def hh_contact_count(pdbfile,
chain1,
chain2,
maxDistance,
excludeRange,
model=1,
print_contact_list=False,
print_summary=False,
count_total_contacts=False,
atomic=False,
protComplex=False,
atomwiseContacts=False,
VDWoverlap=None,
twoCarbonCount=False):
#here, the protein structure is converted into a python object (see p3d docs)
pdb = None
#try:
if chain1 != chain2:
pdb = protein.Protein(pdbfile, chains=[chain1, chain2])
else:
pdb = protein.Protein(pdbfile, chains=[chain1])
#except ValueError as ve:
# print "a value error occurred"
# print ve.args
# print ve.message
#
# sys.exit(1)
#except IndexError:
# print "an index error occurred"
#
#
# sys.exit(1)
#for line in pdb.info():
# print(line)
# this data structure will hold a dicionary where the keys are ordered pairs
# of the residue positions that are in contact, and the value is the distance
# between those residues in angstrom. (--> closest distance between any atoms of the residues)
DistanceMatrix = ddict(float)
''' query Set alphas to have one atom per residue from both chains '''
chain1_alphas = pdb.query('chain {0} and alpha and model {1}'.format(
chain1, model))
chain2_alphas = pdb.query('chain {0} and alpha and model {1}'.format(
chain2, model))
#print "#+#+#+#+#+#+#", len(chain1_alphas),len(chain2_alphas)
if protComplex:
complex_alphas = chain1_alphas + chain2_alphas
else:
complex_alphas = chain1_alphas
chain1_hydrophobic_counter = 0
chain2_hydrophobic_counter = 0
chain1_polar_counter = 0
chain2_polar_counter = 0
contacts_counter = 0
zero_C_counter = 0
one_C_counter = 0
two_C_counter = 0
for alpha in complex_alphas: #these are chain1 alphas if protComplex=False
if atomic:
estimateAtomicSurrounding(Protein=pdb,\
ResidueAtom=alpha,\
targetChain=chain2,\
DistanceMatrix=DistanceMatrix,\
maxDistance=maxDistance,\
intraChainExcludeRange=excludeRange,\
Model=model, \
countHydrophobic=False,\
atomwiseContacts=atomwiseContacts)
# counting all contacts?
if count_total_contacts:
if isHydrophobic(convert321(alpha.aa)):
chain1_hydrophobic_counter += 1
else:
chain1_polar_counter += 1
# add contacts for residue of this alpha carbon atom to dictionary
DistanceMatrix = estimateMinContacts(Protein=pdb,ResidueAtom=alpha,\
targetChain=chain2,DistanceMatrix=DistanceMatrix,\
maxDistance=maxDistance,intraChainExcludeRange=excludeRange,Model=model, countHydrophobic=False,atomwiseContacts=atomwiseContacts,VDWoverlap=VDWoverlap)
else:
# or counting only contacts between hydrophobic residues
if isHydrophobic(convert321(alpha.aa)):
chain1_hydrophobic_counter += 1
#append contacts to DistanceMatrix
DistanceMatrix = estimateMinContacts(Protein=pdb,ResidueAtom=alpha,\
targetChain=chain2,DistanceMatrix=DistanceMatrix,\
maxDistance=maxDistance,intraChainExcludeRange=excludeRange,Model=model,countHydrophobic=True,atomwiseContacts=atomwiseContacts,VDWoverlap=VDWoverlap)
else:
chain1_polar_counter += 1
if print_summary:
for alpha in chain2_alphas:
if isHydrophobic(convert321(alpha.aa)):
chain2_hydrophobic_counter += 1
#DistanceMatrixHH = estimateMinContacts(Protein=pdb,ResidueAtom=alpha,\
# targetChain=chain1,DistanceMatrix=DistanceMatrixHH,\
# maxDistance=maxDistance,intraChainExcludeRange=excludeRange,Model=model)
else:
chain2_polar_counter += 1
#column headers for output table of contacts
if print_contact_list:
if atomwiseContacts:
print "\t".join([
"pos_chain1", "pos_chain2", "contact_dist(A)", "atom1",
