def set_parameters(pdbfile=None,
design_statement=None,
min_dist=None,
num_muts=None):
#
# Set the parameters that are the same for all permutations
#
defaults = Design_pKa.get_defaults()
#
# PDB file
#
defaults['pdb'][0] = pdbfile
#
# pKa calculation parameters
#
defaults['pHstart'][0] = 0.1
defaults['pHstop'][0] = 12.0
defaults['pHstep'][0] = 0.05
defaults['pKMCsteps'][0] = 200000
#
# Design settings
#
# Target
#
defaults['pKas'][0] = design_statement
#
# Method
#
defaults['MC'][0] = 1
defaults['tabulated'][0] = 1
defaults['MCsteps'][0] = 0
defaults['TR'][0] = None
defaults['MC'][0] = 1
#
# Be not-so-noisy
#
defaults['silent'][0] = 2
#
# Minimum distance between target and mutation
#
defaults['min_target_dist'][0] = min_dist
#
# Max number of mutations
#
defaults['max_mutations'][0] = int(num_muts)
#
# Do not save the solutions
#
defaults['save_solutions'][0] = None
return defaults
def set_parameters(pdbfile=None,design_statement=None,min_dist=None,num_muts=None):
#
# Set the parameters that are the same for all permutations
#
defaults=Design_pKa.get_defaults()
#
# PDB file
#
defaults['pdb'][0]=pdbfile
#
# pKa calculation parameters
#
defaults['pHstart'][0]=0.1
defaults['pHstop'][0]=12.0
defaults['pHstep'][0]=0.05
defaults['pKMCsteps'][0]=200000
#
# Design settings
#
# Target
#
defaults['pKas'][0]=design_statement
#
# Method
#
defaults['MC'][0]=1
defaults['tabulated'][0]=1
defaults['MCsteps'][0]=0
defaults['TR'][0]=None
defaults['MC'][0]=1
#
# Be not-so-noisy
#
defaults['silent'][0]=2
#
# Minimum distance between target and mutation
#
defaults['min_target_dist'][0]=min_dist
#
# Max number of mutations
#
defaults['max_mutations'][0]=int(num_muts)
#
# Do not save the solutions
#
defaults['save_solutions'][0]=None
return defaults
def local_defaults(pdbfile,
target_residue,
target_dpKa,
min_dist,
pKMCsteps=None):
#
# Set the parameters that are the same for all permutations
#
defaults = Design_pKa.get_defaults()
# PDB file
defaults['pdb'][0] = pdbfile
#
# pKa calculation parameters
#
defaults['pHstart'][0] = 0.1
defaults['pHstop'][0] = 12.0
defaults['pHstep'][0] = 0.05
defaults['pKMCsteps'][0] = 200000
if pKMCsteps:
defaults['pKMCsteps'][0] = pKMCsteps
#
# Design settings
#
# Target
#
target = target_residue + '=' + target_dpKa
defaults['pKas'][0] = target
#
# Method
#
defaults['MC'][0] = 1
defaults['tabulated'][0] = 1
defaults['MCsteps'][0] = 0
#
# Be not-so-noisy
#
defaults['silent'][0] = 2
#
# Minimum distance between target and mutation
#
defaults['min_target_dist'][0] = min_dist
#
# Do not save the solutions
#
defaults['save_solutions'][0] = None
return defaults
def local_defaults(pdbfile,target_residue,target_dpKa,min_dist,pKMCsteps=None):
#
# Set the parameters that are the same for all permutations
#
defaults=Design_pKa.get_defaults()
# PDB file
defaults['pdb'][0]=pdbfile
#
# pKa calculation parameters
#
defaults['pHstart'][0]=0.1
defaults['pHstop'][0]=12.0
defaults['pHstep'][0]=0.05
defaults['pKMCsteps'][0]=200000
if pKMCsteps:
defaults['pKMCsteps'][0]=pKMCsteps
#
# Design settings
#
# Target
#
target=target_residue+'='+target_dpKa
defaults['pKas'][0]=target
#
# Method
#
defaults['MC'][0]=1
defaults['tabulated'][0]=1
defaults['MCsteps'][0]=0
#
# Be not-so-noisy
#
defaults['silent'][0]=2
#
# Minimum distance between target and mutation
#
defaults['min_target_dist'][0]=min_dist
#
# Do not save the solutions
#
defaults['save_solutions'][0]=None
