491 lines
20 KiB
Python
491 lines
20 KiB
Python
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from __future__ import division
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from __future__ import print_function
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import pickle,sys,os,math,propka.calculations
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import json
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import pkg_resources
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from propka.lib import info, warning
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class bondmaker:
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def __init__(self):
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# predefined bonding distances
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self.distances = {
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'S-S':2.5,
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'F-F':1.7}
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self.distances_squared = {}
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for k in self.distances.keys():
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self.distances_squared[k]=self.distances[k]*self.distances[k]
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self.H_dist = 1.5;
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self.default_dist = 2.0;
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self.H_dist_squared = self.H_dist * self.H_dist
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self.default_dist_squared = self.default_dist * self.default_dist
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self.max_sq_distance = max(list(self.distances_squared.values())+[self.default_dist_squared])
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# protein bonding data
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self.data_file_name = pkg_resources.resource_filename(__name__, 'protein_bonds.json')
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with open(self.data_file_name,'rt') as json_file:
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self.protein_bonds = json.load(json_file)
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self.intra_residue_backbone_bonds = {'N': ['CA'],
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'CA':['N','C'],
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'C': ['CA','O'],
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'O': ['C']}
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self.number_of_pi_electrons_in_bonds_in_backbone = {'C':1,
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'O':1}
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self.number_of_pi_electrons_in_conjugate_bonds_in_backbone = {'N':1}
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self.number_of_pi_electrons_in_bonds_in_sidechains = {'ARG-CZ' :1,
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'ARG-NH1':1,
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'ASN-OD1':1,
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'ASN-CG' :1,
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'ASP-OD1':1,
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'ASP-CG' :1,
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'GLU-OE1':1,
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'GLU-CD' :1,
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'GLN-OE1':1,
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'GLN-CD' :1,
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'HIS-CG' :1,
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'HIS-CD2':1,
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'HIS-ND1':1,
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'HIS-CE1':1,
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'PHE-CG' :1,
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'PHE-CD1':1,
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'PHE-CE1':1,
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'PHE-CZ' :1,
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'PHE-CE2':1,
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'PHE-CD2':1,
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'TRP-CG' :1,
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'TRP-CD1':1,
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'TRP-CE2':1,
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'TRP-CD2':1,
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'TRP-CE3':1,
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'TRP-CZ3':1,
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'TRP-CH2':1,
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'TRP-CZ2':1,
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'TYR-CG' :1,
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'TYR-CD1':1,
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'TYR-CE1':1,
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'TYR-CZ' :1,
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'TYR-CE2':1,
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'TYR-CD2':1}
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self.number_of_pi_electrons_in_conjugate_bonds_in_sidechains = {'ARG-NE' :1,
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'ARG-NH2':1,
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'ASN-ND2':1,
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'GLN-NE2':1,
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'HIS-NE2':1,
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'TRP-NE1':1}
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self.number_of_pi_electrons_in_bonds_ligands = {'C.ar':1,
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'N.pl3':0,
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'C.2':1,
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'O.2':1,
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'O.co2':1,
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'N.ar':1,
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'C.1':2,
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'N.1':2}
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self.number_of_pi_electrons_in_conjugate_bonds_in_ligands = {'N.am':1,'N.pl3':1}
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self.backbone_atoms = list(self.intra_residue_backbone_bonds.keys())
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self.terminal_oxygen_names = ['OXT','O\'\'']
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return
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def find_bonds_for_protein(self, protein):
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""" Finds bonds proteins based on the way atoms
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normally bond in proteins"""
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info('++++ Side chains ++++')
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# side chains
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for chain in protein.chains:
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for residue in chain.residues:
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if residue.resName.replace(' ','') not in ['N+','C-']:
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self.find_bonds_for_side_chain(residue.atoms)
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info('++++ Backbones ++++')
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# backbone
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last_residues = []
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for chain in protein.chains:
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for i in range(1,len(chain.residues)):
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if chain.residues[i-1].resName.replace(' ','') not in ['N+','C-']:
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if chain.residues[i].resName.replace(' ','') not in ['N+','C-']:
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self.connect_backbone(chain.residues[i-1], chain.residues[i])
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last_residues.append(chain.residues[i])
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info('++++ terminal oxygen ++++')
