default=None
If specified, attempt to construct a copy of the Topology from the specified object.
This might be a Topology object, or a file that can be used to construct a Topology object
or serialized Topology object.
"""
from openforcefield.topology.molecule import FrozenMolecule
# Assign cheminformatics models
model = DEFAULT_AROMATICITY_MODEL
self._aromaticity_model = model
# self._fractional_bond_order_model = DEFAULT_FRACTIONAL_BOND_ORDER_MODEL
# self._charge_model = DEFAULT_CHARGE_MODEL
# Initialize storage
self._initialize()
# TODO: Try to construct Topology copy from `other` if specified
if isinstance(other, Topology):
self.copy_initializer(other)
elif isinstance(other, FrozenMolecule):
self.from_molecules([other])
elif isinstance(other, OrderedDict):
self._initialize_from_dict(other)
def _initialize(self):
"""
Initializes a blank Topology.
"""
self._aromaticity_model = DEFAULT_AROMATICITY_MODEL
self._constrained_atom_pairs = dict()
self._box_vectors = None
# self._is_periodic = False
# self._reference_molecule_dicts = set()
# TODO: Look into weakref and what it does. Having multiple topologies might cause a memory leak.
self._reference_molecule_to_topology_molecules = OrderedDict()
self._topology_molecules = list()
@property
def reference_molecules(self):
"""
Get an iterator of reference molecules in this Topology.
Returns
-------
iterable of openforcefield.topology.Molecule
"""
for ref_mol in self._reference_molecule_to_topology_molecules.keys():
yield ref_mol
[docs] @classmethod
def from_molecules(cls, molecules):
"""
Create a new Topology object containing one copy of each of the specified molecule(s).
Parameters
----------
molecules : Molecule or iterable of Molecules
One or more molecules to be added to the Topology
Returns
-------
topology : Topology
The Topology created from the specified molecule(s)
"""
# Ensure that we are working with an iterable
try:
iter(molecules)
except TypeError as te:
# Make iterable object
molecules = [molecules]
# Create Topology and populate it with specified molecules
topology = cls()
for molecule in molecules:
topology.add_molecule(molecule)
return topology
[docs] def assert_bonded(self, atom1, atom2):
"""
Raise an exception if the specified atoms are not bonded in the topology.
Parameters
----------
atom1, atom2 : openforcefield.topology.Atom or int
The atoms or atom topology indices to check to ensure they are bonded
"""
if (type(atom1) is int) and (type(atom2) is int):
atom1 = self.atom(atom1)
atom2 = self.atom(atom2)
# else:
if not (self.is_bonded(atom1, atom2)):
# TODO: Raise more specific exception.
raise Exception(
"Atoms {} and {} are not bonded in topology".format(atom1, atom2)
)
@property
def aromaticity_model(self):
"""
Get the aromaticity model applied to all molecules in the topology.
Returns
-------
aromaticity_model : str
Aromaticity model in use.
"""
return self._aromaticity_model
@aromaticity_model.setter
def aromaticity_model(self, aromaticity_model):
"""
Set the aromaticity model applied to all molecules in the topology.
Parameters
----------
aromaticity_model : str
Aromaticity model to use. One of: ['OEAroModel_MDL']
"""
if not aromaticity_model in ALLOWED_AROMATICITY_MODELS:
msg = "Aromaticity model must be one of {}; specified '{}'".format(
ALLOWED_AROMATICITY_MODELS, aromaticity_model
)
raise ValueError(msg)
self._aromaticity_model = aromaticity_model
@property
def box_vectors(self):
"""Return the box vectors of the topology, if specified
Returns
-------
box_vectors : simtk.unit.Quantity wrapped numpy array of shape (3, 3)
The unit-wrapped box vectors of this topology
"""
return self._box_vectors
@box_vectors.setter
def box_vectors(self, box_vectors):
"""
Sets the box vectors to be used for this topology.
Parameters
----------
box_vectors : simtk.unit.Quantity wrapped numpy array of shape (3, 3)
The unit-wrapped box vectors
"""
if box_vectors is None:
self._box_vectors = None
return
if not hasattr(box_vectors, "unit"):
raise InvalidBoxVectorsError("Given unitless box vectors")
if not (unit.angstrom.is_compatible(box_vectors.unit)):
raise InvalidBoxVectorsError(
"Attempting to set box vectors in units that are incompatible with simtk.unit.Angstrom"
)
if hasattr(box_vectors, "shape"):
if box_vectors.shape == (3,):
box_vectors *= np.eye(3)
if box_vectors.shape != (3, 3):
raise InvalidBoxVectorsError(
f"Box vectors must be shape (3, 3). Found shape {box_vectors.shape}"
)
else:
assert len(box_vectors) == 3
self._box_vectors = box_vectors
@property
def charge_model(self):
"""
Get the partial charge model applied to all molecules in the topology.
Returns
-------
charge_model : str
Charge model used for all molecules in the Topology.
"""
return self._charge_model
@charge_model.setter
def charge_model(self, charge_model):
"""
Set the partial charge model used for all molecules in the topology.
Parameters
----------
charge_model : str
Charge model to use for all molecules in the Topology.
Allowed values: ['AM1-BCC']
* ``AM1-BCC``: Canonical AM1-BCC scheme
"""
if not charge_model in ALLOWED_CHARGE_MODELS:
raise ValueError(
"Charge model must be one of {}; specified '{}'".format(
ALLOWED_CHARGE_MODELS, charge_model
)
)
self._charge_model = charge_model
@property
def constrained_atom_pairs(self):
"""Returns the constrained atom pairs of the Topology
Returns
-------
constrained_atom_pairs : dict
dictionary of the form d[(atom1_topology_index, atom2_topology_index)] = distance (float)
"""
return self._constrained_atom_pairs
@property
def fractional_bond_order_model(self):
"""
Get the fractional bond order model for the Topology.
Returns
-------
fractional_bond_order_model : str
Fractional bond order model in use.
