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 DOPELoopModel or DOPEHRLoopModel classes in place of LoopModel in each of the examples below. See Section 4.4 or Section 4.5 for more details.
# Comparative 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 comparative 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.