def calculate_desolvation(self, filename=None, updater=None):
"""Calculate the desolvation energies for all titratable groups"""
if not getattr(self, 'atom_close', None):
self.get_atoms_around()
#
#
titgrps = self.titratable_groups
residues = titgrps.keys()
residues.sort()
self.desolv = {}
for residue in residues:
if updater:
updater('Calculating for %s' % residue)
for group in titgrps[residue]:
name1 = self.get_titgroup_name(residue, group)
#
# Calculate the desolvation
#
self.desolv[name1] = 12.5 * math.pow(self.atom_close[name1],
1.7)
#
# Write the file
#
if filename:
import pKaIO
X = pKaIO.pKaIO()
X.desolv = self.desolv
X.write_desolv(filename + '.DESOLV.DAT')
return self.desolv
def calculate_desolvation(self,filename=None,updater=None):
"""Calculate the desolvation energies for all titratable groups"""
if not getattr(self,'atom_close',None):
self.get_atoms_around()
#
#
titgrps=self.titratable_groups
residues=titgrps.keys()
residues.sort()
self.desolv={}
for residue in residues:
if updater:
updater('Calculating for %s' %residue)
for group in titgrps[residue]:
name1=self.get_titgroup_name(residue,group)
#
# Calculate the desolvation
#
self.desolv[name1]=12.5*math.pow(self.atom_close[name1],1.7)
#
# Write the file
#
if filename:
import pKaIO
X=pKaIO.pKaIO()
X.desolv=self.desolv
X.write_desolv(filename+'.DESOLV.DAT')
return self.desolv
def _get_CCPS_population(options,args):
"""recalculate titration curves and get the pH-dependent population of select protonation states"""
import pKaIO
pdbfile=args[0]
MCsteps=options.MCsteps
pHstep=options.pHstep
pHstart=options.pHstart
pHend=options.pHstop
IO=pKaIO.pKaIO(pdbfile)
import pKa.pKa_MC
print 'Recalculating wild type titration curves'
pKa_params={'pHstart':pHstart,'pHstop':pHend,'pHstep':pHstep,'pKMCsteps':MCsteps,'verbose':1}
pKaCALC=pKa.pKa_MC.pKa_calculation_class(pdbfile,pKa_info=None,params=pKa_params)
pKaCALC.set_MC_CPP()
#
#
#
groups=pKaCALC.MC.desolv.keys()
groups.sort()
if options.list_groups:
print 'The PDB file contains these titratable groups:\n',groups
return
#
# Set the protonation state
#
CCPS={}
for spec in options.ccps:
split=spec.split('=')
group=split[0]
charge=abs(int(split[1]))
if CCPS.has_key(group):
raise Exception('You cannot specify two protonation states for a single group: %s' %group)
if not group in groups:
raise Exception('Unknown group: %s' %group)
CCPS[group]=charge
#
# Construct monitor_states
#
monitor_states=[]
for group in groups:
if CCPS.has_key(group):
monitor_states.append(CCPS[group])
else:
monitor_states.append(-99)
#
# Calculate the pKa values
#
print 'pHrange: step: %.2f start: %.2f, end: %.2f. MCsteps: %e ' %(pHstep,pHstart,pHend,MCsteps)
wtpkas,titration_curves=pKaCALC.MC.calc_pKas(MCsteps,pHstep,pHstart,pHend,0,
monitor_states=monitor_states)
pHs=pKaCALC.MC.pH[:]
CCPS=pKaCALC.MC.CCPS_pop[:]
if options.show_plot:
import matplotlib.pyplot as plt
plt.plot(pHs,CCPS,'ro-',linewidth=2.0)
plt.show()
return pHs,CCPS
def load_matrix(self):
"""Load a matrix file"""
import tkFileDialog, os
filename=tkFileDialog.askopenfilename(defaultextension='.MATRIX.DAT',
initialdir=os.getcwd(),
parent=self.Dcontrol,
filetypes=[("pKa MATRIX file","*.MATRIX.DAT"),
("All files","*.*")])
if filename:
import pKaIO
self.M=pKaIO.pKaIO()
self.pkamatrix=self.M.read_matrix(filename)
for res1 in self.pkamatrix.keys():
for res2 in self.pkamatrix.keys():
print res1,res2,self.pkamatrix[res1][res2][0]-self.pkamatrix[res1][res2][1]-self.pkamatrix[res1][res2][2]+self.pkamatrix[res1][res2][3]
return
def load_matrix(self):
"""Load a matrix file"""
import tkFileDialog, os
filename = tkFileDialog.askopenfilename(
defaultextension=".MATRIX.DAT",
initialdir=os.getcwd(),
parent=self.Dcontrol,
filetypes=[("pKa MATRIX file", "*.MATRIX.DAT"), ("All files", "*.*")],
)