"""
return self._fractional_bond_order_model
@fractional_bond_order_model.setter
def fractional_bond_order_model(self, fractional_bond_order_model):
"""
Set the fractional bond order model applied to all molecules in the topology.
Parameters
----------
fractional_bond_order_model : str
Fractional bond order model to use. One of: ['Wiberg']
"""
if not fractional_bond_order_model in ALLOWED_FRACTIONAL_BOND_ORDER_MODELS:
raise ValueError(
"Fractional bond order model must be one of {}; specified '{}'".format(
ALLOWED_FRACTIONAL_BOND_ORDER_MODELS, fractional_bond_order_model
)
)
self._fractional_bond_order_model = fractional_bond_order_model
@property
def n_reference_molecules(self):
"""
Returns the number of reference (unique) molecules in in this Topology.
Returns
-------
n_reference_molecules : int
"""
count = 0
for i in self.reference_molecules:
count += 1
return count
@property
def n_topology_molecules(self):
"""
Returns the number of topology molecules in in this Topology.
Returns
-------
n_topology_molecules : int
"""
return len(self._topology_molecules)
@property
def topology_molecules(self):
"""Returns an iterator over all the TopologyMolecules in this Topology
Returns
-------
topology_molecules : Iterable of TopologyMolecule
"""
return self._topology_molecules
@property
def n_topology_atoms(self):
"""
Returns the number of topology atoms in in this Topology.
Returns
-------
n_topology_atoms : int
"""
n_atoms = 0
for reference_molecule in self.reference_molecules:
n_atoms_per_topology_molecule = reference_molecule.n_atoms
n_instances_of_topology_molecule = len(
self._reference_molecule_to_topology_molecules[reference_molecule]
)
n_atoms += n_atoms_per_topology_molecule * n_instances_of_topology_molecule
return n_atoms
@property
def topology_atoms(self):
"""Returns an iterator over the atoms in this Topology. These will be in ascending order of topology index (Note
that this is not necessarily the same as the reference molecule index)
Returns
-------
topology_atoms : Iterable of TopologyAtom
"""
for topology_molecule in self._topology_molecules:
for atom in topology_molecule.atoms:
yield atom
@property
def n_topology_bonds(self):
"""
Returns the number of TopologyBonds in in this Topology.
Returns
-------
n_bonds : int
"""
n_bonds = 0
for reference_molecule in self.reference_molecules:
n_bonds_per_topology_molecule = reference_molecule.n_bonds
n_instances_of_topology_molecule = len(
self._reference_molecule_to_topology_molecules[reference_molecule]
)
n_bonds += n_bonds_per_topology_molecule * n_instances_of_topology_molecule
return n_bonds
@property
def topology_bonds(self):
"""Returns an iterator over the bonds in this Topology
Returns
-------
topology_bonds : Iterable of TopologyBond
"""
for topology_molecule in self._topology_molecules:
for bond in topology_molecule.bonds:
yield bond
@property
def n_topology_particles(self):
"""
Returns the number of topology particles (TopologyAtoms and TopologyVirtualSites) in in this Topology.
Returns
-------
n_topology_particles : int
"""
n_particles = 0
for reference_molecule in self.reference_molecules:
n_particles_per_topology_molecule = reference_molecule.n_particles
n_instances_of_topology_molecule = len(
self._reference_molecule_to_topology_molecules[reference_molecule]
)
n_particles += (
n_particles_per_topology_molecule * n_instances_of_topology_molecule
)
return n_particles
@property
def topology_particles(self):
"""Returns an iterator over the particles (TopologyAtoms and TopologyVirtualSites) in this Topology. The
TopologyAtoms will be in order of ascending Topology index (Note that this may differ from the
order of atoms in the reference molecule index).
Returns
--------
topology_particles : Iterable of TopologyAtom and TopologyVirtualSite
"""
for topology_molecule in self._topology_molecules:
for atom in topology_molecule.atoms:
yield atom
for topology_molecule in self._topology_molecules:
for vs in topology_molecule.virtual_sites:
for vp in vs.particles:
yield vp
@property
def n_topology_virtual_sites(self):
"""
Returns the number of TopologyVirtualSites in in this Topology.
Returns
-------
n_virtual_sites : iterable of TopologyVirtualSites
"""
n_virtual_sites = 0
for reference_molecule in self.reference_molecules:
n_virtual_sites_per_topology_molecule = reference_molecule.n_virtual_sites
n_instances_of_topology_molecule = len(
self._reference_molecule_to_topology_molecules[reference_molecule]
)
n_virtual_sites += (
n_virtual_sites_per_topology_molecule * n_instances_of_topology_molecule
)
return n_virtual_sites
@property
def topology_virtual_sites(self):
"""Get an iterator over the virtual sites in this Topology
Returns
-------
topology_virtual_sites : Iterable of TopologyVirtualSite
"""
for topology_molecule in self._topology_molecules:
for virtual_site in topology_molecule.virtual_sites:
yield virtual_site
@property
def n_angles(self):
"""int: number of angles in this Topology."""
return sum(mol.n_angles for mol in self._topology_molecules)
@property
def angles(self):
"""Iterable of Tuple[TopologyAtom]: iterator over the angles in this Topology."""
for topology_molecule in self._topology_molecules:
for angle in topology_molecule.angles:
yield angle
@property
def n_propers(self):
"""int: number of proper torsions in this Topology."""
return sum(mol.n_propers for mol in self._topology_molecules)
@property
def propers(self):
"""Iterable of Tuple[TopologyAtom]: iterator over the proper torsions in this Topology."""
for topology_molecule in self._topology_molecules:
for proper in topology_molecule.propers:
yield proper
@property
def n_impropers(self):
"""int: number of improper torsions in this Topology."""
return sum(mol.n_impropers for mol in self._topology_molecules)
@property
def impropers(self):
"""Iterable of Tuple[TopologyAtom]: iterator over the improper torsions in this Topology."""
for topology_molecule in self._topology_molecules:
for improper in topology_molecule.impropers:
yield improper
class _ChemicalEnvironmentMatch:
"""Represents the match of a given chemical environment query, storing
both the matched topology atom indices and the indices of the corresponding
reference molecule atoms, as well as a reference to the reference molecule.