return defaults
def get_this_defaults(pdbfile,target_residue,target_dpKa):
#
# Set the parameters that are the same for all permutations
#
import Design_pKa
defaults=Design_pKa.get_defaults()
# PDB file
defaults['pdb'][0]=pdbfile
#
# pKa calculation parameters
#
defaults['pHstart'][0]=0.0
defaults['pHstop'][0]=14.0
defaults['pHstep'][0]=0.05
defaults['MCsteps'][0]=1
defaults['pKMCsteps'][0]=50000
#
# Design settings
#
# Target
#
target=target_residue+'='+target_dpKa
defaults['pKas'][0]=target
#
# Be not-so-noisy
#
defaults['silent'][0]=1
#
# Minimum distance between target and mutation
#
defaults['min_target_dist'][0]=5.0
defaults['max_mutations'][0]=20.0
return defaults
def get_this_defaults(pdbfile, target_residue, target_dpKa):
#
# Set the parameters that are the same for all permutations
#
import Design_pKa
defaults = Design_pKa.get_defaults()
# PDB file
defaults['pdb'][0] = pdbfile
#
# pKa calculation parameters
#
defaults['pHstart'][0] = 0.0
defaults['pHstop'][0] = 14.0
defaults['pHstep'][0] = 0.05
defaults['MCsteps'][0] = 1
defaults['pKMCsteps'][0] = 50000
#
# Design settings
#
# Target
#
target = target_residue + '=' + target_dpKa
defaults['pKas'][0] = target
#
# Be not-so-noisy
#
defaults['silent'][0] = 1
#
# Minimum distance between target and mutation
#
defaults['min_target_dist'][0] = 5.0
defaults['max_mutations'][0] = 20.0
return defaults
def get_solutions(pdbfile,target_residue,target_dpKa,dpKas):
#
# Main routine.
# Get the solutions with MC_tab and then rescore them with a subset of
# the different methods
#
# Get solutions
#
import Design_pKa
defaults=Design_pKa.get_defaults()
defaults=get_this_defaults(pdbfile,target_residue,target_dpKa)
# Method
defaults['MC'][0]=1
defaults['tabulated'][0]=1
#
# Check if we already did this..
#
missing=None
for x in range(1,11):
if not dpKas.has_key(x):
missing=1
print 'Design solutions not calculated'
break
#
# Do it?
#
if missing:
solutions=Design_pKa.run_opt(defaults)
solution_keys=solutions.keys()
else:
solution_keys=dpKas.keys()
solution_keys.sort()
#
# Calculate pKa values using the other methods
#
# Define all the other methods that we will use
#
# First element is method, second is value of 'tabulated'
#
methods=[['TR',None],[None,None],['MC',None],['TR',1],['MC',1]]
for solution in solution_keys[:10]:
#
# Make sure the dictionary is ready
#
if not dpKas.has_key(solution):
dpKas[solution]={}
dpKas[solution]['mutations']=solutions[solution]['mutations']
realmut=None
for mutation in solutions[solution]['mutations']:
if mutation:
realmut=1
if not realmut:
continue
#
# Now calc dpKas with different methods
#
for method,tabulated in methods:
#
# Print info
#
print
print 'Calculating dpKa for %s with %s. Tabulated: %s' %(str(dpKas[solution]['mutations']),method,tabulated)
#
# Get defaults
#
defaults=get_this_defaults(pdbfile,target_residue,target_dpKa)
if method:
# Choose method
defaults[method][0]=1
#
# Set tabulated
#
defaults['tabulated'][0]=tabulated
#
# Set the general parameters
#
mutations=dpKas[solution]['mutations']
import string
#
# Remove all None elements from mutations
#
filtered_muts=[]
for mut in mutations:
if mut:
filtered_muts.append(mut)
#
# Set the mutations variable in defaults
#
defaults['mutations'][0]=string.join(filtered_muts,',')
# Calculate delta pkas
defaults['calc_dpka'][0]=1
#
# Set a more meaningful method name
#
method_name=method
if not method:
method_name='phi/ln10'