if filename:
import pKaIO
self.M = pKaIO.pKaIO()
self.pkamatrix = self.M.read_matrix(filename)
for res1 in self.pkamatrix.keys():
for res2 in self.pkamatrix.keys():
print res1, res2, self.pkamatrix[res1][res2][0] - self.pkamatrix[res1][res2][1] - self.pkamatrix[
res1
][res2][2] + self.pkamatrix[res1][res2][3]
return
def _get_CCPS_population(options, args):
"""recalculate titration curves and get the pH-dependent population of select protonation states"""
import pKaIO
pdbfile = args[0]
MCsteps = options.MCsteps
pHstep = options.pHstep
pHstart = options.pHstart
pHend = options.pHstop
IO = pKaIO.pKaIO(pdbfile)
import pKa.pKa_MC
print 'Recalculating wild type titration curves'
pKa_params = {
'pHstart': pHstart,
'pHstop': pHend,
'pHstep': pHstep,
'pKMCsteps': MCsteps,
'verbose': 1
}
pKaCALC = pKa.pKa_MC.pKa_calculation_class(pdbfile,
pKa_info=None,
params=pKa_params)
pKaCALC.set_MC_CPP()
#
#
#
groups = pKaCALC.MC.desolv.keys()
groups.sort()
if options.list_groups:
print 'The PDB file contains these titratable groups:\n', groups
return
#
# Set the protonation state
#
CCPS = {}
for spec in options.ccps:
split = spec.split('=')
group = split[0]
charge = abs(int(split[1]))
if CCPS.has_key(group):
raise Exception(
'You cannot specify two protonation states for a single group: %s'
% group)
if not group in groups:
raise Exception('Unknown group: %s' % group)
CCPS[group] = charge
#
# Construct monitor_states
#
monitor_states = []
for group in groups:
if CCPS.has_key(group):
monitor_states.append(CCPS[group])
else:
monitor_states.append(-99)
#
# Calculate the pKa values
#
print 'pHrange: step: %.2f start: %.2f, end: %.2f. MCsteps: %e ' % (
pHstep, pHstart, pHend, MCsteps)
wtpkas, titration_curves = pKaCALC.MC.calc_pKas(
MCsteps, pHstep, pHstart, pHend, 0, monitor_states=monitor_states)
pHs = pKaCALC.MC.pH[:]
CCPS = pKaCALC.MC.CCPS_pop[:]
if options.show_plot:
import matplotlib.pyplot as plt
plt.plot(pHs, CCPS, 'ro-', linewidth=2.0)
plt.show()
return pHs, CCPS
def calculate_background(self, filename=None, updater=None):
"""Calculate the background interaction energy"""
if not getattr(self, 'atom_close', None):
self.get_atoms_around()
#
# Calc the background ene
#
titgrps = self.titratable_groups
residues = titgrps.keys()
residues.sort()
self.background = {}
count = 0
for residue in residues:
if updater:
updater('Calculating for %s' % residue)
for group in titgrps[residue]:
name1 = self.get_titgroup_name(residue, group)
#
# Calculate the background interaction energy
#
# First approximation: we count potential hydrogen bonds
#
hbonds = 0
tot_bonds = 0
#
# Get the sign right
#
counted = {}
sign = group['charge']
for atom in self.close_atoms_list[name1]:
for atom2 in group['atoms']:
#
# First for full-strength hydrogen bonds
#
hb = self.is_hydrogen_bond(atom, residue + ':' + atom2,
2.2, 3.5)
if hb == 1:
if not counted.has_key(atom):
#print 'Accepting from',atom,residue+':'+atom2
hbonds = hbonds - 1 * sign
elif hb == 2:
if not counted.has_key(atom):
#print 'Donating to',atom,residue+':'+atom2
hbonds = hbonds + 1 * sign
#
if hb:
tot_bonds = tot_bonds + 1
#counted[atom]=1
#
# Then for weaker - purely electrostatic interactions
# These are only counted half
#
hb = self.is_hydrogen_bond(atom, residue + ':' + atom2,
3.5, 7.0)
weak_hb = 0.3
if hb == 1:
if not counted.has_key(atom):
#print 'Accepting from',atom,residue+':'+atom2
hbonds = hbonds - weak_hb * sign
elif hb == 2:
if not counted.has_key(atom):
#print 'Donating to',atom,residue+':'+atom2
hbonds = hbonds + weak_hb * sign
#
if hb:
tot_bonds = tot_bonds + weak_hb
#counted[atom]=1
#
#
#print 'Hbonds: %3d, tot_bonds: %3d' %(hbonds,tot_bonds)
self.background[name1] = 0.69 * hbonds * math.pow(
self.atom_close[name1], 1)
#
# Write the file
#
if filename:
import pKaIO
X = pKaIO.pKaIO()
