def reverse_map_molecule(molecule, target, mapping_moieties):
print('unique')
cg_molecule = clone(molecule) # CG molecule
aa_template = target[molecule.name] # full aa Compound for molecule
aa_moieties = mapping_moieties[
molecule.name] # list of lists of indices for each bead
aa_molecule = Compound() # this will have the final aa molecule
cg_to_aa = [] # list of tuples containing (real index, aa atom)
# now cycle through beads
for index, bead in enumerate(cg_molecule.particles()):
aa_atoms = Compound() # placeholder for molecule atoms
[
aa_atoms.add(clone(aa_template.children[i]))
for i in aa_moieties[index]
]
aa_atoms.translate_to(bead.pos) # shift to cg_bead position
cg_to_aa += list(zip(aa_moieties[index], aa_atoms.children))
# sort atoms in cg_to_aa and add them to the aa_molecule
cg_to_aa = sorted(cg_to_aa)
for atom in cg_to_aa:
aa_molecule.add(clone(atom[1]))
# add bonds from the template
aa_template = aa_template.to_trajectory()
for i, j in aa_template.top.bonds:
aa_molecule.add_bond([aa_molecule[i.index], aa_molecule[j.index]])
# equilibrate molecule and shift back to center
# if the atom names match OpenBabel forcefield naming convention:
try:
aa_molecule.energy_minimization(steps=2500)
# otherwise rename with just element names:
except:
atomnames = [i.name for i in aa_molecule] # get the atomnames
for atom in aa_molecule: # make the atomnames elements
atom.name = atom.name[0]
aa_molecule.energy_minimization(steps=2500)
for i, atom in enumerate(atomnames):
aa_molecule[i].name = atomnames[i]
#aa_molecule.translate(center)
aa_molecule.name = molecule.name
return aa_molecule
def _clone(self, clone_of=None, root_container=None):
"""A faster alternative to deepcopying.
Does not resolve circular dependencies. This should be safe provided
you never try to add the top of a Compound hierarchy to a
sub-Compound. Clones compound hierarchy only, not the bonds.
"""
if root_container is None:
root_container = self
if clone_of is None:
clone_of = dict()
# If this compound has already been cloned, return that.
if self in clone_of:
return clone_of[self]
# Otherwise we make a new clone.
cls = self.__class__
newone = cls.__new__(cls)
# Remember that we're cloning the new one of self.
clone_of[self] = newone
newone.name = deepcopy(self.name)
newone.wrapped = clone(self.wrapped)
if hasattr(self, 'index'):
newone.index = deepcopy(self.index)
if self.children is None:
newone.children = None
else:
newone.children = OrderedSet()
# Parent should be None initially.
newone.parent = None
newone.labels = OrderedDict()
newone.referrers = set()
newone.bond_graph = None
# Add children to clone.
if self.children:
for child in self.children:
newchild = child._clone(clone_of, root_container)
newone.children.add(newchild)
newchild.parent = newone
# Copy labels, except bonds with atoms outside the hierarchy.
if self.labels:
for label, compound in self.labels.items():
if not isinstance(compound, list):
newone.labels[label] = compound._clone(
clone_of, root_container)
compound.referrers.add(clone_of[compound])
else:
# compound is a list of compounds, so we create an empty
# list, and add the clones of the original list elements.
newone.labels[label] = []
for subpart in compound:
newone.labels[label].append(
subpart._clone(clone_of, root_container))
# Referrers must have been handled already, or the will
# be handled
return newone
def reverse_map_solvent(cg_molecule,
target,
sol_per_bead=4,
cutoff=2,
scaling_factor=5):
"""
molecules: list of water beads
target: single atomistic solvent molecule
sol_per_bead: number of atomistic solvent molecules per CG bead
cutoff: max distance an atomistic molecule can be placed from the
center of the CG bead
"""
solvent = Compound() # will contain all the solvent molecules in a bead
solvent_molecule = Compound() # placeholder for each single molecule
# for each atomistic molcule
print("unique")
for i in range(sol_per_bead):
# get a random vector by which to shift the atomistic molecule
"""
randx = cutoff * (1 - 2 * np.random.rand())
randy = np.sqrt(cutoff**2 - randx**2) * (1 - 2 * np.random.rand()) # randy bobandy
randz = np.sqrt(cutoff**2 - randx**2 - randy**2) * (1 - 2 * np.random.rand())
"""
randx = 0.0
randy = 0.0
randz = 0.0
if i == 0:
randx += 1.0
elif i == 1:
randx -= 1.0
elif i == 2:
randy += 1.0
elif i == 3:
randy -= 1.0
shift_vec = np.array([randx, randy, randz])
shift_vec *= 0.2
#np.random.shuffle(shift_vec)
# get random angles to spin the solvent molecule by
theta = 2 * np.pi * np.random.rand()
phi = np.pi * np.random.rand()
# make a solvent molecule compound and shift it to the correct position
solvent_molecule = clone(target)
solvent_molecule.translate_to(cg_molecule.pos + shift_vec)
solvent_molecule.spin(theta, [0, 0, 1])
solvent_molecule.spin(phi, [1, 0, 0])
# add the molecule to the bead compound
solvent.add(solvent_molecule)
# time to minimize the energy!
# try with current atom names
"""
try:
solvent.energy_minimization(steps=500)
# otherwise rename with just element names:
except:
atomnames = [i.name for i in solvent] # get the atomnames
for atom in solvent: # make the atomnames elements
atom.name=atom.name[0]
solvent.energy_minimization(steps=500)
for i, atom in enumerate(atomnames):
solvent[i].name = atomnames[i]
"""
# scale the solvent by 5
# get a list of individual molecules (so that it separates them into residues)
solvent = [clone(child) for child in solvent.children]
for i, solvent_compound in enumerate(solvent):
solvent[i].name = cg_molecule.name
solvent[i].translate_to(np.array(solvent[i].pos) * scaling_factor)
return solvent