Hi , I am not able to model beta sheets even if i am using model_addrsr,py file. Can anyone please help me out..!! This is the script file i used.

# Addition of restraints to the default ones from modeller import * from modeller.automodel import * # Load the automodel class

log.verbose() env = environ()

# directories for input atom files env.io.atom_files_directory = ['.', '../atom_files']

class MyModel(automodel): def special_restraints(self, aln): rsr = self.restraints at = self.atoms # Add some restraints from a file: # rsr.append(file='my_rsrs1.rsr')

# Residues 20 through 30 should be an alpha helix: # rsr.add(secondary_structure.alpha(self.residue_range('269:', '302:'))) # rsr.add(secondary_structure.alpha(self.residue_range('171:', '189:'))) # rsr.add(secondary_structure.alpha(self.residue_range('171:', '189:'))) # rsr.add(secondary_structure.alpha(self.residue_range('171:', '189:'))) # rsr.add(secondary_structure.alpha(self.residue_range('209:', '228:'))) # rsr.add(secondary_structure.alpha(self.residue_range('236:', '255:'))) # rsr.add(secondary_structure.alpha(self.residue_range('335:', '353:'))) # Two beta-strands: # rsr.add(secondary_structure.strand(self.residue_range('148:', '154:'))) rsr.add(secondary_structure.strand(self.residue_range('65:', '75:'))) # An anti-parallel sheet composed of the two strands: # rsr.add(secondary_structure.sheet(at['N:1'], at['O:14'], # sheet_h_bonds=-5)) # Use the following instead for a *parallel* sheet: # rsr.add(secondary_structure.sheet(at['N:1'], at['O:9'], # sheet_h_bonds=5))

# Restrain the specified CA-CA distance to 10 angstroms (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['CA:35'], # at['CA:40']), # mean=10.0, stdev=0.1))

a = MyModel(env, alnfile = 'target-temp.ali', # alignment filename knowns = 'template', # codes of the templates sequence = 'target') # code of the target a.starting_model= 1 # index of the first model a.ending_model = 2 # index of the last model # (determines how many models to calculate) a.make() # do homology modeling

# Get a list of all successfully built models from a.outputs ok_models = filter(lambda x: x['failure'] is None, a.outputs)