X.backgr = self.background
X.write_backgr(filename + '.BACKGR.DAT')
return self.background
def calculate_matrix(self, filename=None, eps=8, exdi=80, updater=None):
"""
# This function calculates a simplified version of the charge-charge interaction
# energy matrix
#
#
# Calculate the factor that converts formal charges and distances in A into kT energies
# eps is the dielectric constant
"""
factor = (1.0 /
(4.0 * pi * e0)) * (e * e / A) * 1.0 / eps * 1.0 / (k * T)
#
# Get the fast scaled accessibility
#
acc = self.get_atoms_around(updater=updater)
#
# And now we calculate the matrix
#
import string
if not getattr(self, 'titratable_groups', None):
self.get_titratable_groups()
self.matrix = {}
self.distmatrix = {}
titgrps = self.titratable_groups
residues = titgrps.keys()
residues.sort()
#
# Get the total number of calcs
#
ncalcs = len(residues) * len(residues)
count = 0
for residue in residues:
for group in titgrps[residue]:
name1 = self.get_titgroup_name(residue, group)
if not self.matrix.has_key(name1):
self.matrix[name1] = {}
if not self.distmatrix.has_key(name1):
self.distmatrix[name1] = {}
#
# Calculate distance from center of atoms
#
x = 0.0
y = 0.0
z = 0.0
for atom in group['atoms']:
x = x + self.atoms[residue + ':' + atom]['X'] / float(
len(group['atoms']))
y = y + self.atoms[residue + ':' + atom]['Y'] / float(
len(group['atoms']))
z = z + self.atoms[residue + ':' + atom]['Z'] / float(
len(group['atoms']))
#
# Now for the second residue
#
for residue2 in titgrps.keys():
for group2 in titgrps[residue2]:
if not updater is None:
updater('%d of %d (%4.1f%% completed)' %
(count, ncalcs,
float(count) / float(ncalcs) * 100.0))
count = count + 1
name2 = self.get_titgroup_name(residue2, group2)
if self.matrix[name1].has_key(name2):
continue
#
# Get center of atoms for this res
#
x2 = 0.0
y2 = 0.0
z2 = 0.0
for atom in group2['atoms']:
x2 = x2 + self.atoms[residue2 + ':' +
atom]['X'] / float(
len(group2['atoms']))
y2 = y2 + self.atoms[residue2 + ':' +
atom]['Y'] / float(
len(group2['atoms']))
z2 = z2 + self.atoms[residue2 + ':' +
atom]['Z'] / float(
len(group2['atoms']))
#
# Get the distance
#
v1 = numpy.array([x, y, z])
v2 = numpy.array([x2, y2, z2])
import geometry
dist = geometry.length(v1 - v2)
if dist != 0:
crg1 = group['charge']
crg2 = group2['charge']
ene = factor * float(crg1 * crg2) / (math.pow(
dist, 1.5))
#
# Get the influence of the acc
#
acc_frac = math.sqrt(acc[name1] * acc[name2])
acc_frac = math.pow(acc_frac, 2.0)
ene = ene * 1.99 * acc_frac + (
1.0 -
acc_frac) * float(eps) / float(exdi) * ene
else:
ene = 0.0
#if ene:
# print '%20s - %20s: %7.3f' %(name1,name2,ene)
self.matrix[name1][name2] = [ene, 0.0, 0.0, 0.0]
self.distmatrix[name1][name2] = dist
if not self.matrix.has_key(name2):
self.matrix[name2] = {}
self.matrix[name2] = {}
self.matrix[name2][name1] = [ene, 0.0, 0.0, 0.0]
self.distmatrix[name2][name1] = dist
#
# Write the matrix file
#
if filename:
import pKaIO
X = pKaIO.pKaIO()
X.matrix = self.matrix
X.write_matrix(filename + '.MATRIX.DAT')
return self.matrix
def calculate_background(self,filename=None,updater=None):
"""Calculate the background interaction energy"""
if not getattr(self,'atom_close',None):
self.get_atoms_around()
#
# Calc the background ene
#
titgrps=self.titratable_groups
residues=titgrps.keys()
residues.sort()
self.background={}
count=0
for residue in residues:
if updater:
updater('Calculating for %s' %residue)
for group in titgrps[residue]:
name1=self.get_titgroup_name(residue,group)
#
# Calculate the background interaction energy
#
# First approximation: we count potential hydrogen bonds
#
hbonds=0
tot_bonds=0
#
# Get the sign right
#
counted={}
sign=group['charge']
for atom in self.close_atoms_list[name1]:
for atom2 in group['atoms']:
#
# First for full-strength hydrogen bonds
#
hb=self.is_hydrogen_bond(atom,residue+':'+atom2,2.2,3.5)
if hb==1:
if not counted.has_key(atom):
#print 'Accepting from',atom,residue+':'+atom2
hbonds=hbonds-1*sign
elif hb==2:
if not counted.has_key(atom):
#print 'Donating to',atom,residue+':'+atom2
hbonds=hbonds+1*sign
#
if hb:
tot_bonds=tot_bonds+1
#counted[atom]=1
#
# Then for weaker - purely electrostatic interactions
# These are only counted half
#
hb=self.is_hydrogen_bond(atom,residue+':'+atom2,3.5,7.0)
weak_hb=0.3
if hb==1:
if not counted.has_key(atom):
#print 'Accepting from',atom,residue+':'+atom2
hbonds=hbonds-weak_hb*sign
elif hb==2:
if not counted.has_key(atom):
#print 'Donating to',atom,residue+':'+atom2
hbonds=hbonds+weak_hb*sign
#
if hb:
tot_bonds=tot_bonds+weak_hb
#counted[atom]=1
#
#
#print 'Hbonds: %3d, tot_bonds: %3d' %(hbonds,tot_bonds)
self.background[name1]=0.69*hbonds*math.pow(self.atom_close[name1],1)
#
# Write the file
#
if filename:
import pKaIO
X=pKaIO.pKaIO()
X.backgr=self.background
X.write_backgr(filename+'.BACKGR.DAT')
return self.background
def calculate_matrix(self,filename=None,eps=8,exdi=80,updater=None):
"""
# This function calculates a simplified version of the charge-charge interaction
# energy matrix
#
#
# Calculate the factor that converts formal charges and distances in A into kT energies
# eps is the dielectric constant
"""
factor=(1.0/(4.0*pi*e0))*(e*e/A)*1.0/eps*1.0/(k*T)
#
# Get the fast scaled accessibility
#
acc=self.get_atoms_around(updater=updater)
#
# And now we calculate the matrix
#
import string
if not getattr(self,'titratable_groups',None):
self.get_titratable_groups()
self.matrix={}
self.distmatrix={}
titgrps=self.titratable_groups
residues=titgrps.keys()
residues.sort()
#
# Get the total number of calcs
#
ncalcs=len(residues)*len(residues)
count=0
for residue in residues:
for group in titgrps[residue]:
name1=self.get_titgroup_name(residue,group)
if not self.matrix.has_key(name1):
self.matrix[name1]={}
if not self.distmatrix.has_key(name1):
self.distmatrix[name1]={}
#
# Calculate distance from center of atoms
#
x=0.0
y=0.0
z=0.0
for atom in group['atoms']:
x=x+self.atoms[residue+':'+atom]['X']/float(len(group['atoms']))
y=y+self.atoms[residue+':'+atom]['Y']/float(len(group['atoms']))
z=z+self.atoms[residue+':'+atom]['Z']/float(len(group['atoms']))
#
# Now for the second residue
#
for residue2 in titgrps.keys():
for group2 in titgrps[residue2]:
if not updater is None:
updater('%d of %d (%4.1f%% completed)' %(count,ncalcs,float(count)/float(ncalcs)*100.0))
count=count+1
name2=self.get_titgroup_name(residue2,group2)
if self.matrix[name1].has_key(name2):
continue
#
# Get center of atoms for this res
#
x2=0.0
y2=0.0
z2=0.0
for atom in group2['atoms']:
x2=x2+self.atoms[residue2+':'+atom]['X']/float(len(group2['atoms']))
y2=y2+self.atoms[residue2+':'+atom]['Y']/float(len(group2['atoms']))
z2=z2+self.atoms[residue2+':'+atom]['Z']/float(len(group2['atoms']))
#
# Get the distance
#
v1=numpy.array([x,y,z])
v2=numpy.array([x2,y2,z2])
import geometry
dist=geometry.length(v1-v2)
if dist!=0:
crg1=group['charge']
crg2=group2['charge']
ene=factor*float(crg1*crg2)/(math.pow(dist,1.5))
#
# Get the influence of the acc
#
acc_frac=math.sqrt(acc[name1]*acc[name2])
acc_frac=math.pow(acc_frac,2.0)
ene=ene*1.99*acc_frac+(1.0-acc_frac)*float(eps)/float(exdi)*ene
else:
ene=0.0
#if ene:
# print '%20s - %20s: %7.3f' %(name1,name2,ene)
self.matrix[name1][name2]=[ene,0.0,0.0,0.0]
self.distmatrix[name1][name2]=dist
if not self.matrix.has_key(name2):
self.matrix[name2]={}
self.matrix[name2]={}
self.matrix[name2][name1]=[ene,0.0,0.0,0.0]
self.distmatrix[name2][name1]=dist
#
# Write the matrix file
#
if filename:
import pKaIO
X=pKaIO.pKaIO()
X.matrix=self.matrix
X.write_matrix(filename+'.MATRIX.DAT')
return self.matrix