#
# Is this tabulated mode?
#
if tabulated:
method_name=method_name+'_tab'
#
# Get the dpKa(s)
#
if not dpKas[solution].has_key(method_name):
tmp=Design_pKa.run_opt(defaults)
#
# We should have only one key
#
keys=tmp.keys()
if len(keys)!=1:
print keys
raise 'Too many keys when calculating dpkas for one solution'
dpKas[solution][method_name]=tmp[keys[0]]
#
# Done
#
return dpKas
def __init__(self,pdbfile,user_params={},reporter_groups=None):
"""Read the pdbfile and the wild type pKa values
Define the reporter groups"""
# Topdir
import os
self.topdir=os.getcwd()
#
# Set the PDB file name
#
self.pdbfile=os.path.join(self.topdir,pdbfile)
import Protool
self.PI=Protool.structureIO()
self.PI.readpdb(self.pdbfile)
#
# Get the defaults from Design_pKa
#
import Design_pKa
defaults=Design_pKa.get_defaults()
self.params={}
for key in defaults.keys():
self.params[key]=defaults[key][0]
self.params['pKMCsteps']=20000
self.params['recalc_intpka']=True
self.params['recalc_intpka_dist']=20.0
self.params['save_temp_files']=False
#
# Change the values that the user specified
#
for u_par in user_params.keys():
self.params[u_par]=user_params[u_par]
#
# Set the pKa calc parms as a subset
#
self.pKarun_params={}
include=['indi','dbcrit','ion','allow_unknown_atoms','unknown_crg','unknown_rad']
import copy
for key in include:
self.pKarun_params[key]=copy.copy(self.params[key])
#
# Set the output handler
#
self.O=Design_pKa.verbose(self.params['verbose'])
#
# Instantiate the pKa_info class and instruct it to save nothing
#
import Design_pKa_help
print 'pKa_info, PDB file',self.pdbfile
self.pKa_info=Design_pKa_help.pKa_info(pdbfile=self.pdbfile,parent=self,PBEsolver=self.params['PBEsolver'],save_file=False)
#
# Set the calculation routine to CPP
#
import pKa_MC
self.pKaCALC=pKa_MC.pKa_calculation_class(pdbfile=self.pdbfile,pKa_info=self.pKa_info,params=self.params,parent=self)
self.pKaCALC.set_MC_CPP()
#
# Re-calculate the wild type pKa values
#
print 'Calculating wild type pKa values'
self.wt_pKas,self.wt_prot_states=self.pKaCALC.calc_wt_pkas()
#
# Set the reporter groups
#
if reporter_groups:
self.reporter_groups=reporter_groups
else:
self.reporter_groups=self.wt_pKas.keys()
return
def get_solutions(pdbfile, target_residue, target_dpKa, dpKas):
#
# Main routine.
# Get the solutions with MC_tab and then rescore them with a subset of
# the different methods
#
# Get solutions
#
import Design_pKa
defaults = Design_pKa.get_defaults()
defaults = get_this_defaults(pdbfile, target_residue, target_dpKa)
# Method
defaults['MC'][0] = 1
defaults['tabulated'][0] = 1
#
# Check if we already did this..
#
missing = None
for x in range(1, 11):
if not dpKas.has_key(x):
missing = 1
print 'Design solutions not calculated'
