If there is an equivalent disulfide bridge in any of the templates aligned with the target, automodel will automatically generate appropriate disulfide bond restraints2.3 for you (by using the model.patch_ss_templates() command).
Explicit manual restraints can be added by the model.patch() command using the CHARMM topology file DISU patching residue. You must redefine the automodel.special_patches() routine to add these or other patches.
It is better to use model.patch_ss_templates() rather than model.patch() where possible because the dihedral angles are restrained more precisely by using the templates than by using the general rules of stereochemistry.
Some CHARMM parameter files have a multiple dihedral entry for the disulfide dihedral angle χ3 that consists of three individual entries with periodicities of 1, 2 and 3. This is why you see three feature restraints for a single disulfide in the output of the selection.energy() command.
Note that the residue numbers that you patch refer to the model, not the templates. See Section 2.2.6 for more discussion.
# Comparative modeling by the automodel class from modeller import * # Load standard Modeller classes from modeller.automodel import * # Load the automodel class # Redefine the special_patches routine to include the additional disulfides # (this routine is empty by default): class MyModel(automodel): def special_patches(self, aln): # A disulfide between residues 8 and 45: self.patch(residue_type='DISU', residues=(self.residues['8'], self.residues['45'])) 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'] a = MyModel(env, alnfile = 'alignment.ali', # alignment filename knowns = '5fd1', # codes of the templates sequence = '1fdx') # code of the target a.starting_model= 1 # index of the first model a.ending_model = 1 # index of the last model # (determines how many models to calculate) a.make() # do the actual comparative modeling