def _makeUniverse(self):
from MMTK.Proteins import Protein, PeptideChain
from MMTK.ForceFields import CalphaForceField
self.universe = self.raw_trajectory.universe
self.proteins = self.universe.objectList(Protein)
universe_calpha = MMTK.InfiniteUniverse(CalphaForceField(2.5))
calpha_map = {}
for protein in self.proteins:
chains_calpha = []
for chain in protein:
chains_calpha.append(
PeptideChain(chain.sequence(), model='calpha'))
protein_calpha = Protein(chains_calpha)
universe_calpha.addObject(protein_calpha)
for i in range(len(protein)):
chain = protein[i]
chain_calpha = protein_calpha[i]
for j in range(len(chain)):
calpha_map[chain[j].peptide.C_alpha] = \
chain_calpha[j].peptide.C_alpha
chain_calpha[j].peptide.C_alpha.setMass(1.)
conf = self.raw_trajectory[0]
for atom, calpha in calpha_map.items():
calpha.setPosition(conf[atom])
self.universe_calpha = universe_calpha
universe_calpha.configuration()
self.map = universe_calpha.numberOfAtoms() * [None]
for atom, calpha in calpha_map.items():
self.map[calpha.index] = atom.index
def retrievePeptideChain(self, sequence, mol_system_chain):
from MMTK.Proteins import PeptideChain, Residue
chain = PeptideChain(None)
n_terminus = \
mol_system_chain.residues[0].molResidue.chemCompVar.linking == "start"
c_terminus = \
mol_system_chain.residues[-1].molResidue.chemCompVar.linking == "end"
chain.version_spec = {
'n_terminus': n_terminus,
'c_terminus': c_terminus,
'model': 'all',
'circular': False
}
numbers = [r.seqId for r in mol_system_chain.residues]
chain.groups = []
n = 0
for residue, number in zip(sequence, numbers):
n = n + 1
r = Residue(residue, 'all')
r.name = r.symbol + str(number)
r.sequence_number = n
r.parent = chain
chain.groups.append(r)
chain._setupChain(False, {}, None)
return chain
def retrievePeptideChain(self, sequence, mol_system_chain):
from MMTK.Proteins import PeptideChain, Residue
chain = PeptideChain(None)
n_terminus = \
mol_system_chain.residues[0].molResidue.chemCompVar.linking == "start"
c_terminus = \
mol_system_chain.residues[-1].molResidue.chemCompVar.linking == "end"
chain.version_spec = {'n_terminus': n_terminus,
'c_terminus': c_terminus,
'model': 'all',
'circular': False}
numbers = [r.seqId for r in mol_system_chain.residues]
chain.groups = []
n = 0
for residue, number in zip(sequence, numbers):
n = n + 1
r = Residue(residue, 'all')
r.name = r.symbol + str(number)
r.sequence_number = n
r.parent = chain
chain.groups.append(r)
chain._setupChain(False, {}, None)
return chain
# The first file contains a monomer, the second one a tetramer in # which each chain is almost identical to the monomer from the first # file. We have to cut off the last (incomplete) residue from the # monomer and the last three residues of each chain of the tetramers # to get matching sequences. We'll just deal with one of the chains of # the tetramer here. monomer = configuration1.peptide_chains[0] monomer.removeResidues(-1, None) tetramer_1 = configuration2.peptide_chains[0] tetramer_1.removeResidues(-3, None) # Next we build a PeptideChain for the monomer. We use a C-alpha # model, which is sufficient for the purpose of this script. chain = PeptideChain(monomer, model='calpha') # How big is this beast? For a quick guess, print the size of the smallest # rectangular box containing it: p1, p2 = chain.boundingBox() print "Size of a bounding box: %4.2f x %4.2f x %4.2f nm" % tuple(p2-p1) # Formalities: we define a universe and put the chain inside. # Then we make a copy of the configuration of the universe for later use. # This is necessary because configurations are defined only for # universes (for various good reasons...). universe = InfiniteUniverse() universe.addObject(chain) monomer_configuration = copy(universe.configuration())
