def pdb2pka_sugelm(self):
"""Explore all possible mutations and calculate a phimap for each using pdb2pka (APBS)"""
import Protool
P=Protool.structureIO()
P.readpdb(self.pdbfile)
P.RemoveALT()
#import Protool.mutate
#MUT=Protool.mutate.Mutate(P)
#
# Construct arrays
#
import pKD_dict
self.data=pKD_dict.pKD_dict()
self.atom_data=pKD_dict.pKD_dict()
#
# Create dir for mutant PDB files
#
import os
mutdir=os.path.join(self.topdir,self.pdbfile+'.pdbs')
if not os.path.isdir(mutdir):
os.mkdir(mutdir)
#
# Loop over all residues
#
residues=P.residues.keys()
residues.sort()
for residue in residues:
orgres=P.resname(residue)
print 'Calculating for %s %s' %(residue,P.resname(residue))
#
# If neutral mutate to Asp, Glu, Lys, Arg, His
#
targets=[]
for res in ['ARG','LYS','HIS','ASP','GLU']:
if P.resname(residue)!=res:
targets.append(res)
#if orgres=='GLU':
# targets.append('GLN')
#elif orgres=='ASP':
# targets.append('ASN')
#elif orgres=='HIS':
# targets.append('PHE')
#elif orgres=='ARG' or P.resname(residue)=='LYS':
# targets.append('MET')
#
# Target identified. Now model each
#
for target in targets:
import pKD_tools
resid=pKD_tools.get_resid_from_res(residue)
orgres=P.resname(residue)
filename=os.path.join(mutdir,'%s:%s:%s.pdb' %(residue,orgres,target))
mutation='%s:%s:%s' %(residue,orgres,target)
if not os.path.isfile(filename):
import Design_pKa_help
Design_pKa_help.make_mutation(self.pdbfile,mutation)
NP=Protool.structureIO()
NP.readpdb(filename)
NP.writepdb(filename,TER=None)
#
# Calculate the interaction energies
#
protein,routines,forcefield,apbs_setup,lig_titgrps = pdb2pka.pre_init(pdbfilename=filename,
ff='parse',
ligand=None,
verbose=1)
mypkaRoutines = pdb2pka.pKaRoutines(protein, routines, forcefield,apbs_setup)
#
# Find our group
#
sp=residue.split(':')
chainid=sp[0]
resnum=int(sp[1])
mypkaRoutines.findTitratableGroups()
this_pKa=None
for pKa in mypkaRoutines.pKas:
print pKa.residue.resSeq,resnum
print pKa.residue.chainID,chainid
print pKa.residue.name,target
print pKa.pKaGroup.name,target
print '--------------'
print 'ChainID',pKa.residue.chainID
if pKa.residue.resSeq==resnum and pKa.residue.chainID==chainid and pKa.residue.name==target and pKa.pKaGroup.name==target:
#print 'Found group',pKa.residue.resSeq,pKa.pKaGroup.name
this_pKa=pKa
break
if not this_pKa:
raise Exception,'Could not find inserted titratable group'
mypkaRoutines.get_interaction_energies_setup(this_pKa,mode='pKD')
matrix=mypkaRoutines.matrix
#
# Dig the interaction energies out of the pdb2pka array
#
for titration1 in matrix[this_pKa].keys():
for state1 in matrix[this_pKa][titration1].keys():
grp_sub=matrix[this_pKa][titration1][state1]
if mypkaRoutines.is_charged(this_pKa,titration1,state1):
for pKa2 in grp_sub.keys():
import string
chainID2=pKa.residue.chainID
resid2='%s:%s' %(chainID2,string.zfill(pKa2.residue.resSeq,4))
for titration2 in grp_sub[pKa2].keys():
for state2 in grp_sub[pKa2][titration2].keys():
if mypkaRoutines.is_charged(pKa2,titration2,state2):
#
# Both states are charged, so now we can pull the
# interaction energies out
#
if not self.data.has_key(mutation):
self.data[mutation]={}
self.data[mutation][resid2]=grp_sub[pKa2][titration2][state2]
#
# Get the potentials at all atoms too
#
all_pots=mypkaRoutines.all_potentials[this_pKa][titration1][state1]
sub_all_pots=all_pots[pKa2][titration2][state2]