"atom2", "AA1", "AA2", "#C-atoms/contact"
])
else:
print "\t".join([
"pos_chain1", "pos_chain2", "contact_dist(A)", "AA1",
"hydropathy1", "surface1(nm^2)", "mass1(Da)", "AA2",
"hydropathy2", "surface2(nm^2)", "mass2(Da)"
])
for coords, value in DistanceMatrix.items():
if atomwiseContacts:
AA1 = coords[4]
AA2 = coords[5]
atom1 = coords[2]
atom2 = coords[3]
C_atoms = 0
if "C" in atom1:
C_atoms += 1
if "C" in atom2:
C_atoms += 1
if C_atoms == 0:
zero_C_counter += 1
elif C_atoms == 1:
one_C_counter += 1
elif C_atoms == 2:
two_C_counter += 1
if print_contact_list:
print "\t".join([
str(coords[0]),
str(coords[1]),
str(value),
str(atom1),
str(atom2), AA1, AA2,
str(C_atoms)
])
else:
if print_contact_list:
AA1 = coords[2]
AA2 = coords[3]
hydropath1 = calcHydropathy(AA1)
hydropath2 = calcHydropathy(AA2)
surf1 = calcSideChainSurface(AA1)
surf2 = calcSideChainSurface(AA2)
mass1 = calcMass(AA1)
mass2 = calcMass(AA2)
print "\t".join([
str(coords[0]),
str(coords[1]),
str(value), AA1,
str(hydropath1),
str(surf1),
str(mass1), AA2,
str(hydropath2),
str(surf2),
str(mass2)
])
contacts_counter += 1
if print_summary:
print "===================================================================="
print "PDB file:", pdbfile
print "chain {0} vs chain {1}".format(chain1, chain2)
if count_total_contacts:
print "total contacts counted:", contacts_counter
else:
print "hydrophobic contacts counted:", contacts_counter
if atomwiseContacts:
print "C/C atom contacts:", two_C_counter
print "--------------------------------------------------------------------"
print "chain1:", chain1
print "length1:", len(chain1_alphas)
print "polar1:", str(chain1_polar_counter)
print "hydrophobic1:", str(chain1_hydrophobic_counter)
ch1_seq = ""
ch1_dict = {}
for alpha in chain1_alphas:
ch1_dict[alpha.resid] = convert321(alpha.aa)
for i in range(1, len(chain1_alphas) + 1):
ch1_seq += ch1_dict[i]
print "sequence1:", ch1_seq
if chain1 != chain2:
print "--------------------------------------------------------------------"
print "chain2:", chain2
print "length2:", len(chain2_alphas)
print "polar2:", str(chain2_polar_counter)
print "hydrophobic2:", str(chain2_hydrophobic_counter)
ch2_seq = ""
ch2_dict = {}
for alpha in chain2_alphas:
ch2_dict[alpha.resid] = convert321(alpha.aa)
for i in range(1, len(chain2_alphas) + 1):
ch2_seq += ch2_dict[i]
print "sequence2:", ch2_seq
print "===================================================================="
if twoCarbonCount:
return two_C_counter
else:
return contacts_counter
def isHydrophobic(residue):
if calcHydropathy(residue) > 0:
return True
else:
return False
def estimateAtomicSurrounding(Protein=None,
ResidueAtom=None,
targetChain=None,
DistanceMatrix=None,
maxDistance=None,
intraChainExcludeRange=None,
Model=None,
countHydrophobic=False,
protComplex=False,
VDWoverlap=None):
# atoms of focal residue
residueAtoms = Protein.query(
'protein and resid {0} and chain {1} and model {2}'.format(
ResidueAtom.resid, ResidueAtom.chain, model))
# filter residues within the excluded intra-chain distance range (upstream and downstream)
exclude_string = ""
if intraChainExcludeRange != None:
resid = ResidueAtom.resid
prot_len = len(Protein.atoms)
exclude_list = []
for i in range(resid - intraChainExcludeRange,
resid + intraChainExcludeRange + 1):
if i >= 0 and i < prot_len:
exclude_list.append(i)
exclude_string = str(exclude_list).strip("[]")
# get surrounding atoms for this residue (within maxDistance) in target chain
if protComplex:
surrounding1 = Protein.query('protein and within {0} of'.format(maxDistance)\
,residueAtoms,'and chain {1} not resid {1} and model {2}'.format(ResidueAtom.chain,exclude_string, model))
surrounding2 = Protein.query('protein and within {0} of'.format(maxDistance)\
,residueAtoms,'and chain {1} not resid {1} and model {2}'.format(targetChain,exclude_string, model))
surrounding = surrounding1 + surrounding2
else:
surrounding = Protein.query('protein and within {0} of'.format(maxDistance)\
,residueAtoms,'and chain {0} and not resid {1} and model {2}'.format(targetChain, exclude_string, model))
nAtoms = len(surrounding)
print ResidueAtom.resid, ResidueAtom.aa, ResidueAtom.chain, nAtoms, calcHydropathy(
convert321(ResidueAtom.aa)),
#for residAtom in residueAtoms:
# tmp = residAtom.atype
# print tmp,
#print "|",
C_counter = 0
CA_counter = 0
non_C_counter = 0
h_counter = 0
p_counter = 0
self_counter = 0
for atom in surrounding:
tmp = atom.atype
tmp_aa = atom.aa
#if atom.resid == ResidueAtom.resid:
# self_counter+=1
hP = calcHydropathy(convert321(tmp_aa))
if hP > 0 and not "CA" in tmp:
h_counter += 1
else:
p_counter += 1
if "CA" in tmp:
CA_counter += 1
if "C" in tmp:
C_counter += 1
else:
non_C_counter += 1
#print tmp,
if non_C_counter == 0:
ratio = C_counter
else:
ratio = (C_counter / float(non_C_counter))
print C_counter, non_C_counter, h_counter, p_counter, CA_counter
def isHydrophobic(residue): if calcHydropathy(residue) > 0: return True else: return False
def hh_contact_count(pdbfile, chain1, chain2,maxDistance, excludeRange,model=1,print_contact_list=False,print_summary=False,count_total_contacts=False,atomic=False,protComplex=False,atomwiseContacts=False,VDWoverlap=None,twoCarbonCount=False):
#here, the protein structure is converted into a python object (see p3d docs)
pdb=None
#try:
if chain1 != chain2:
pdb = protein.Protein(pdbfile,chains=[chain1,chain2])
else:
pdb = protein.Protein(pdbfile,chains=[chain1])
#except ValueError as ve:
# print "a value error occurred"
# print ve.args
# print ve.message
#
# sys.exit(1)
#except IndexError:
# print "an index error occurred"
#
#
# sys.exit(1)
#for line in pdb.info():
# print(line)
# this data structure will hold a dicionary where the keys are ordered pairs
# of the residue positions that are in contact, and the value is the distance
# between those residues in angstrom. (--> closest distance between any atoms of the residues)
DistanceMatrix = ddict(float)
''' query Set alphas to have one atom per residue from both chains '''
chain1_alphas = pdb.query('chain {0} and alpha and model {1}'.format(chain1, model))
chain2_alphas = pdb.query('chain {0} and alpha and model {1}'.format(chain2, model))
#print "#+#+#+#+#+#+#", len(chain1_alphas),len(chain2_alphas)
if protComplex:
complex_alphas = chain1_alphas + chain2_alphas
else:
complex_alphas = chain1_alphas
chain1_hydrophobic_counter = 0
chain2_hydrophobic_counter = 0
chain1_polar_counter = 0
chain2_polar_counter = 0
contacts_counter = 0
zero_C_counter = 0
one_C_counter = 0
two_C_counter = 0
for alpha in complex_alphas: #these are chain1 alphas if protComplex=False
if atomic:
estimateAtomicSurrounding(Protein=pdb,\
ResidueAtom=alpha,\
targetChain=chain2,\
DistanceMatrix=DistanceMatrix,\
maxDistance=maxDistance,\
intraChainExcludeRange=excludeRange,\
Model=model, \
countHydrophobic=False,\
atomwiseContacts=atomwiseContacts)