# The first file contains a monomer, the second one a tetramer in
# which each chain is almost identical to the monomer from the first
# file. We have to cut off the last (incomplete) residue from the
# monomer and the last three residues of each chain of the tetramers
# to get matching sequences. We'll just deal with one of the chains of
# the tetramer here.
monomer = configuration1.peptide_chains[0]
monomer.removeResidues(-1, None)
tetramer_1 = configuration2.peptide_chains[0]
tetramer_1.removeResidues(-3, None)
# Next we build a PeptideChain for the monomer. We use a C-alpha
# model, which is sufficient for the purpose of this script.
chain = PeptideChain(monomer, model='calpha')
# How big is this beast? For a quick guess, print the size of the smallest
# rectangular box containing it:
p1, p2 = chain.boundingBox()
print("Size of a bounding box: %4.2f x %4.2f x %4.2f nm" % tuple(p2 - p1))
# Formalities: we define a universe and put the chain inside.
# Then we make a copy of the configuration of the universe for later use.
# This is necessary because configurations are defined only for
# universes (for various good reasons...).
universe = InfiniteUniverse()
universe.addObject(chain)
monomer_configuration = copy(universe.configuration())
# The first file contains a monomer, the second one a tetramer in # which each chain is almost identical to the monomer from the first # file. We have to cut off the last (incomplete) residue from the # monomer and the last three residues of each chain of the tetramers # to get matching sequences. We'll just deal with one of the chains of # the tetramer here. monomer = configuration1.peptide_chains[0] monomer.removeResidues(-1, None) tetramer_1 = configuration2.peptide_chains[0] tetramer_1.removeResidues(-3, None) # Next we build a PeptideChain for the monomer. We have to specify # that we have no C terminus (missing) and no hydrogens. chain = PeptideChain(monomer, model='no_hydrogens', c_terminus=0) # How big is this beast? For a quick guess, print the size of the smallest # rectangular box containing it: p1, p2 = chain.boundingBox() print "Size of a bounding box: %4.2f x %4.2f x %4.2f nm" % tuple(p2-p1) # Formalities: we define a universe and put the chain inside. # Then we make a copy of the configuration of the universe for later use. # This is necessary because configurations are defined only for # universes (for various good reasons...). universe = InfiniteUniverse() universe.addObject(chain) monomer_configuration = copy(universe.configuration())
# Choose all objects of class "Protein"
proteins = universe.objectList(Protein)
# Construct an initial configuration in which the proteins are contiguous.
conf = universe.contiguousObjectConfiguration(proteins)
# Construct a C_alpha representation and a mapping from the "real"
# C_alpha atoms to their counterparts in the reduced model.
universe_calpha = InfiniteUniverse()
index = 0
map = []
for protein in proteins:
chains_calpha = []
for chain in protein:
chains_calpha.append(PeptideChain(chain.sequence(),
model='calpha'))
protein_calpha = Protein(chains_calpha)
universe_calpha.addObject(protein_calpha)
for i in range(len(protein)):
chain = protein[i]
chain_calpha = protein_calpha[i]
for j in range(len(chain)):
r = conf[chain[j].peptide.C_alpha]
chain_calpha[j].peptide.C_alpha.setPosition(r)
chain_calpha[j].peptide.C_alpha.index = index
map.append(chain[j].peptide.C_alpha.index)
index = index + 1
universe_calpha.configuration()
# Open the new trajectory for just the interesting objects.
trajectory_calpha = Trajectory(universe_calpha, 'calpha_trajectory.nc', 'w')
configuration = PDBConfiguration('insulin.pdb')
# Cut off the first three residues of the third chain.
configuration.peptide_chains[2].removeResidues(0, 3)
# Mark the second chain as modified
for chain in configuration.peptide_chains:
chain.modified = 0
configuration.peptide_chains[2].modified = 1
# Construct the peptide chain objects without hydrogens. For
# modified chains, don't use the N-terminal form for the fist residue.
chains = []
for chain in configuration.peptide_chains:
if chain.modified:
chains.append(PeptideChain(chain, model='no_hydrogens', n_terminus=0))
else:
chains.append(PeptideChain(chain, model='no_hydrogens'))
# Make the protein object.
insulin = Protein(chains)
#
# Stop here, since the last "problem" is just an illustration,
# you can't run it directly because there is no "special residue"
# definition.
#
if 0:
#
# Fourth problem: construct a protein with a non-standard residue.