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[modeller_usage] Beta strand



Dear All,

Please, I cannot model a beta strand (predicted as such by PSI PRED) in a protein model, even adding further restraints. I think this
depends on the fact that this region is not structured in the templates.

Please, any suggestions (see .py below)?

Many thanks.

Claudia

-------

# Homology modeling with multiple templates
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']

class MyModel(automodel):
   def special_restraints(self, aln):
       rsr = self.restraints
       at = self.atoms
#       unpick('1:', '73:')
#       condense('1:', '73:')
#       Add some restraints from a file:
#       rsr.append(file='my_rsrs1.rsr')

#       Residues 49 through 55 should be an alpha helix:
        rsr.add(secondary_structure.alpha(self.residue_range('39:', '45:')))
#       Two beta-strands:
#       rsr.add(secondary_structure.strand(self.residue_range('1:', '5:')))
#       rsr.add(secondary_structure.strand(self.residue_range('19:', '26:')))
#       rsr.add(secondary_structure.strand(self.residue_range('33:', '35:')))
#       rsr.add(secondary_structure.strand(self.residue_range('55:', '58:')))
       rsr.add(secondary_structure.strand(self.residue_range('68:', '72:')))
#       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  = 'Alignment2.ali', # alignment filename
             knowns   = ('pco','Tas','gen','Rap'),     # codes of the templates
             sequence = 'sALK1')               # code of the target
a.starting_model= 1                 # index of the first model
a.ending_model  = 10                 # index of the last model
                                   # (determines how many models to calculate)
a.make()                            # do the actual homology modeling


--
Claudia Scotti, MD PhD
Department of Experimental Medicine
University of Pavia
Via Ferrata, 1
27100 Pavia
Italy
Tel. 0382 986335
Facs 0382 986893


Claudia Scotti
Dipartimento di Medicina Sperimentale
Sezione di Patologia Generale
Universita' di Pavia
Via Ferrata, 1
27100 Pavia
Italia
Tel. 0039 0382 986335/8/1
Facs 0039 0382 303673