for atom in sub_all_pots.keys():
resid=mutation
import pKD_tools
resid2=pKD_tools.get_resid_from_res(atom)
atomname=atom.split(':')[-1] #atom.name
if atomname[0]=='H' or atomname in ['N','C','O']:
continue # Skip all H atoms and all non-CA backbone atoms to save memory
if not self.atom_data.has_key(resid):
self.atom_data[resid]={}
if not self.atom_data[resid].has_key(resid2):
self.atom_data[resid][resid2]={}
self.atom_data[resid][resid2][atomname]=abs(sub_all_pots[atom])
return self.data,self.atom_data
def pdb2pka_sugelm(self):
"""Explore all possible mutations and calculate a phimap for each using pdb2pka (APBS)"""
import Protool
P = Protool.structureIO()
P.readpdb(self.pdbfile)
P.RemoveALT()
#import Protool.mutate
#MUT=Protool.mutate.Mutate(P)
#
# Construct arrays
#
import pKD_dict
self.data = pKD_dict.pKD_dict()
self.atom_data = pKD_dict.pKD_dict()
#
# Create dir for mutant PDB files
#
import os
mutdir = os.path.join(self.topdir, self.pdbfile + '.pdbs')
if not os.path.isdir(mutdir):
os.mkdir(mutdir)
#
# Loop over all residues
#
residues = P.residues.keys()
residues.sort()
for residue in residues:
orgres = P.resname(residue)
print 'Calculating for %s %s' % (residue, P.resname(residue))
#
# If neutral mutate to Asp, Glu, Lys, Arg, His
#
targets = []
for res in ['ARG', 'LYS', 'HIS', 'ASP', 'GLU']:
if P.resname(residue) != res:
targets.append(res)
#if orgres=='GLU':
# targets.append('GLN')
#elif orgres=='ASP':
# targets.append('ASN')
#elif orgres=='HIS':
# targets.append('PHE')
#elif orgres=='ARG' or P.resname(residue)=='LYS':
# targets.append('MET')
#
# Target identified. Now model each
#
for target in targets:
import pKD_tools
resid = pKD_tools.get_resid_from_res(residue)
orgres = P.resname(residue)
filename = os.path.join(
mutdir, '%s:%s:%s.pdb' % (residue, orgres, target))
mutation = '%s:%s:%s' % (residue, orgres, target)
if not os.path.isfile(filename):
import Design_pKa_help
Design_pKa_help.make_mutation(self.pdbfile, mutation)
NP = Protool.structureIO()
NP.readpdb(filename)
NP.writepdb(filename, TER=None)
#
# Calculate the interaction energies
#
protein, routines, forcefield, apbs_setup, lig_titgrps = pdb2pka.pre_init(
pdbfilename=filename, ff='parse', ligand=None, verbose=1)
mypkaRoutines = pdb2pka.pKaRoutines(protein, routines,
forcefield, apbs_setup)
#
# Find our group
#
sp = residue.split(':')
chainid = sp[0]
resnum = int(sp[1])
mypkaRoutines.findTitratableGroups()
this_pKa = None
for pKa in mypkaRoutines.pKas:
print pKa.residue.resSeq, resnum
print pKa.residue.chainID, chainid
print pKa.residue.name, target
print pKa.pKaGroup.name, target
print '--------------'
print 'ChainID', pKa.residue.chainID
if pKa.residue.resSeq == resnum and pKa.residue.chainID == chainid and pKa.residue.name == target and pKa.pKaGroup.name == target:
#print 'Found group',pKa.residue.resSeq,pKa.pKaGroup.name
this_pKa = pKa
break
if not this_pKa:
raise Exception, 'Could not find inserted titratable group'
mypkaRoutines.get_interaction_energies_setup(this_pKa,
mode='pKD')
matrix = mypkaRoutines.matrix
#
# Dig the interaction energies out of the pdb2pka array
#
for titration1 in matrix[this_pKa].keys():
for state1 in matrix[this_pKa][titration1].keys():
grp_sub = matrix[this_pKa][titration1][state1]
if mypkaRoutines.is_charged(this_pKa, titration1,
state1):
for pKa2 in grp_sub.keys():
