To get an approximate model very quickly (to get a rough idea of what it looks like, or to confirm that the alignment is reasonable) call the AutoModel.very_fast() method before AutoModel.make(). This uses only a very limited amount of variable target function optimization with conjugate gradients, and thus is roughly 3 times faster than the default procedure.
Note that no randomization of the starting structure is done in this case, so only a single model can be produced.
This example also demonstrates the use of the assess_methods keyword, to request model assessment. In this case the GA341 method is requested. See section 4.1.1.
# Very fast comparative modeling by the AutoModel class from modeller import * from modeller.automodel import * # Load the AutoModel class #from modeller import soap_protein_od log.verbose() env = Environ() # directories for input atom files env.io.atom_files_directory = ['.', '../atom_files'] a = AutoModel(env, alnfile='alignment.ali', # alignment filename knowns='5fd1', # codes of the templates sequence='1fdx', # code of the target assess_methods=assess.GA341) # request GA341 model assessment # assess_methods=(assess.GA341, assess.DOPE)) # GA341 and DOPE # assess_methods=soap_protein_od.Scorer()) # assess with SOAP a.very_fast() # prepare for extremely fast optimization a.starting_model = 2 a.ending_model = 2 a.final_malign3d = True a.make() # make the comparative model