Getting a very fast and approximate model

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.

Example: examples/automodel/model-fast.py

# 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