break
#
# Do it?
#
if missing:
solutions = Design_pKa.run_opt(defaults)
solution_keys = solutions.keys()
else:
solution_keys = dpKas.keys()
solution_keys.sort()
#
# Calculate pKa values using the other methods
#
# Define all the other methods that we will use
#
# First element is method, second is value of 'tabulated'
#
methods = [['TR', None], [None, None], ['MC', None], ['TR', 1], ['MC', 1]]
for solution in solution_keys[:10]:
#
# Make sure the dictionary is ready
#
if not dpKas.has_key(solution):
dpKas[solution] = {}
dpKas[solution]['mutations'] = solutions[solution]['mutations']
realmut = None
for mutation in solutions[solution]['mutations']:
if mutation:
realmut = 1
if not realmut:
continue
#
# Now calc dpKas with different methods
#
for method, tabulated in methods:
#
# Print info
#
print
print 'Calculating dpKa for %s with %s. Tabulated: %s' % (str(
dpKas[solution]['mutations']), method, tabulated)
#
# Get defaults
#
defaults = get_this_defaults(pdbfile, target_residue, target_dpKa)
if method:
# Choose method
defaults[method][0] = 1
#
# Set tabulated
#
defaults['tabulated'][0] = tabulated
#
# Set the general parameters
#
mutations = dpKas[solution]['mutations']
import string
#
# Remove all None elements from mutations
#
filtered_muts = []
for mut in mutations:
if mut:
filtered_muts.append(mut)
#
# Set the mutations variable in defaults
#
defaults['mutations'][0] = string.join(filtered_muts, ',')
# Calculate delta pkas
defaults['calc_dpka'][0] = 1
#
# Set a more meaningful method name
#
method_name = method
if not method:
method_name = 'phi/ln10'
#
# Is this tabulated mode?
#
if tabulated:
method_name = method_name + '_tab'
#
# Get the dpKa(s)
#
if not dpKas[solution].has_key(method_name):
tmp = Design_pKa.run_opt(defaults)
#
# We should have only one key
#
keys = tmp.keys()
if len(keys) != 1:
print keys
raise 'Too many keys when calculating dpkas for one solution'
dpKas[solution][method_name] = tmp[keys[0]]
#
# Done
#
return dpKas
def run_sugelm(pdbfile):
"""Run the SugELM command"""
#
# Get the name of the PDB file
#
import os
pdb_name = os.path.split(pdbfile)[1]
pdb_dir = os.path.split(pdbfile)[0]
topdir = os.getcwd()
#
# Check if pKa values were calculated for this file
#
import pKaTool.pKaIO
X = pKaTool.pKaIO.pKaIO(pdbfile)
if not X.calculation_completed:
print 'pKa calculation not completed for %s' % pdbfile
return None
#
# Read the pKa values
#
pkas = X.readpka()
target = pkas.keys()[2]
#
# Create the SUGELM file
#
import Design_pKa
tparams = Design_pKa.get_defaults()
params = {}
for key in tparams.keys():
params[key] = tparams[key][0]
#
# Set the other parameters
#
params['pHstart'] = 0.1
params['pHstop'] = 12.0
params['pHstep'] = 0.05
params['pKMCsteps'] = 200000,
params['pKas'] = target + '=+1.0'
params['MC'] = 0
params['TR'] = 0
params['min_target_dist'] = 1.0
params['save_solutions'] = None
params['silent'] = 0
params['pdb'] = pdbfile
params['generate_mutations'] = True
#
# Log message
#
import sys
print 'Starting pKD mutation preparation'
sys.stdout.flush()
try:
X = Design_pKa.Design_pKa(params)
X.get_interaction_energies()
print 'Calculated interaction energies'
except:
send_email('*****@*****.**', 'SUGELM failed for ' + pdbfile)
return None
#
# Write a flag file to alert the scheduler
#
fd = open(os.path.join(pdb_dir, 'ready'), 'w')
