Hi Ben, I try to make a distance restraint between two atoms (protein and cofator) in a homodimer protein. However, I face another error: [flavios@localhost]$ mod9.13 model-mult-simmetry-bond.py Could not find platform independent libraries <prefix> Could not find platform dependent libraries <exec_prefix> Consider setting $PYTHONHOME to <prefix>[:<exec_prefix>] 'import site' failed; use -v for traceback Traceback (most recent call last): File "model-mult-simmetry-bond.py", line 40, in ? a.make() File "/usr/lib/modeller9.13/modlib/modeller/automodel/automodel.py", line 108, in make self.multiple_models(atmsel) File "/usr/lib/modeller9.13/modlib/modeller/automodel/automodel.py", line 212, in multiple_models self.outputs.append(self.single_model(atmsel, num)) File "/usr/lib/modeller9.13/modlib/modeller/automodel/automodel.py", line 308, in single_model self.model_analysis(atmsel, filename, out, num) File "/usr/lib/modeller9.13/modlib/modeller/automodel/automodel.py", line 350, in model_analysis self.user_after_single_model() File "model-mult-simmetry-bond.py", line 34, in user_after_single_model rsr.add(forms.gaussian(group=physical.xy_distance, feature=features.distance(at['NZ:38'], at['C4:382']), mean=1.5, stdev=0.1)) NameError: global name 'rsr' is not defined
I am certain that it must be an script error, but I do not know how to fix (I am not familiar with python script). My script is:
# Homology modeling with single template from modeller import * # Load standard Modeller classes from modeller.automodel import * # Load the automodel class
log.verbose() # request verbose output env = environ() # create a new MODELLER environment to build this model in
# directories for input atom files env.io.atom_files_directory = ['.', '../atom_files']
# Read in HETATM records from template PDBs env.io.hetatm = True env.io.water = True
class MyModel(automodel): def special_restraints(self, aln): rsr = self.restraints at = self.atoms # Constrain the A, B, C and D chains to be identical (but only restrain # the C-alpha atoms, to reduce the number of interatomic distances # that need to be calculated): s1 = selection(self.chains['A']).only_atom_types('CA') s2 = selection(self.chains['B']).only_atom_types('CA') self.restraints.symmetry.append(symmetry(s1, s2, 1))
def user_after_single_model(self): # Report on symmetry violations greater than 1A after building # each model: self.restraints.symmetry.report(1.0)
#Restrain between LYS and PLP (st. dev.=0.1) #Use a harmonic potential and X-Y distance group. rsr.add(forms.gaussian(group=physical.xy_distance, feature=features.distance(at['NZ:38'], at['C4:382']), mean=1.5, stdev=0.1)) rsr.add(forms.gaussian(group=physical.xy_distance, feature=features.distance(at['NZ:424'], at['C4:768']), mean=1.5, stdev=0.1))
a=MyModel(env, alnfile='AlRacem-mult.ali', knowns=('4A3Q', '1BD0'), sequence='AlRacem', assess_methods=(assess.DOPE, assess.GA341)) a.starting_model = 1 a.ending_model = 10 a.make()
# Get a list of all successfully built models from a.outputs ok_models = filter(lambda x: x['failure'] is None, a.outputs)
# Rank the models by DOPE score key = 'DOPE score' ok_models.sort(lambda a,b: cmp(a[key], b[key]))
# Get top model m = ok_models[0]
print "Top model 1: %s (DOPE score %.3f)" % (m['name'], m[key]) m = ok_models[1]
print "Top model 2: %s (DOPE score %.3f)" % (m['name'], m[key]) m = ok_models[2]
print "Top model 3: %s (DOPE score %.3f)" % (m['name'], m[key]) m = ok_models[3]
print "Top model 4: %s (DOPE score %.3f)" % (m['name'], m[key]) m = ok_models[4]
print "Top model 5: %s (DOPE score %.3f)" % (m['name'], m[key])
------------------------------------- Flavio Augusto Vicente Seixas Laboratory of Structural Biochemistry Department of Biochemistry Universidade Estadual de Maringá, PR, Brazil http://www.uem.br