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)