"""
@property
def reference_atom_indices(self):
"""tuple of int: The indices of the corresponding reference molecule atoms."""
return self._reference_atom_indices
@property
def reference_molecule(self):
"""topology.molecule.Molecule: The corresponding reference molecule."""
return self._reference_molecule
@property
def topology_atom_indices(self):
"""tuple of int: The matched topology atom indices."""
return self._topology_atom_indices
def __init__(
self, reference_atom_indices, reference_molecule, topology_atom_indices
):
"""Constructs a new _ChemicalEnvironmentMatch object
Parameters
----------
reference_atom_indices: tuple of int
The indices of the corresponding reference molecule atoms.
reference_molecule: topology.molecule.Molecule
The corresponding reference molecule.
topology_atom_indices: tuple of int
The matched topology atom indices.
"""
assert len(reference_atom_indices) == len(topology_atom_indices)
self._reference_atom_indices = reference_atom_indices
self._reference_molecule = reference_molecule
self._topology_atom_indices = topology_atom_indices
[docs] def chemical_environment_matches(
self, query, aromaticity_model="MDL", toolkit_registry=GLOBAL_TOOLKIT_REGISTRY
):
"""
Retrieve all matches for a given chemical environment query.
TODO:
* Do we want to generalize this to other kinds of queries too, like mdtraj DSL, pymol selections, atom index slices, etc?
We could just call it topology.matches(query)
Parameters
----------
query : str or ChemicalEnvironment
SMARTS string (with one or more tagged atoms) or ``ChemicalEnvironment`` query
Query will internally be resolved to SMARTS using ``query.as_smarts()`` if it has an ``.as_smarts`` method.
aromaticity_model : str
Override the default aromaticity model for this topology and use the specified aromaticity model instead.
Allowed values: ['MDL']
Returns
-------
matches : list of Topology._ChemicalEnvironmentMatch
A list of tuples, containing the topology indices of the matching atoms.
"""
# Render the query to a SMARTS string
if type(query) is str:
smarts = query
elif type(query) is ChemicalEnvironment:
smarts = query.as_smarts()
else:
raise ValueError(
f"Don't know how to convert query '{query}' into SMARTS string"
)
# Perform matching on each unique molecule, unrolling the matches to all matching copies
# of that molecule in the Topology object.
matches = list()
for ref_mol in self.reference_molecules:
# Find all atomsets that match this definition in the reference molecule
# This will automatically attempt to match chemically identical atoms in
# a canonical order within the Topology
ref_mol_matches = ref_mol.chemical_environment_matches(
smarts, toolkit_registry=toolkit_registry
)
if len(ref_mol_matches) == 0:
continue
# Unroll corresponding atom indices over all instances of this molecule.
for topology_molecule in self._reference_molecule_to_topology_molecules[
ref_mol
]:
# topology_molecule_start_index = topology_molecule.atom_start_topology_index
# Loop over matches
for reference_match in ref_mol_matches:
# Collect indices of matching TopologyAtoms.
topology_atom_indices = []
for reference_molecule_atom_index in reference_match:
reference_atom = topology_molecule.reference_molecule.atoms[
reference_molecule_atom_index
]
topology_atom = TopologyAtom(reference_atom, topology_molecule)
topology_atom_indices.append(
topology_atom.topology_particle_index
)
environment_match = Topology._ChemicalEnvironmentMatch(
tuple(reference_match), ref_mol, tuple(topology_atom_indices)
)
matches.append(environment_match)
return matches
[docs] def to_dict(self):
"""Convert to dictionary representation."""
# Implement abstract method Serializable.to_dict()
raise NotImplementedError() # TODO
[docs] @classmethod
def from_dict(cls, d):
"""Static constructor from dictionary representation."""
# Implement abstract method Serializable.to_dict()
raise NotImplementedError() # TODO
# TODO: Merge this into Molecule.from_networkx if/when we implement that.
# TODO: can we now remove this as we have the ability to do this in the Molecule class?
@staticmethod
def _networkx_to_hill_formula(mol_graph):
"""
Convert a networkX representation of a molecule to a molecule formula. Used in printing out
informative error messages when a molecule from an openmm topology can't be matched.
Parameters
----------
mol_graph : a networkX graph
The graph representation of a molecule
Returns
-------
formula : str
The molecular formula of the graph molecule
"""
from simtk.openmm.app import Element
# Make a flat list of all atomic numbers in the molecule
atom_nums = []
for idx in mol_graph.nodes:
atom_nums.append(mol_graph.nodes[idx]["atomic_number"])
# Count the number of instances of each atomic number
at_num_to_counts = dict([(unq, atom_nums.count(unq)) for unq in atom_nums])
symbol_to_counts = {}
# Check for C and H first, to make a correct hill formula (remember dicts in python 3.6+ are ordered)
if 6 in at_num_to_counts:
symbol_to_counts["C"] = at_num_to_counts[6]
del at_num_to_counts[6]
if 1 in at_num_to_counts:
symbol_to_counts["H"] = at_num_to_counts[1]
del at_num_to_counts[1]
# Now count instances of all elements other than C and H, in order of ascending atomic number
sorted_atom_nums = sorted(at_num_to_counts.keys())
for atom_num in sorted_atom_nums:
symbol_to_counts[
Element.getByAtomicNumber(atom_num).symbol
] = at_num_to_counts[atom_num]
# Finally format the formula as string
formula = ""
for ele, count in symbol_to_counts.items():
formula += f"{ele}{count}"
return formula
[docs] @classmethod
def from_openmm(cls, openmm_topology, unique_molecules=None):
"""
Construct an openforcefield Topology object from an OpenMM Topology object.
Parameters
----------
openmm_topology : simtk.openmm.app.Topology
An OpenMM Topology object
unique_molecules : iterable of objects that can be used to construct unique Molecule objects
All unique molecules must be provided, in any order, though multiple copies of each molecule are allowed.
