Difference between revisions of "Workflow homology modelling glucocerebrosidase"

From Bioinformatikpedia
(MODELLER)
(Modelling of the Target Structure)
Line 20: Line 20:
 
# Run the following Python script with command '<code>mod9.9 model.py</code>' to model the structure of the target sequence:
 
# Run the following Python script with command '<code>mod9.9 model.py</code>' to model the structure of the target sequence:
 
<code>
 
<code>
from modeller.automodel import *
+
from modeller.automodel import * <br/>
log.verbose()
+
log.verbose()<br/>
env = environ()
+
env = environ()<br/>
  +
env.io.atom_files_directory = ''<br/>
 
  +
a = automodel (env, alnfile = '1OGS_2NT0.ali', knowns = '2NT0', sequence = '1OGS')<br/>
env.io.atom_files_directory = ''
 
  +
a.starting_model = 1<br/>
a = automodel (env,
 
  +
a.ending_model = 1<br/>
alnfile = '1OGS_2NT0.ali',
 
  +
a.make()<br/>
knowns = '2NT0',
 
sequence = '1OGS')
 
a.starting_model = 1
 
a.ending_model = 1
 
a.make()
 
 
</code>
 
</code>

Revision as of 08:52, 10 June 2011

MODELLER

Preparation of the Alignment File

  1. Save target protein sequence in PIR-format: target.pir
  2. Save PDB-file of template sequence: template:pdb
    If PDB-file consists of several chains: split pdb file with the help of splitpdb (note that minor changes are needed, so that the ATOM coordinates are listed in the resulting PDB-file instead of HETATOMS).
  3. Run the following Python script with command 'mod9.9 align.py' to create target template alignment in PIR-format:

log.verbose()
env = environ()
aln = alignment(env)
mdl= model(env, file='template')
aln.append_model(mdl, align_codes='template')
aln.append(file='target.pir', align_codes=('target'))
aln.align(gap_penalties_1d=(-600,-400))
aln.write(file='target_template.ali', alignment_format='PIR')
aln.write(file='target_template.pap', alignment_format='PAP')

Modelling of the Target Structure

  1. Run the following Python script with command 'mod9.9 model.py' to model the structure of the target sequence:

from modeller.automodel import * 
log.verbose()
env = environ()
env.io.atom_files_directory =
a = automodel (env, alnfile = '1OGS_2NT0.ali', knowns = '2NT0', sequence = '1OGS')
a.starting_model = 1
a.ending_model = 1
a.make()