# counting all contacts?
if count_total_contacts:
if isHydrophobic(convert321(alpha.aa)):
chain1_hydrophobic_counter += 1
else:
chain1_polar_counter += 1
# add contacts for residue of this alpha carbon atom to dictionary
DistanceMatrix = estimateMinContacts(Protein=pdb,ResidueAtom=alpha,\
targetChain=chain2,DistanceMatrix=DistanceMatrix,\
maxDistance=maxDistance,intraChainExcludeRange=excludeRange,Model=model, countHydrophobic=False,atomwiseContacts=atomwiseContacts,VDWoverlap=VDWoverlap)
else:
# or counting only contacts between hydrophobic residues
if isHydrophobic(convert321(alpha.aa)):
chain1_hydrophobic_counter += 1
#append contacts to DistanceMatrix
DistanceMatrix = estimateMinContacts(Protein=pdb,ResidueAtom=alpha,\
targetChain=chain2,DistanceMatrix=DistanceMatrix,\
maxDistance=maxDistance,intraChainExcludeRange=excludeRange,Model=model,countHydrophobic=True,atomwiseContacts=atomwiseContacts,VDWoverlap=VDWoverlap)
else:
chain1_polar_counter += 1
if print_summary:
for alpha in chain2_alphas:
if isHydrophobic(convert321(alpha.aa)):
chain2_hydrophobic_counter += 1
#DistanceMatrixHH = estimateMinContacts(Protein=pdb,ResidueAtom=alpha,\
# targetChain=chain1,DistanceMatrix=DistanceMatrixHH,\
# maxDistance=maxDistance,intraChainExcludeRange=excludeRange,Model=model)
else:
chain2_polar_counter += 1
#column headers for output table of contacts
if print_contact_list:
if atomwiseContacts:
print "\t".join(["pos_chain1","pos_chain2","contact_dist(A)","atom1","atom2","AA1","AA2","#C-atoms/contact"])
else:
print "\t".join(["pos_chain1","pos_chain2","contact_dist(A)","AA1","hydropathy1","surface1(nm^2)","mass1(Da)","AA2","hydropathy2","surface2(nm^2)","mass2(Da)"])
for coords,value in DistanceMatrix.items():
if atomwiseContacts:
AA1 = coords[4]
AA2 = coords[5]
atom1 = coords[2]
atom2 = coords[3]
C_atoms=0
if "C" in atom1:
C_atoms += 1
if "C" in atom2:
C_atoms += 1
if C_atoms == 0:
zero_C_counter += 1
elif C_atoms == 1:
one_C_counter += 1
elif C_atoms == 2:
two_C_counter += 1
if print_contact_list:
print "\t".join([str(coords[0]),str(coords[1]),str(value),str(atom1),str(atom2),AA1,AA2,str(C_atoms) ])
else:
if print_contact_list:
AA1 = coords[2]
AA2 = coords[3]
hydropath1 = calcHydropathy(AA1)
hydropath2 = calcHydropathy(AA2)
surf1 = calcSideChainSurface(AA1)
surf2 = calcSideChainSurface(AA2)
mass1 = calcMass(AA1)
mass2 = calcMass(AA2)
print "\t".join([str(coords[0]),str(coords[1]),str(value),AA1,str(hydropath1),str(surf1),str(mass1),AA2,str(hydropath2),str(surf2),str(mass2) ])
contacts_counter += 1
if print_summary:
print "===================================================================="
print "PDB file:", pdbfile
print "chain {0} vs chain {1}".format(chain1, chain2)
if count_total_contacts:
print "total contacts counted:", contacts_counter
else:
print "hydrophobic contacts counted:", contacts_counter
if atomwiseContacts:
print "C/C atom contacts:",two_C_counter
print "--------------------------------------------------------------------"
print "chain1:",chain1
print "length1:", len(chain1_alphas)