The atomic elements and bond connectivity will be used to match the reference molecules
to molecule graphs appearing in the OpenMM ``Topology``. If bond orders are present in the
OpenMM ``Topology``, these will be used in matching as well.
If all bonds have bond orders assigned in ``mdtraj_topology``, these bond orders will be used to attempt to construct
the list of unique Molecules if the ``unique_molecules`` argument is omitted.
Returns
-------
topology : openforcefield.topology.Topology
An openforcefield Topology object
"""
import networkx as nx
from openforcefield.topology.molecule import Molecule
# Check to see if the openMM system has defined bond orders, by looping over all Bonds in the Topology.
omm_has_bond_orders = True
for omm_bond in openmm_topology.bonds():
if omm_bond.order is None:
omm_has_bond_orders = False
# Convert all unique mols to graphs
topology = cls()
graph_to_unq_mol = {}
for unq_mol in unique_molecules:
unq_mol_graph = unq_mol.to_networkx()
for existing_graph in graph_to_unq_mol.keys():
if Molecule.are_isomorphic(
existing_graph,
unq_mol_graph,
return_atom_map=False,
aromatic_matching=False,
formal_charge_matching=False,
bond_order_matching=omm_has_bond_orders,
atom_stereochemistry_matching=False,
bond_stereochemistry_matching=False,
)[0]:
msg = (
"Error: Two unique molecules have indistinguishable "
"graphs: {} and {}".format(
unq_mol, graph_to_unq_mol[existing_graph]
)
)
raise DuplicateUniqueMoleculeError(msg)
graph_to_unq_mol[unq_mol_graph] = unq_mol
# Convert all openMM mols to graphs
omm_topology_G = nx.Graph()
for atom in openmm_topology.atoms():
omm_topology_G.add_node(
atom.index, atomic_number=atom.element.atomic_number
)
for bond in openmm_topology.bonds():
omm_topology_G.add_edge(
bond.atom1.index, bond.atom2.index, bond_order=bond.order
)
# For each connected subgraph (molecule) in the topology, find its match in unique_molecules
topology_molecules_to_add = list()
for omm_mol_G in (
omm_topology_G.subgraph(c).copy()
for c in nx.connected_components(omm_topology_G)
):
match_found = False
for unq_mol_G in graph_to_unq_mol.keys():
isomorphic, mapping = Molecule.are_isomorphic(
omm_mol_G,
unq_mol_G,
return_atom_map=True,
aromatic_matching=False,
formal_charge_matching=False,
bond_order_matching=omm_has_bond_orders,
atom_stereochemistry_matching=False,
bond_stereochemistry_matching=False,
)
if isomorphic:
# Take the first valid atom indexing map
first_topology_atom_index = min(mapping.keys())
topology_molecules_to_add.append(
(first_topology_atom_index, unq_mol_G, mapping.items())
)
match_found = True
break
if match_found is False:
hill_formula = Molecule.to_hill_formula(omm_mol_G)
msg = f"No match found for molecule {hill_formula}. "
probably_missing_conect = [
"C",
"H",
"O",
"N",
"P",
"S",
"F",
"Cl",
"Br",
]
if hill_formula in probably_missing_conect:
msg += (
"This would be a very unusual molecule to try and parameterize, "
"and it is likely that the data source it was read from does not "
"contain connectivity information. If this molecule is coming from "
"PDB, please ensure that the file contains CONECT records. The PDB "
"format documentation (https://www.wwpdb.org/documentation/"
'file-format-content/format33/sect10.html) states "CONECT records '
"are mandatory for HET groups (excluding water) and for other bonds "
'not specified in the standard residue connectivity table."'
)
raise ValueError(msg)
# The connected_component_subgraph function above may have scrambled the molecule order, so sort molecules
# by their first atom's topology index
topology_molecules_to_add.sort(key=lambda x: x[0])
for first_index, unq_mol_G, top_to_ref_index in topology_molecules_to_add:
local_top_to_ref_index = dict(
[
(top_index - first_index, ref_index)
for top_index, ref_index in top_to_ref_index
]
)
topology.add_molecule(
graph_to_unq_mol[unq_mol_G],
local_topology_to_reference_index=local_top_to_ref_index,
)
topology.box_vectors = openmm_topology.getPeriodicBoxVectors()
# TODO: How can we preserve metadata from the openMM topology when creating the OFF topology?
return topology
[docs] def to_openmm(self, ensure_unique_atom_names=True):
"""
Create an OpenMM Topology object.
The OpenMM ``Topology`` object will have one residue per topology
molecule. Currently, the number of chains depends on how many copies
of the same molecule are in the ``Topology``. Molecules with more
than 5 copies are all assigned to a single chain, otherwise one
chain is created for each molecule. This behavior may change in
the future.
Parameters
----------
ensure_unique_atom_names : bool, optional. Default=True
Whether to check that the molecules in each molecule have
unique atom names, and regenerate them if not. Note that this
looks only at molecules, and does not guarantee uniqueness in
the entire Topology.
Returns
-------
openmm_topology : simtk.openmm.app.Topology
An OpenMM Topology object
"""
from simtk.openmm.app import Aromatic, Double, Single
from simtk.openmm.app import Topology as OMMTopology
from simtk.openmm.app import Triple
from simtk.openmm.app.element import Element as OMMElement
omm_topology = OMMTopology()
# Create unique atom names
if ensure_unique_atom_names:
for ref_mol in self.reference_molecules:
if not ref_mol.has_unique_atom_names:
ref_mol.generate_unique_atom_names()
# Keep track of which chains and residues have been added.
mol_to_chains = {}
mol_to_residues = {}
# Go through atoms in OpenFF to preserve the order.
omm_atoms = []
# We need to iterate over the topology molecules if we want to
# keep track of chains/residues as Atom.topology_molecule is
# instantiated every time and can't be used as a key.
for topology_molecule in self.topology_molecules:
for atom in topology_molecule.atoms:
reference_molecule = topology_molecule.reference_molecule
n_molecules = len(
self._reference_molecule_to_topology_molecules[reference_molecule]
)
