Building a model from multiple templates

It is straightforward a to build a model using information from multiple templates — simply provide an alignment between all of the templates and your target sequence, and list all of the templates in the knowns argument, as demonstrated below. MODELLER will automatically combine the templates; there is no need to superpose the structures (although you can request that this is done by setting automodel.initial_malign3d).

Example: examples/automodel/model-multiple.py

# Comparative modeling with multiple templates
from modeller import *              # Load standard Modeller classes
from modeller.automodel import *    # Load the automodel class

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 = automodel(env,
              alnfile  = 'align-multiple.ali', # alignment filename
              knowns   = ('5fd1', '1bqx'),     # 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

Example: examples/automodel/align-multiple.ali


C; A multiple alignment in the PIR format; used in tutorial

>P1;5fd1
structureX:5fd1:1    :A:106  :A:ferredoxin:Azotobacter vinelandii: 1.90: 0.19
AFVVTDNCIKCKYTDCVEVCPVDCFYEGPNFLVIHPDECIDCALCEPECPAQAIFSEDEVPEDMQEFIQLNAELA
EVWPNITEKKDPLPDAEDWDGVKGKLQHLER*

>P1;1bqx
structureN:1bqx:   1 :A: 77  :A:ferredoxin:Bacillus schlegelii:-1.00:-1.00
AYVITEPCIGTKCASCVEVCPVDCIHEGEDQYYIDPDVCIDCGACEAVCPVSAIYHEDFVPEEWKSYIQKNRDFF
KK-----------------------------*

>P1;1fdx
sequence:1fdx:1    : :54   : :ferredoxin:Peptococcus aerogenes: 2.00:-1.00
AYVINDSC--IACGACKPECPVNIIQGS--IYAIDADSCIDCGSCASVCPVGAPNPED-----------------
-------------------------------*



Automatic builds 2018-05-30