print "polar1:",str(chain1_polar_counter)
print "hydrophobic1:",str(chain1_hydrophobic_counter)
ch1_seq=""
ch1_dict={}
for alpha in chain1_alphas:
ch1_dict[alpha.resid] = convert321(alpha.aa)
for i in range(1,len(chain1_alphas)+1):
ch1_seq += ch1_dict[i]
print "sequence1:",ch1_seq
if chain1 != chain2:
print "--------------------------------------------------------------------"
print "chain2:",chain2
print "length2:", len(chain2_alphas)
print "polar2:",str(chain2_polar_counter)
print "hydrophobic2:",str(chain2_hydrophobic_counter)
ch2_seq=""
ch2_dict={}
for alpha in chain2_alphas:
ch2_dict[alpha.resid] = convert321(alpha.aa)
for i in range(1,len(chain2_alphas)+1):
ch2_seq += ch2_dict[i]
print "sequence2:",ch2_seq
print "===================================================================="
if twoCarbonCount:
return two_C_counter
else:
return contacts_counter
def estimateAtomicSurrounding(Protein=None,ResidueAtom=None,targetChain=None,DistanceMatrix=None,maxDistance=None, intraChainExcludeRange=None, Model=None, countHydrophobic=False,protComplex=False,VDWoverlap=None):
# atoms of focal residue
residueAtoms = Protein.query('protein and resid {0} and chain {1} and model {2}'.format(ResidueAtom.resid, ResidueAtom.chain, model))
# filter residues within the excluded intra-chain distance range (upstream and downstream)
exclude_string = ""
if intraChainExcludeRange != None:
resid = ResidueAtom.resid
prot_len = len(Protein.atoms)
exclude_list=[]
for i in range(resid-intraChainExcludeRange, resid+intraChainExcludeRange+1):
if i >= 0 and i < prot_len:
exclude_list.append(i)
exclude_string=str(exclude_list).strip("[]")
# get surrounding atoms for this residue (within maxDistance) in target chain
if protComplex:
surrounding1 = Protein.query('protein and within {0} of'.format(maxDistance)\
,residueAtoms,'and chain {1} not resid {1} and model {2}'.format(ResidueAtom.chain,exclude_string, model))
surrounding2 = Protein.query('protein and within {0} of'.format(maxDistance)\
,residueAtoms,'and chain {1} not resid {1} and model {2}'.format(targetChain,exclude_string, model))
surrounding=surrounding1+surrounding2
else:
surrounding = Protein.query('protein and within {0} of'.format(maxDistance)\
,residueAtoms,'and chain {0} and not resid {1} and model {2}'.format(targetChain, exclude_string, model))
nAtoms=len(surrounding)
print ResidueAtom.resid, ResidueAtom.aa,ResidueAtom.chain, nAtoms, calcHydropathy(convert321(ResidueAtom.aa)),
#for residAtom in residueAtoms:
# tmp = residAtom.atype
# print tmp,
#print "|",
C_counter = 0
CA_counter =0
non_C_counter = 0
h_counter=0
p_counter=0
self_counter=0
for atom in surrounding:
tmp = atom.atype
tmp_aa = atom.aa
#if atom.resid == ResidueAtom.resid:
# self_counter+=1
hP = calcHydropathy(convert321(tmp_aa))
if hP > 0 and not "CA" in tmp:
h_counter += 1
else:
p_counter += 1
if "CA" in tmp:
CA_counter += 1
if "C" in tmp:
C_counter += 1
else:
non_C_counter += 1
#print tmp,
if non_C_counter == 0:
ratio=C_counter
else:
ratio = (C_counter/float(non_C_counter))
print C_counter,non_C_counter,h_counter,p_counter,CA_counter