# Add 1 chain per molecule unless there are more than 5 copies,
# in which case we add a single chain for all of them.
if n_molecules <= 5:
# We associate a chain to each molecule.
key_molecule = topology_molecule
else:
# We associate a chain to all the topology molecule.
key_molecule = reference_molecule
# Create a new chain if it doesn't exit.
try:
chain = mol_to_chains[key_molecule]
except KeyError:
chain = omm_topology.addChain()
mol_to_chains[key_molecule] = chain
# Add one molecule for each topology molecule.
try:
residue = mol_to_residues[topology_molecule]
except KeyError:
residue = omm_topology.addResidue(reference_molecule.name, chain)
mol_to_residues[topology_molecule] = residue
# Add atom.
element = OMMElement.getByAtomicNumber(atom.atomic_number)
omm_atom = omm_topology.addAtom(atom.atom.name, element, residue)
# Make sure that OpenFF and OpenMM Topology atoms have the same indices.
assert atom.topology_atom_index == int(omm_atom.id) - 1
omm_atoms.append(omm_atom)
# Add all bonds.
bond_types = {1: Single, 2: Double, 3: Triple}
for bond in self.topology_bonds:
atom1, atom2 = bond.atoms
atom1_idx, atom2_idx = atom1.topology_atom_index, atom2.topology_atom_index
bond_type = (
Aromatic if bond.bond.is_aromatic else bond_types[bond.bond_order]
)
omm_topology.addBond(
omm_atoms[atom1_idx],
omm_atoms[atom2_idx],
type=bond_type,
order=bond.bond_order,
)
if self.box_vectors is not None:
omm_topology.setPeriodicBoxVectors(self.box_vectors)
return omm_topology
[docs] def to_file(self, filename, positions, file_format="PDB", keepIds=False):
"""
To save a PDB file with coordinates as well as topology from openforcefield topology object
Reference: https://github.com/openforcefield/openforcefield/issues/502
Note: 1. This doesn't handle virtual sites (they're ignored)
2. Atom numbering may not remain same, for example if the atoms in water are numbered as 1001, 1002, 1003,
they would change to 1, 2, 3.
This doesn't affect the topology or coordinates or atom-ordering in anyway
3. Same issue with the amino acid names in the pdb file, they are not returned
Parameters
----------
filename : str
name of the pdb file to write to
positions : n_atoms x 3 numpy array or simtk.unit.Quantity-wrapped n_atoms x 3 iterable
Can be an openmm 'quantity' object which has atomic positions as a list of Vec3s along with associated units, otherwise a 3D array of UNITLESS numbers are considered as "Angstroms" by default
file_format : str
Output file format. Case insensitive. Currently only supported value is "pdb".
"""
from simtk.openmm.app import PDBFile
from simtk.unit import Quantity, angstroms
openmm_top = self.to_openmm()
if not isinstance(positions, Quantity):
positions = positions * angstroms
file_format = file_format.upper()
if file_format != "PDB":
raise NotImplementedError("Topology.to_file supports only PDB format")
# writing to PDB file
with open(filename, "w") as outfile:
PDBFile.writeFile(openmm_top, positions, outfile, keepIds)
[docs] @staticmethod
def from_mdtraj(mdtraj_topology, unique_molecules=None):
"""
Construct an openforcefield Topology object from an MDTraj Topology object.
Parameters
----------
mdtraj_topology : mdtraj.Topology
An MDTraj Topology object
unique_molecules : iterable of objects that can be used to construct unique Molecule objects
All unique molecules mult be provided, in any order, though multiple copies of each molecule are allowed.
The atomic elements and bond connectivity will be used to match the reference molecules
to molecule graphs appearing in the MDTraj ``Topology``. If bond orders are present in the
MDTraj ``Topology``, these will be used in matching as well.
If all bonds have bond orders assigned in ``mdtraj_topology``, these bond orders will be used to attempt to construct
the list of unique Molecules if the ``unique_molecules`` argument is omitted.
Returns
-------
topology : openforcefield.Topology
An openforcefield Topology object
"""
return Topology.from_openmm(
mdtraj_topology.to_openmm(), unique_molecules=unique_molecules
)
# TODO: Jeff prepended an underscore on this before 0.2.0 release to remove it from the API.
# Before exposing this, we should look carefully at the information that is preserved/lost during this
# conversion, and make it clear what would happen to this information in a round trip. For example,
# we should know what would happen to formal and partial bond orders and charges, stereochemistry, and
# multi-conformer information. It will be important to document these risks to users, as all of these
# factors could lead to unintended behavior during system parameterization.
def _to_mdtraj(self):
"""
Create an MDTraj Topology object.
Returns
----------
mdtraj_topology : mdtraj.Topology
An MDTraj Topology object
#"""
import mdtraj as md
return md.Topology.from_openmm(self.to_openmm())
[docs] @staticmethod
def from_parmed(parmed_structure, unique_molecules=None):
"""
.. warning:: This functionality will be implemented in a future toolkit release.
Construct an openforcefield Topology object from a ParmEd Structure object.
Parameters
----------
parmed_structure : parmed.Structure
A ParmEd structure object
unique_molecules : iterable of objects that can be used to construct unique Molecule objects
All unique molecules mult be provided, in any order, though multiple copies of each molecule are allowed.
The atomic elements and bond connectivity will be used to match the reference molecules
to molecule graphs appearing in the structure's ``topology`` object. If bond orders are present in the
structure's ``topology`` object, these will be used in matching as well.
If all bonds have bond orders assigned in the structure's ``topology`` object,
these bond orders will be used to attempt to construct
the list of unique Molecules if the ``unique_molecules`` argument is omitted.
Returns
-------
topology : openforcefield.Topology
An openforcefield Topology object
"""
import parmed
# TODO: Implement functionality
raise NotImplementedError
[docs] def to_parmed(self):
"""
.. warning:: This functionality will be implemented in a future toolkit release.
Create a ParmEd Structure object.
