Workflow homology modelling glucocerebrosidase

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Revision as of 11:57, 11 June 2011 by Braunt (talk | contribs) (Preparation of the Alignment File)

Detailed workflow of the different homology modelling approaches for glucocerebrosidase. Return to overview.

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 ATOM coordinates get listed in the resulting PDB-file instead of HETATOMS).
  3. Run the following Python script with command 'mod9.9 align.py' to create a 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:
    Note that all files (alignment- and structure file) must be in the same folder

from modeller.automodel import * 
log.verbose()
env = environ()
env.io.atom_files_directory =
a = automodel (env, alnfile = 'target_template.ali', knowns = 'template', sequence = 'target')
a.starting_model = 1
a.ending_model = 1
a.make()

I-TASSER

SWISS-MODELLER

Automated Mode

The automated mode should only be used, if target and template share more than 50% of sequence identity.

Alignment Mode

To create the Alignments needed as input, the tool ClustalW2 was used in this case.