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