Returns
----------
parmed_structure : parmed.Structure
A ParmEd Structure objecft
"""
import parmed
# TODO: Implement functionality
raise NotImplementedError
# TODO: Jeff prepended an underscore on this before 0.2.0 release to remove it from the API.
# This function is deprecated and expects the OpenEye toolkit. We need to discuss what
# to do with this functionality in light of our move to the ToolkitWrapper architecture.
# Also, as written, this function implies several things about our toolkit's ability to
# handle biopolymers. We need to discuss how much of this functionality we will expose
# and how we can make our toolkit's current scope clear to users..
@staticmethod
def _from_openeye(oemol):
"""
Create a Molecule from an OpenEye molecule.
Requires the OpenEye toolkit to be installed.
Parameters
----------
oemol : openeye.oechem.OEMol
An OpenEye molecule
Returns
-------
molecule : openforcefield.Molecule
An openforcefield molecule
"""
# TODO: Convert this to cls.from_molecules(Molecule.from_openeye())?
# OE Hierarchical molecule view
hv = oechem.OEHierView(
oemol,
oechem.OEAssumption_BondedResidue
+ oechem.OEAssumption_ResPerceived
+ oechem.OEAssumption_PDBOrder,
)
# Create empty OpenMM Topology
topology = app.Topology()
# Dictionary used to map oe atoms to openmm atoms
oe_atom_to_openmm_at = {}
for chain in hv.GetChains():
# TODO: Fail if hv contains more than one molecule.
# Create empty OpenMM Chain
openmm_chain = topology.addChain(chain.GetChainID())
for frag in chain.GetFragments():
for hres in frag.GetResidues():
# Get OE residue
oe_res = hres.GetOEResidue()
# Create OpenMM residue
openmm_res = topology.addResidue(oe_res.GetName(), openmm_chain)
for oe_at in hres.GetAtoms():
# Select atom element based on the atomic number
element = app.element.Element.getByAtomicNumber(
oe_at.GetAtomicNum()
)
# Add atom OpenMM atom to the topology
openmm_at = topology.addAtom(
oe_at.GetName(), element, openmm_res
)
openmm_at.index = oe_at.GetIdx()
# Add atom to the mapping dictionary
oe_atom_to_openmm_at[oe_at] = openmm_at
if topology.getNumAtoms() != mol.NumAtoms():
oechem.OEThrow.Error(
"OpenMM topology and OEMol number of atoms mismatching: "
"OpenMM = {} vs OEMol = {}".format(
topology.getNumAtoms(), mol.NumAtoms()
)
)
# Count the number of bonds in the openmm topology
omm_bond_count = 0
def IsAmideBond(oe_bond):
# TODO: Can this be replaced by a SMARTS query?
# This supporting function checks if the passed bond is an amide bond or not.
# Our definition of amide bond C-N between a Carbon and a Nitrogen atom is:
# O
# ║
# CA or O-C-N-
# |
# The amide bond C-N is a single bond
if oe_bond.GetOrder() != 1:
return False
atomB = oe_bond.GetBgn()
atomE = oe_bond.GetEnd()
# The amide bond is made by Carbon and Nitrogen atoms
if not (
atomB.IsCarbon()
and atomE.IsNitrogen()
or (atomB.IsNitrogen() and atomE.IsCarbon())
):
return False
# Select Carbon and Nitrogen atoms
if atomB.IsCarbon():
C_atom = atomB
N_atom = atomE
else:
C_atom = atomE
N_atom = atomB
# Carbon and Nitrogen atoms must have 3 neighbour atoms
if not (C_atom.GetDegree() == 3 and N_atom.GetDegree() == 3):
return False
double_bonds = 0
single_bonds = 0
for bond in C_atom.GetBonds():
# The C-O bond can be single or double.
if (bond.GetBgn() == C_atom and bond.GetEnd().IsOxygen()) or (
bond.GetBgn().IsOxygen() and bond.GetEnd() == C_atom
):
if bond.GetOrder() == 2:
double_bonds += 1
if bond.GetOrder() == 1:
single_bonds += 1
# The CA-C bond is single
if (bond.GetBgn() == C_atom and bond.GetEnd().IsCarbon()) or (
bond.GetBgn().IsCarbon() and bond.GetEnd() == C_atom
):
if bond.GetOrder() == 1:
single_bonds += 1
# Just one double and one single bonds are connected to C
# In this case the bond is an amide bond
if double_bonds == 1 and single_bonds == 1:
return True
else:
return False
# Creating bonds
for oe_bond in mol.GetBonds():
# Set the bond type
if oe_bond.GetType() is not "":
if oe_bond.GetType() in [
"Single",
"Double",
"Triple",
"Aromatic",
"Amide",
]:
off_bondtype = oe_bond.GetType()
else:
off_bondtype = None
else:
if oe_bond.IsAromatic():
oe_bond.SetType("Aromatic")
off_bondtype = "Aromatic"
elif oe_bond.GetOrder() == 2:
oe_bond.SetType("Double")
off_bondtype = "Double"
elif oe_bond.GetOrder() == 3:
oe_bond.SetType("Triple")
off_bondtype = "Triple"
elif IsAmideBond(oe_bond):
oe_bond.SetType("Amide")
off_bondtype = "Amide"
elif oe_bond.GetOrder() == 1:
oe_bond.SetType("Single")
off_bondtype = "Single"
else:
off_bondtype = None
molecule.add_bond(
oe_atom_to_openmm_at[oe_bond.GetBgn()],
oe_atom_to_openmm_at[oe_bond.GetEnd()],
type=off_bondtype,
order=oe_bond.GetOrder(),
)
if molecule.n_bondsphe != mol.NumBonds():
oechem.OEThrow.Error(
"OpenMM topology and OEMol number of bonds mismatching: "
"OpenMM = {} vs OEMol = {}".format(omm_bond_count, mol.NumBonds())
)
dic = mol.GetCoords()
positions = [Vec3(v[0], v[1], v[2]) for k, v in dic.items()] * unit.angstrom
return topology, positions
# TODO: Jeff prepended an underscore on this before 0.2.0 release to remove it from the API.
# This function is deprecated and expects the OpenEye toolkit. We need to discuss what
# to do with this functionality in light of our move to the ToolkitWrapper architecture.
# It also expects Topology to be organized by chain, which is not currently the case.
# Bringing this function back would require non-trivial engineering and testing, and we
# would want to discuss what "guarantee" of correctness it could offer.
def _to_openeye(self, positions=None, aromaticity_model=DEFAULT_AROMATICITY_MODEL):
"""
Create an OpenEye OEMol from the topology
Requires the OpenEye toolkit to be installed.
