def comp_score(receptor_file, ligand_file):
"""Compute the Cornell score for a docking configuration."""
# Parse the two files
pdb_receptor = parse_pdb(receptor_file)
pdb_ligand = parse_pdb(ligand_file)
# Create a pdb object for the docking
pdb_docking = Pdb()
for chainID in pdb_receptor.keys():
pdb_docking.add_chain("R" + chainID, pdb_receptor[chainID])
for chainID in pdb_ligand.keys():
pdb_docking.add_chain("L" + chainID, pdb_ligand[chainID])
# Create the Cornell ojbect for the docking
cornell_dock = Cornell_calc(pdb_docking)
# Split the list of atom's index between ligand and receptor
last_receptor = len(pdb_receptor.get_atom_list())
last_ligand = len(pdb_ligand.get_atom_list())
receptor_idx = range(last_receptor)
ligand_idx = range(last_receptor, last_receptor + last_ligand)
#compute the score
score = 0
for i in receptor_idx:
for j in ligand_idx:
score += cornell_dock.get_Eij(i, j)
return score
def rmsdInterface(file_Ligand_Natif, file_Ligand_Soluce, listeIndices):
PDB1 = pdb.parse_pdb(file_Ligand_Natif)
PDB2 = pdb.parse_pdb(file_Ligand_Soluce)
coord1 = PDB1.get_CA_Elems(listeIndices)
coord2 = PDB1.get_CA_Elems(listeIndices)
distanceMatrix = distances(coord2, coord2)
return rmsd(distanceMatrix)
def rmsdLigant(file_Ligand_Natif, file_Ligand_Soluce):
PDB1 = pdb.parse_pdb(file_Ligand_Natif)
PDB2 = pdb.parse_pdb(file_Ligand_Soluce)
coordCa1 = PDB1.get_CA()
coordCa2 = PDB2.get_CA()
distance = distances(coordCa1, coordCa2)
return rmsd(distance)
def rmsdComplexe(file_Ligand_Natif, file_Ligand_Soluce, file_Rec_Natif):
PDB1 = pdb.parse_pdb(file_Ligand_Natif)
PDB2 = pdb.parse_pdb(file_Ligand_Soluce)
PDB_REC = pdb.parse_pdb(file_Rec_Natif)
coordCa_Ligand_Natif = PDB1.get_CA()
coordCa_Ligand_Soluce = PDB2.get_CA()
coordCa_REC = PDB_REC.get_CA()
complexe = coordCa_REC + coordCa_Ligand_Natif
solution = coordCa_REC + coordCa_Ligand_Soluce
distance = distances(complexe, solution)
return rmsd(distance)
from parser_pdb import parse_pdb
from Protein import interface
import os
good_pdb = []
rec = parse_pdb("../data/Rec_natif.pdb")
for pdb_file in os.listdir("../data"):
important_residues = set({'39', '42', '29', '35', '76', '38'})
if (pdb_file.find("natif") == -1 and pdb_file != 'ex.pdb'
and pdb_file.find(".pdb") != -1):
print(pdb_file) # to follow the progression
lig = parse_pdb("../data/" + pdb_file)
if len(
interface(
rec.values()[0],
lig.values()[0])[1].intersection(important_residues)) >= 4:
good_pdb.append(pdb_file)
good_pdb_file = open("../data/scoring_Cornell/good_pdb.txt", 'w')
for pdb in good_pdb:
good_pdb_file.write(pdb + '\n')
from Cornell import Cornell_calc
from parser_pdb import parse_pdb
from structureToolsProjPython import preparePDB
official = preparePDB("../data/ex.pdb", "D")
test = Cornell_calc(parse_pdb("../data/ex.pdb"))
for chain in official["chains"]:
for curres in official[chain]["reslist"]:
for atomtype in official[chain][curres]["atomlist"]:
atom = official[chain][curres][atomtype]
id_at = int(atom['id']) - 1
if atom["charge"] != test.get_q(id_at):
print (curres, official[chain][curres]["resname"], atomtype, "charge")
print(id_at)
if atom["vdw"] != test.get_r(id_at):
print (curres, official[chain][curres]["resname"], atomtype, "vdw")
print(id_at)
if atom["epsilon"] != test.get_epsilon(id_at):
print (curres, official[chain][curres]["resname"], atomtype, "epsilon")
print(id_at)
official = None
official = preparePDB("../data/Lig_natif.pdb", "D")
test = Cornell_calc(parse_pdb("../data/Lig_natif.pdb"))
id_at = 0
for chain in official["chains"]:
for curres in official[chain]["reslist"]:
for atomtype in official[chain][curres]["atomlist"]:
atom = official[chain][curres][atomtype]
if atom["charge"] != test.get_q(id_at):