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# terminal OXT
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for last_residue in last_residues:
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self.find_bonds_for_terminal_oxygen(last_residue)
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info('++++ cysteines ++++')
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# Cysteines
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for chain in protein.chains:
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for i in range(0,len(chain.residues)):
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if chain.residues[i].resName == 'CYS':
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for j in range(0,len(chain.residues)):
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if chain.residues[j].resName == 'CYS' and j != i:
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self.check_for_cysteine_bonds(chain.residues[i],
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chain.residues[j])
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return
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def check_for_cysteine_bonds(self, cys1, cys2):
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for atom1 in cys1.atoms:
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if atom1.name == 'SG':
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for atom2 in cys2.atoms:
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if atom2.name == 'SG':
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if propka.calculations.squared_distance(atom1,atom2) < self.SS_dist_squared:
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self.make_bond(atom1, atom2)
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return
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def find_bonds_for_terminal_oxygen(self, residue):
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for atom1 in residue.atoms:
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if atom1.name in self.terminal_oxygen_names:
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for atom2 in residue.atoms:
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if atom2.name == 'C':
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self.make_bond(atom1, atom2)
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return
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def connect_backbone(self, residue1, residue2):
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""" Sets up bonds in the backbone """
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# residue 1
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self.find_bonds_for_residue_backbone(residue1)
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# residue 2
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self.find_bonds_for_residue_backbone(residue2)
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# inter-residue bond
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for atom1 in residue1.atoms:
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if atom1.name == 'C':
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for atom2 in residue2.atoms:
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if atom2.name == 'N':
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if propka.calculations.squared_distance(atom1,atom2) < self.default_dist_squared:
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self.make_bond(atom1, atom2)
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return
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def find_bonds_for_residue_backbone(self, residue):
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for atom1 in residue.atoms:
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if atom1.name in list(self.number_of_pi_electrons_in_bonds_in_backbone.keys()):
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atom1.number_of_pi_electrons_in_double_and_triple_bonds = self.number_of_pi_electrons_in_bonds_in_backbone[atom1.name]
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if atom1.name in list(self.number_of_pi_electrons_in_conjugate_bonds_in_backbone.keys()) and len(atom1.bonded_atoms)>1: # last part to avoid including N-term
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atom1.number_of_pi_electrons_in_conjugate_double_and_triple_bonds = self.number_of_pi_electrons_in_conjugate_bonds_in_backbone[atom1.name]
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if atom1.name in self.backbone_atoms:
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for atom2 in residue.atoms:
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if atom2.name in self.intra_residue_backbone_bonds[atom1.name]:
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self.make_bond(atom1, atom2)
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return
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def find_bonds_for_side_chain(self, atoms):
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""" Finds bonds for a side chain """
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for atom1 in atoms:
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key = '%s-%s'%(atom1.resName,atom1.name)
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if key in list(self.number_of_pi_electrons_in_bonds_in_sidechains.keys()):
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atom1.number_of_pi_electrons_in_double_and_triple_bonds = self.number_of_pi_electrons_in_bonds_in_sidechains[key]
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if key in list(self.number_of_pi_electrons_in_conjugate_bonds_in_sidechains.keys()):
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atom1.number_of_pi_electrons_in_conjugate_double_and_triple_bonds = self.number_of_pi_electrons_in_conjugate_bonds_in_sidechains[key]
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if not atom1.name in self.backbone_atoms:
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if not atom1.name in self.terminal_oxygen_names:
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for atom2 in atoms:
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if atom2.name in self.protein_bonds[atom1.resName][atom1.name]:
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self.make_bond(atom1,atom2)
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return
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def find_bonds_for_ligand(self, ligand):
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""" Finds bonds for all atoms in the molecule """
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# identify bonding atoms
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self.find_bonds_for_atoms(ligand.atoms)
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self.add_pi_electron_table_info(ligand.atoms)
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return
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def add_pi_electron_table_info(self, atoms):
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# apply table information on pi-electrons
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for atom in atoms:
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# for ligands
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if atom.type == 'hetatm':
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if atom.sybyl_type in self.number_of_pi_electrons_in_bonds_ligands.keys():
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atom.number_of_pi_electrons_in_double_and_triple_bonds = self.number_of_pi_electrons_in_bonds_ligands[atom.sybyl_type]
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if atom.sybyl_type in self.number_of_pi_electrons_in_conjugate_bonds_in_ligands.keys():
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atom.number_of_pi_electrons_in_conjugate_double_and_triple_bonds = self.number_of_pi_electrons_in_conjugate_bonds_in_ligands[atom.sybyl_type]
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# for protein
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if atom.type == 'atom':
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key = '%s-%s'%(atom.resName,atom.name)
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if key in list(self.number_of_pi_electrons_in_bonds_in_sidechains.keys()):