fd.write('SUGELM is done\n')
fd.close()
return 1
def __init__(self, pdbfile, user_params={}, reporter_groups=None):
"""Read the pdbfile and the wild type pKa values
Define the reporter groups"""
# Topdir
import os
self.topdir = os.getcwd()
#
# Set the PDB file name
#
self.pdbfile = os.path.join(self.topdir, pdbfile)
import Protool
self.PI = Protool.structureIO()
self.PI.readpdb(self.pdbfile)
#
# Get the defaults from Design_pKa
#
import Design_pKa
defaults = Design_pKa.get_defaults()
self.params = {}
for key in defaults.keys():
self.params[key] = defaults[key][0]
self.params['pKMCsteps'] = 20000
self.params['recalc_intpka'] = True
self.params['recalc_intpka_dist'] = 20.0
self.params['save_temp_files'] = False
#
# Change the values that the user specified
#
for u_par in user_params.keys():
self.params[u_par] = user_params[u_par]
#
# Set the pKa calc parms as a subset
#
self.pKarun_params = {}
include = [
'indi', 'dbcrit', 'ion', 'allow_unknown_atoms', 'unknown_crg',
'unknown_rad'
]
import copy
for key in include:
self.pKarun_params[key] = copy.copy(self.params[key])
#
# Set the output handler
#
self.O = Design_pKa.verbose(self.params['verbose'])
#
# Instantiate the pKa_info class and instruct it to save nothing
#
import Design_pKa_help
print 'pKa_info, PDB file', self.pdbfile
self.pKa_info = Design_pKa_help.pKa_info(
pdbfile=self.pdbfile,
parent=self,
PBEsolver=self.params['PBEsolver'],
save_file=False)
#
# Set the calculation routine to CPP
#
import pKa_MC
self.pKaCALC = pKa_MC.pKa_calculation_class(pdbfile=self.pdbfile,
pKa_info=self.pKa_info,
params=self.params,
parent=self)
self.pKaCALC.set_MC_CPP()
#
# Re-calculate the wild type pKa values
#
print 'Calculating wild type pKa values'
self.wt_pKas, self.wt_prot_states = self.pKaCALC.calc_wt_pkas()
#
# Set the reporter groups
#
if reporter_groups:
self.reporter_groups = reporter_groups
else:
self.reporter_groups = self.wt_pKas.keys()
return
def run_sugelm(pdbfile):
"""Run the SugELM command"""
#
# Get the name of the PDB file
#
import os
pdb_name=os.path.split(pdbfile)[1]
pdb_dir=os.path.split(pdbfile)[0]
topdir=os.getcwd()
#
# Check if pKa values were calculated for this file
#
import pKaTool.pKaIO
X=pKaTool.pKaIO.pKaIO(pdbfile)
if not X.calculation_completed:
print 'pKa calculation not completed for %s' %pdbfile
return None
#
# Read the pKa values
#
pkas=X.readpka()
target=pkas.keys()[2]
#
# Create the SUGELM file
#
import Design_pKa
tparams=Design_pKa.get_defaults()
params={}
for key in tparams.keys():
params[key]=tparams[key][0]
#
# Set the other parameters
#
params['pHstart']=0.1
params['pHstop']=12.0
params['pHstep']=0.05
params['pKMCsteps']=200000,
params['pKas']=target+'=+1.0'
params['MC']=0
params['TR']=0
params['min_target_dist']=1.0
params['save_solutions']=None
params['silent']=0
params['pdb']=pdbfile
params['generate_mutations']=True
#
# Log message
#
import sys
print 'Starting pKD mutation preparation'
sys.stdout.flush()
try:
X=Design_pKa.Design_pKa(params)
X.get_interaction_energies()
print 'Calculated interaction energies'
except:
send_email('*****@*****.**','SUGELM failed for '+pdbfile)
return None
#
# Write a flag file to alert the scheduler
#
fd=open(os.path.join(pdb_dir,'ready'),'w')
fd.write('SUGELM is done\n')
fd.close()
return 1
