Difference between revisions of "Workflow homology modelling glucocerebrosidase"
From Bioinformatikpedia
(→Modelling of the Target Structure) |
(→Preparation of the Alignment File) |
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# Save PDB-file of template sequence: template:pdb |
# Save PDB-file of template sequence: template:pdb |
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#: If PDB-file consists of several chains: split pdb file with the help of [http://structure.usc.edu/splitpdb/ splitpdb] (note that minor changes are needed, so that ATOM coordinates get listed in the resulting PDB-file instead of HETATOMS). |
#: If PDB-file consists of several chains: split pdb file with the help of [http://structure.usc.edu/splitpdb/ splitpdb] (note that minor changes are needed, so that ATOM coordinates get listed in the resulting PDB-file instead of HETATOMS). |
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| − | # Run the following Python script with command '<code>mod9.9 align.py</code>' to create |
+ | # Run the following Python script with command '<code>mod9.9 align.py</code>' to create a target-template alignment in PIR-format: |
<code> |
<code> |
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log.verbose()<br/> |
log.verbose()<br/> |
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Revision as of 09:03, 10 June 2011
MODELLER
Preparation of the Alignment File
- Save target protein sequence in PIR-format: target.pir
- 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).
- 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
- 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()