import string
chainID2 = pKa.residue.chainID
resid2 = '%s:%s' % (
chainID2,
string.zfill(pKa2.residue.resSeq, 4))
for titration2 in grp_sub[pKa2].keys():
for state2 in grp_sub[pKa2][
titration2].keys():
if mypkaRoutines.is_charged(
pKa2, titration2, state2):
#
# Both states are charged, so now we can pull the
# interaction energies out
#
if not self.data.has_key(mutation):
self.data[mutation] = {}
self.data[mutation][
resid2] = grp_sub[pKa2][
titration2][state2]
#
# Get the potentials at all atoms too
#
all_pots = mypkaRoutines.all_potentials[
this_pKa][titration1][state1]
sub_all_pots = all_pots[pKa2][
titration2][state2]
for atom in sub_all_pots.keys():
resid = mutation
import pKD_tools
resid2 = pKD_tools.get_resid_from_res(
atom)
atomname = atom.split(':')[
-1] #atom.name
if atomname[
0] == 'H' or atomname in [
'N', 'C', 'O'
]:
continue # Skip all H atoms and all non-CA backbone atoms to save memory
if not self.atom_data.has_key(
resid):
self.atom_data[resid] = {}
if not self.atom_data[
resid].has_key(resid2):
self.atom_data[resid][
resid2] = {}
self.atom_data[resid][resid2][
atomname] = abs(
sub_all_pots[atom])
return self.data, self.atom_data
def pdb2pka_desolv_backgr(self,residue):
"""Calculate the desolvation and background interaction energy for a residue"""
protein,routines,forcefield,apbs_setup,lig_titgrps = pdb2pka.pre_init(pdbfilename=self.pdbfile,
ff='parse',
ligand=None,
verbose=1)
mypkaRoutines = pdb2pka.pKaRoutines(protein, routines, forcefield,apbs_setup)
#
# Find our group
#
sp=residue.split(':')
chainid=sp[0]
#if chainid!='':
# raise Exception,'pKD cannot handle PDB files with ChainIDs!'
resnum=int(sp[1])
target=sp[2]
mypkaRoutines.findTitratableGroups()
this_pKa=None
for pKa in mypkaRoutines.pKas:
print pKa.residue
print pKa.uniqueid
print pKa.residue.resSeq,resnum, pKa.residue.chainID,'CID',chainid,pKa.residue.name,target,pKa.pKaGroup.name,target
#if pKa.residue.resSeq==resnum and pKa.residue.chainID==chainid and pKa.residue.name==target and pKa.pKaGroup.name==target:
if pKa.residue.resSeq==resnum and pKa.residue.chainID==chainid and pKa.residue.name==target and pKa.pKaGroup.name==target:
this_pKa=pKa
break
if not this_pKa:
raise Exception,'Could not find inserted titratable group'
mypkaRoutines.calculateBackground(onlypKa=pKa)
mypkaRoutines.calculateDesolvation(onlypKa=pKa)
#
# Get the intrinsic pKa
#
pKaGroup=pKa.pKaGroup
Gtype=pKa.pKaGroup.type
#
# We measure intrinsic pKa values against a single reference state
#
desolv=[]
backgr=[]
import math
ln10=math.log(10)
for titration in pKaGroup.DefTitrations:
#
# Find an uncharged reference state
#
ref_state=mypkaRoutines.neutral_ref_state[pKa][titration]
all_states=titration.allstates
all_states.sort()
for state in all_states:
if mypkaRoutines.is_charged(pKa,titration,state)==1:
dpKa_desolv=(pKa.desolvation[state]-pKa.desolvation[ref_state])/ln10
dpKa_backgr=(pKa.background[state]-pKa.background[ref_state])/ln10
#
# Make acid and base modifications
#
if Gtype=='base':
dpKa_desolv=-dpKa_desolv
dpKa_backgr=-dpKa_backgr
#
# Now calculate intrinsic pKa
#
backgr.append(dpKa_backgr)
desolv.append(dpKa_desolv)
intpKa=titration.modelpKa+dpKa_desolv+dpKa_backgr
#print 'Energy difference for %s -> %s [reference state] is %5.2f pKa units' %(state,ref_state,intpKa)
pKa.intrinsic_pKa[state]=intpKa
else:
#
# Neutral states - why do we treat them differently?
#
dpKa_desolv=(pKa.desolvation[state]-pKa.desolvation[ref_state])/ln10
dpKa_backgr=(pKa.background[state]-pKa.background[ref_state])/ln10
#
# Make acid and base modifications
#
if Gtype=='base':
dpKa_desolv=-dpKa_desolv
dpKa_backgr=-dpKa_backgr
backgr.append(dpKa_backgr)
desolv.append(dpKa_desolv)
dpKa=dpKa_desolv+dpKa_backgr
#print 'Energy difference for %s -> %s [reference state] is %5.2f kT' %(state,ref_state,dpKa)
pKa.intrinsic_pKa[state]=dpKa
#print '-----------------'
#
# One value is zero, so just get the avg of the rest
#
des_sum=0.0
for val in desolv:
des_sum=des_sum+val
des_sum=des_sum/float(len(desolv)-1)
#
bac_sum=0.0
for val in backgr:
bac_sum=bac_sum+val
bac_sum=bac_sum/float(len(backgr)-1)
return {residue:des_sum},{residue:bac_sum}
def pdb2pka_desolv_backgr(self, residue):
"""Calculate the desolvation and background interaction energy for a residue"""
protein, routines, forcefield, apbs_setup, lig_titgrps = pdb2pka.pre_init(
pdbfilename=self.pdbfile, ff='parse', ligand=None, verbose=1)
mypkaRoutines = pdb2pka.pKaRoutines(protein, routines, forcefield,
apbs_setup)
#
# Find our group
#
sp = residue.split(':')
chainid = sp[0]
#if chainid!='':
# raise Exception,'pKD cannot handle PDB files with ChainIDs!'
resnum = int(sp[1])
target = sp[2]
mypkaRoutines.findTitratableGroups()
this_pKa = None
for pKa in mypkaRoutines.pKas:
print pKa.residue
print pKa.uniqueid
print pKa.residue.resSeq, resnum, pKa.residue.chainID, 'CID', chainid, pKa.residue.name, target, pKa.pKaGroup.name, target
#if pKa.residue.resSeq==resnum and pKa.residue.chainID==chainid and pKa.residue.name==target and pKa.pKaGroup.name==target:
if pKa.residue.resSeq == resnum and pKa.residue.chainID == chainid and pKa.residue.name == target and pKa.pKaGroup.name == target:
this_pKa = pKa
break
if not this_pKa:
raise Exception, 'Could not find inserted titratable group'
mypkaRoutines.calculateBackground(onlypKa=pKa)
mypkaRoutines.calculateDesolvation(onlypKa=pKa)
#
# Get the intrinsic pKa
#
pKaGroup = pKa.pKaGroup
Gtype = pKa.pKaGroup.type
#
# We measure intrinsic pKa values against a single reference state
#
desolv = []
backgr = []
import math
ln10 = math.log(10)
for titration in pKaGroup.DefTitrations:
#
# Find an uncharged reference state
#
ref_state = mypkaRoutines.neutral_ref_state[pKa][titration]
all_states = titration.allstates
all_states.sort()
for state in all_states:
if mypkaRoutines.is_charged(pKa, titration, state) == 1:
dpKa_desolv = (pKa.desolvation[state] -
pKa.desolvation[ref_state]) / ln10
dpKa_backgr = (pKa.background[state] -
pKa.background[ref_state]) / ln10
#
# Make acid and base modifications
#
if Gtype == 'base':
dpKa_desolv = -dpKa_desolv
dpKa_backgr = -dpKa_backgr
#
# Now calculate intrinsic pKa
#
backgr.append(dpKa_backgr)
desolv.append(dpKa_desolv)
intpKa = titration.modelpKa + dpKa_desolv + dpKa_backgr
#print 'Energy difference for %s -> %s [reference state] is %5.2f pKa units' %(state,ref_state,intpKa)
pKa.intrinsic_pKa[state] = intpKa
else:
#
# Neutral states - why do we treat them differently?
#
dpKa_desolv = (pKa.desolvation[state] -
pKa.desolvation[ref_state]) / ln10
dpKa_backgr = (pKa.background[state] -
pKa.background[ref_state]) / ln10
#
# Make acid and base modifications
#
if Gtype == 'base':
dpKa_desolv = -dpKa_desolv
dpKa_backgr = -dpKa_backgr
backgr.append(dpKa_backgr)
desolv.append(dpKa_desolv)
dpKa = dpKa_desolv + dpKa_backgr
#print 'Energy difference for %s -> %s [reference state] is %5.2f kT' %(state,ref_state,dpKa)
pKa.intrinsic_pKa[state] = dpKa
#print '-----------------'
#
# One value is zero, so just get the avg of the rest
#
des_sum = 0.0
for val in desolv:
des_sum = des_sum + val
des_sum = des_sum / float(len(desolv) - 1)
#
bac_sum = 0.0
for val in backgr:
bac_sum = bac_sum + val
bac_sum = bac_sum / float(len(backgr) - 1)
return {residue: des_sum}, {residue: bac_sum}
