To automatically refine loop regions after building standard automodel models, simply use the loopmodel class rather than automodel; see the example below.
In many cases, you can obtain better quality loops (at the expense of more computer time) by using the newer DOPE-based loop modeling protocol. In this case, just use the dope_loopmodel or dopehr_loopmodel classes in place of loopmodel in each of the examples below. See Section 4.4 or Section 4.5 for more details.
# Homology modeling by the automodel class 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'] a = loopmodel(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.md_level = None # No refinement of model a.loop.starting_model = 1 # First loop model a.loop.ending_model = 4 # Last loop model a.loop.md_level = refine.fast # Loop model refinement level a.make() # do homology modeling
After generating the standard model(s), a number of loop models are generated for each model, from loopmodel.loop.starting_model to loopmodel.loop.ending_model. Each loop model is written out with the .BL extension. See section A.5 for more information.