Returns
-------
oemol : openeye.oechem.OEMol
An OpenEye molecule
positions : simtk.unit.Quantity with shape [nparticles,3], optional, default=None
Positions to use in constructing OEMol.
If virtual sites are present in the Topology, these indices will be skipped.
NOTE: This comes from https://github.com/oess/oeommtools/blob/master/oeommtools/utils.py
"""
oe_mol = oechem.OEMol()
# Python set used to identify atoms that are not in protein residues
keep = set(proteinResidues).union(dnaResidues).union(rnaResidues)
for chain in topology.chains():
for res in chain.residues():
# Create an OEResidue
oe_res = oechem.OEResidue()
# Set OEResidue name
oe_res.SetName(res.name)
# If the atom is not a protein atom then set its heteroatom
# flag to True
if res.name not in keep:
oe_res.SetFragmentNumber(chain.index + 1)
oe_res.SetHetAtom(True)
# Set OEResidue Chain ID
oe_res.SetChainID(chain.id)
# res_idx = int(res.id) - chain.index * len(chain._residues)
# Set OEResidue number
oe_res.SetResidueNumber(int(res.id))
for openmm_at in res.atoms():
# Create an OEAtom based on the atomic number
oe_atom = oe_mol.NewAtom(openmm_at.element._atomic_number)
# Set atom name
oe_atom.SetName(openmm_at.name)
# Set Symbol
oe_atom.SetType(openmm_at.element.symbol)
# Set Atom index
oe_res.SetSerialNumber(openmm_at.index + 1)
# Commit the changes
oechem.OEAtomSetResidue(oe_atom, oe_res)
# Update the dictionary OpenMM to OE
openmm_atom_to_oe_atom[openmm_at] = oe_atom
if self.n_atoms != oe_mol.NumAtoms():
raise Exception(
"OEMol has an unexpected number of atoms: "
"Molecule has {} atoms, while OEMol has {} atoms".format(
topology.n_atom, oe_mol.NumAtoms()
)
)
# Create bonds
for off_bond in self.topology_bonds():
oe_mol.NewBond(oe_atoms[bond.atom1], oe_atoms[bond.atom2], bond.bond_order)
if off_bond.type:
if off_bond.type == "Aromatic":
oe_atom0.SetAromatic(True)
oe_atom1.SetAromatic(True)
oe_bond.SetAromatic(True)
oe_bond.SetType("Aromatic")
elif off_bond.type in ["Single", "Double", "Triple", "Amide"]:
oe_bond.SetType(omm_bond.type)
else:
oe_bond.SetType("")
if self.n_bonds != oe_mol.NumBonds():
oechem.OEThrow.Erorr(
"OEMol has an unexpected number of bonds:: "
"Molecule has {} bonds, while OEMol has {} bonds".format(
self.n_bond, oe_mol.NumBonds()
)
)
if positions is not None:
# Set the OEMol positions
particle_indices = [
atom.particle_index for atom in self.topology_atoms
] # get particle indices
pos = positions[particle_indices].value_in_units_of(unit.angstrom)
pos = list(itertools.chain.from_iterable(pos))
oe_mol.SetCoords(pos)
oechem.OESetDimensionFromCoords(oe_mol)
return oe_mol
[docs] def get_bond_between(self, i, j):
"""Returns the bond between two atoms
Parameters
----------
i, j : int or TopologyAtom
Atoms or atom indices to check
Returns
-------
bond : TopologyBond
The bond between i and j.
"""
if (type(i) is int) and (type(j) is int):
atomi = self.atom(i)
atomj = self.atom(j)
elif (type(i) is TopologyAtom) and (type(j) is TopologyAtom):
atomi = i
atomj = j
else:
raise Exception(
"Invalid input passed to is_bonded(). Expected ints or TopologyAtoms, "
"got {} and {}".format(i, j)
)
for top_bond in atomi.topology_bonds:
for top_atom in top_bond.atoms:
if top_atom == atomi:
continue
if top_atom == atomj:
return top_bond
raise NotBondedError("No bond between atom {} and {}".format(i, j))
[docs] def is_bonded(self, i, j):
"""Returns True if the two atoms are bonded
Parameters
----------
i, j : int or TopologyAtom
Atoms or atom indices to check
Returns
-------
is_bonded : bool
True if atoms are bonded, False otherwise.
"""
try:
self.get_bond_between(i, j)
return True
except NotBondedError:
return False
[docs] def atom(self, atom_topology_index):
"""
Get the TopologyAtom at a given Topology atom index.
Parameters
----------
atom_topology_index : int
The index of the TopologyAtom in this Topology
Returns
-------
An openforcefield.topology.TopologyAtom
"""
assert type(atom_topology_index) is int
assert 0 <= atom_topology_index < self.n_topology_atoms
this_molecule_start_index = 0
next_molecule_start_index = 0
for topology_molecule in self._topology_molecules:
next_molecule_start_index += topology_molecule.n_atoms
if next_molecule_start_index > atom_topology_index:
atom_molecule_index = atom_topology_index - this_molecule_start_index
# NOTE: the index here should still be in the topology index order, NOT the reference molecule's
return topology_molecule.atom(atom_molecule_index)
this_molecule_start_index += topology_molecule.n_atoms
# Potentially more computationally efficient lookup ( O(largest_molecule_natoms)? )
# start_index_2_top_mol is an ordered dict of [starting_atom_index] --> [topology_molecule]
# search_range = range(atom_topology_index - largest_molecule_natoms, atom_topology_index)
# search_index = atom_topology_index
# while not(search_index in start_index_2_top_mol.keys()): # Only efficient if start_index_2_top_mol.keys() is a set (constant time lookups)
# search_index -= 1
# topology_molecule = start_index_2_top_mol(search_index)
# atom_molecule_index = atom_topology_index - search_index
# return topology_molecule.atom(atom_molecule_index)
[docs] def virtual_site(self, vsite_topology_index):
"""
Get the TopologyAtom at a given Topology atom index.