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atom.number_of_pi_electrons_in_double_and_triple_bonds = self.number_of_pi_electrons_in_bonds_in_sidechains[key]
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if key in list(self.number_of_pi_electrons_in_conjugate_bonds_in_sidechains.keys()):
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atom.number_of_pi_electrons_in_conjugate_double_and_triple_bonds = self.number_of_pi_electrons_in_conjugate_bonds_in_sidechains[key]
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if atom.name in list(self.number_of_pi_electrons_in_bonds_in_backbone.keys()):
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atom.number_of_pi_electrons_in_double_and_triple_bonds = self.number_of_pi_electrons_in_bonds_in_backbone[atom.name]
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if atom.name in list(self.number_of_pi_electrons_in_conjugate_bonds_in_backbone.keys()) and len(atom.bonded_atoms)>1: # last part to avoid including N-term
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atom.number_of_pi_electrons_in_conjugate_double_and_triple_bonds = self.number_of_pi_electrons_in_conjugate_bonds_in_backbone[atom.name]
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return
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def find_bonds_for_protein_by_distance(self, molecule):
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""" Finds bonds for all atoms in the molecule """
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#self.find_bonds_for_protein(molecule)
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atoms = []
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for chain in molecule.chains:
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for residue in chain.residues:
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if residue.resName.replace(' ','') not in ['N+','C-']:
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for atom in residue.atoms:
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atoms.append(atom)
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self.find_bonds_for_atoms_using_boxes(atoms) #####
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#self.find_bonds_for_atoms(atoms) #####
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return atoms
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def find_bonds_for_atoms(self, atoms):
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""" Finds all bonds for a list of atoms"""
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no_atoms = len(atoms)
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for i in range(no_atoms):
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for j in range(i+1,no_atoms):
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if atoms[i] in atoms[j].bonded_atoms:
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continue
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if self.check_distance(atoms[i], atoms[j]):
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self.make_bond(atoms[i],atoms[j])
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# di-sulphide bonds
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if atoms[i].element == 'S' and atoms[j].element == 'S':
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atoms[i].cysteine_bridge = True
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atoms[j].cysteine_bridge = True
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return
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def check_distance(self, atom1, atom2):
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sq_dist = propka.calculations.squared_distance(atom1, atom2)
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if sq_dist > self.max_sq_distance:
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return False
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key = '%s-%s'%(atom1.element,atom2.element)
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h_count = key.count('H')
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if sq_dist < self.H_dist_squared and h_count==1:
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return True
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if sq_dist < self.default_dist_squared and h_count==0:
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return True
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if key in self.distances_squared.keys():
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if sq_dist < self.distances_squared[key]:
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return True
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return False
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def find_bonds_for_molecules_using_boxes(self, molecules):
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""" Finds all bonds for a molecular container"""
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for name in molecules.conformation_names:
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self.find_bonds_for_atoms_using_boxes(molecules.conformations[name].atoms)
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#for chain in molecules.conformations[name].chains:
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# self.find_bonds_for_atoms_using_boxes(molecules.conformations[name].get_chain(chain))
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return
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def add_pi_electron_information(self, molecules):
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for name in molecules.conformation_names:
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self.add_pi_electron_table_info(molecules.conformations[name].atoms)
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return
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def find_bonds_for_atoms_using_boxes(self, atoms):
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""" Finds all bonds for a list of atoms"""
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box_size = 2.5
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# find min and max coordinates
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xmin = 1e6; xmax = -1e6
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ymin = 1e6; ymax = -1e6
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zmin = 1e6; zmax = -1e6
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for atom in atoms:
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if atom.x > xmax:
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xmax = atom.x
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if atom.y > ymax:
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ymax = atom.y
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if atom.z > zmax:
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zmax = atom.z
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if atom.x < xmin:
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xmin = atom.x
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if atom.y < ymin:
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ymin = atom.y
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if atom.z < zmin:
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zmin = atom.z
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xlen = xmax-xmin
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ylen = ymax-ymin
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zlen = zmax-zmin
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#info('x range: [%6.2f;%6.2f] %6.2f'%(xmin,xmax,xlen))
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#info('y range: [%6.2f;%6.2f] %6.2f'%(ymin,ymax,ylen))
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#info('z range: [%6.2f;%6.2f] %6.2f'%(zmin,zmax,zlen))
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# how many boxes do we need in each dimension?
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# NOTE: math.ceil() returns an int in python3 and a float in
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# python2, so we need to convert it to an int for range() to work in
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# both versions. See PEP 3141.