Parameters
----------
vsite_topology_index : int
The index of the TopologyVirtualSite in this Topology
Returns
-------
An openforcefield.topology.TopologyVirtualSite
"""
assert type(vsite_topology_index) is int
assert 0 <= vsite_topology_index < self.n_topology_virtual_sites
this_molecule_start_index = 0
next_molecule_start_index = 0
for topology_molecule in self._topology_molecules:
next_molecule_start_index += topology_molecule.n_virtual_sites
if next_molecule_start_index > vsite_topology_index:
vsite_molecule_index = vsite_topology_index - this_molecule_start_index
return topology_molecule.virtual_site(vsite_molecule_index)
this_molecule_start_index += topology_molecule.n_virtual_sites
[docs] def bond(self, bond_topology_index):
"""
Get the TopologyBond at a given Topology bond index.
Parameters
----------
bond_topology_index : int
The index of the TopologyBond in this Topology
Returns
-------
An openforcefield.topology.TopologyBond
"""
assert type(bond_topology_index) is int
assert 0 <= bond_topology_index < self.n_topology_bonds
this_molecule_start_index = 0
next_molecule_start_index = 0
for topology_molecule in self._topology_molecules:
next_molecule_start_index += topology_molecule.n_bonds
if next_molecule_start_index > bond_topology_index:
bond_molecule_index = bond_topology_index - this_molecule_start_index
return topology_molecule.bond(bond_molecule_index)
this_molecule_start_index += topology_molecule.n_bonds
[docs] def add_particle(self, particle):
"""Add a Particle to the Topology.
Parameters
----------
particle : Particle
The Particle to be added.
The Topology will take ownership of the Particle.
"""
pass
[docs] def add_molecule(self, molecule, local_topology_to_reference_index=None):
"""Add a Molecule to the Topology. You can optionally request that the atoms be added to the Topology in
a different order than they appear in the Molecule.
Parameters
----------
molecule : Molecule
The Molecule to be added.
local_topology_to_reference_index: dict, optional, default = None
Dictionary of {TopologyMolecule_atom_index : Molecule_atom_index} for the TopologyMolecule that will be
built. If None, this function will add the atoms to the Topology in the order that they appear in the
reference molecule.
Returns
-------
index : int
The index of this molecule in the topology
"""
from openforcefield.topology.molecule import FrozenMolecule, Molecule
if local_topology_to_reference_index is None:
local_topology_to_reference_index = dict(
(i, i) for i in range(molecule.n_atoms)
)
mol_smiles = molecule.to_smiles()
reference_molecule = None
for potential_ref_mol in self._reference_molecule_to_topology_molecules.keys():
if mol_smiles == potential_ref_mol.to_smiles():
# If the molecule is already in the Topology.reference_molecules, add another reference to it in
# Topology.molecules
reference_molecule = potential_ref_mol
# Graph-match this molecule to see if it's in the same order
# Default settings use full matching
_, atom_map = Molecule.are_isomorphic(
molecule, reference_molecule, return_atom_map=True
)
if atom_map is None:
raise Exception(1)
new_mapping = {}
for local_top_idx, ref_idx in local_topology_to_reference_index.items():
new_mapping[local_top_idx] = atom_map[ref_idx]
local_topology_to_reference_index = new_mapping
# raise Exception(local_topology_to_reference_index)
break
if reference_molecule is None:
# If it's a new unique molecule, make and store an immutable copy of it
reference_molecule = FrozenMolecule(molecule)
self._reference_molecule_to_topology_molecules[reference_molecule] = list()
topology_molecule = TopologyMolecule(
reference_molecule, self, local_topology_to_reference_index
)
self._topology_molecules.append(topology_molecule)
self._reference_molecule_to_topology_molecules[reference_molecule].append(
self._topology_molecules[-1]
)
index = len(self._topology_molecules) - 1
return index
[docs] def add_constraint(self, iatom, jatom, distance=True):
"""
Mark a pair of atoms as constrained.
Constraints between atoms that are not bonded (e.g., rigid waters) are permissible.
Parameters
----------
iatom, jatom : Atom
Atoms to mark as constrained
These atoms may be bonded or not in the Topology
distance : simtk.unit.Quantity, optional, default=True
Constraint distance
``True`` if distance has yet to be determined
``False`` if constraint is to be removed
"""
# Check that constraint hasn't already been specified.
if (iatom, jatom) in self._constrained_atom_pairs:
existing_distance = self._constrained_atom_pairs[(iatom, jatom)]
if unit.is_quantity(existing_distance) and (distance is True):
raise Exception(
f"Atoms ({iatom},{jatom}) already constrained with distance {existing_distance} but attempting to override with unspecified distance"
)
if (existing_distance is True) and (distance is True):
raise Exception(
f"Atoms ({iatom},{jatom}) already constrained with unspecified distance but attempting to override with unspecified distance"
)
if distance is False:
del self._constrained_atom_pairs[(iatom, jatom)]
del self._constrained_atom_pairs[(jatom, iatom)]
return
self._constrained_atom_pairs[(iatom, jatom)] = distance
self._constrained_atom_pairs[(jatom, iatom)] = distance
[docs] def is_constrained(self, iatom, jatom):
"""
Check if a pair of atoms are marked as constrained.
Parameters
----------
iatom, jatom : int
Indices of atoms to mark as constrained.
Returns
-------
distance : simtk.unit.Quantity or bool
True if constrained but constraints have not yet been applied
Distance if constraint has already been added to System
"""
if (iatom, jatom) in self._constrained_atom_pairs:
return self._constrained_atom_pairs[(iatom, jatom)]
else:
return False