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self.no_box_x = max(1, int(math.ceil(xlen/box_size)))
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self.no_box_y = max(1, int(math.ceil(ylen/box_size)))
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self.no_box_z = max(1, int(math.ceil(zlen/box_size)))
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#info('No. box x: %6.2f'%self.no_box_x)
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#info('No. box y: %6.2f'%self.no_box_y)
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#info('No. box z: %6.2f'%self.no_box_z)
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# initialize boxes
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self.boxes = {}
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for x in range(self.no_box_x):
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for y in range(self.no_box_y):
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for z in range(self.no_box_z):
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self.boxes[(x,y,z)] = []
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# put atoms into boxes
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for atom in atoms:
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x = math.floor((atom.x-xmin)/box_size)
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y = math.floor((atom.y-ymin)/box_size)
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z = math.floor((atom.z-zmin)/box_size)
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self.put_atom_in_box(x,y,z,atom)
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# assign bonds
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for key, value in self.boxes.items():
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self.find_bonds_for_atoms(value)
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return
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def put_atom_in_box(self,x,y,z,atom):
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# atom in the x,y,z box and the up to 7 neighboring boxes on
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# one side of the x,y,z box in each dimension
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for bx in [x,x+1]:
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for by in [y,y+1]:
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for bz in [z,z+1]:
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key = (bx,by,bz)
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try:
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self.boxes[key].append(atom)
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except KeyError:
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# No box exists for this coordinate
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pass
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#info(atom,'->',key,':',len(self.boxes[key]))
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return
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def has_bond(self, atom1, atom2):
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if atom1 in atom2.bonded_atoms or atom2 in atom1.bonded_atoms:
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return True
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return False
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def make_bond(self, atom1, atom2):
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""" Makes a bond between atom1 and atom2 """
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if atom1 == atom2:
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return
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#info('making bond for',atom1,atom2)
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if not atom1 in atom2.bonded_atoms:
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atom2.bonded_atoms.append(atom1)
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if not atom2 in atom1.bonded_atoms:
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atom1.bonded_atoms.append(atom2)
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return
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def generate_protein_bond_dictionary(self, atoms):
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for atom in atoms:
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for bonded_atom in atom.bonded_atoms:
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resi_i = atom.resName
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name_i = atom.name
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resi_j = bonded_atom.resName
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name_j = bonded_atom.name
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if not name_i in self.backbone_atoms or\
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not name_j in self.backbone_atoms:
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if not name_i in self.terminal_oxygen_names and\
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not name_j in self.terminal_oxygen_names:
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if not resi_i in list(self.protein_bonds.keys()):
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self.protein_bonds[resi_i] = {}
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if not name_i in self.protein_bonds[resi_i]:
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self.protein_bonds[resi_i][name_i] = []
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if not name_j in self.protein_bonds[resi_i][name_i]:
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self.protein_bonds[resi_i][name_i].append(name_j)
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if not resi_j in list(self.protein_bonds.keys()):
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self.protein_bonds[resi_j] = {}
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if not name_j in self.protein_bonds[resi_j]:
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self.protein_bonds[resi_j][name_j] = []
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if not name_i in self.protein_bonds[resi_j][name_j]:
|
|
self.protein_bonds[resi_j][name_j].append(name_i)
|
|
|
|
|
|
return
|
|
|
|
|
|
if __name__ == '__main__':
|
|
# If called directly, set up protein bond dictionary
|
|
import protein, pdb, sys,os
|
|
arguments = sys.argv
|
|
if len(arguments) != 2:
|
|
info('Usage: bonds.py <pdb_file>')
|
|
sys.exit(0)
|
|
|
|
filename = arguments[1]
|
|
if not os.path.isfile(filename):
|
|
info('Error: Could not find \"%s\"' % filename)
|
|
sys.exit(1)
|
|
|
|
pdblist = pdb.readPDB(filename)
|
|
my_protein = protein.Protein(pdblist,'test.pdb')
|
|
|
|
for chain in my_protein.chains:
|
|
for residue in chain.residues:
|
|
residue.atoms = [atom for atom in residue.atoms if atom.element != 'H']
|
|
|
|
b = bondmaker()
|
|
#b.protein_bonds = {}
|
|
atoms = b.find_bonds_for_protein_by_distance(my_protein)
|
|
# b.generate_protein_bond_dictionary(atoms)
|
|
|
|
#file = open(b.data_file_name,'wb')
|
|
#pickle.dump(b.protein_bonds, file)
|
|
#file.close()
|