Difference between revisions of "TSD Homology modelling protocol"
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===Visualisation with Pymol=== |
===Visualisation with Pymol=== |
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SWISS-MODEL provides a model file containing the error coding in the B factor column. |
SWISS-MODEL provides a model file containing the error coding in the B factor column. |
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− | This error coding was adopted for the superimposed model. The command therefore is: |
+ | This error coding was adopted for the superimposed reference-model illustration. The command therefore is: |
spectrum b, red_blue, <model-name> |
spectrum b, red_blue, <model-name> |
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Revision as of 13:43, 4 June 2012
Back to results.
Contents
Template selection
HHpred and COMA were employed in order to complement the 3 sequence identity classes.
SWISS-MODEL
The modelling was performed with the webserver of SWISS-MODEL in automated mode and alignment mode.
Visualisation with Pymol
SWISS-MODEL provides a model file containing the error coding in the B factor column. This error coding was adopted for the superimposed reference-model illustration. The command therefore is:
spectrum b, red_blue, <model-name>
iTasser
Modeller
Get all necessary files <source lang="bash"> cd ../input/
- HEXA sequence
wget http://www.uniprot.org/uniprot/P06865.fasta sed -ri 's/^>.+/>P06865/' P06865.fasta
- Reference structure
wget http://www.pdb.org/pdb/files/2GJX.pdb
- Templates
wget http://www.pdb.org/pdb/files/2GK1.pdb wget http://www.pdb.org/pdb/files/3GH5.pdb wget http://www.pdb.org/pdb/files/1O7A.pdb </source>
Create the pairwise alignments, using Modeller internal methods <source lang=python>
- !/usr/bin/env python
from modeller import *
OUT='../prediction/'
def makeAli(targetId, targetFile, templateId, templateFile, templateChain) :
env = environ() aln = alignment(env) mdl = model(env, file=templateFile, model_segment=('FIRST:'+templateChain, 'LAST:'+templateChain)) aln.append_model(mdl, align_codes=templateId, atom_files=templateFile) aln.append(file=targetFile, align_codes=targetId, alignment_format='FASTA') aln.align2d() aln.check() aln.write(file=OUT+targetId+templateId+'-2d.ali', alignment_format='PIR') aln.malign() aln.check() aln.write(file=OUT+targetId+templateId+'.ali', alignment_format='PIR') return
makeAli('P06865','../input/P06865.fasta','2GK1', '../input/2GK1.pdb','A' ) makeAli('P06865','../input/P06865.fasta','1O7A', '../input/1O7A.pdb','D' ) makeAli('P06865','../input/P06865.fasta','3GH5', '../input/3GH5.pdb','A' ) </source>
Call modeller on a single alignment file <source lang="python">
- !/usr/bin/env python
from modeller import * from modeller.automodel import * import os import sys
ali = sys.argv[1] strc = sys.argv[2] wd = sys.argv[3]
os.chdir(wd)
env = environ()
a = automodel(env,
alnfile = ali, knowns = strc, sequence = 'P06865', assess_methods=(assess.DOPE, assess.GA341))
a.starting_model= 1 a.ending_model = 1 a.make() </source>
Caller script for all modeller predictions
<source lang="bash">
- !/bin/bash
- Ugly hotfix so we can work in our own folders later on (who hardcodes filepaths AND doesn't allow output folders?!)
sed -i 's|X:../input|X:../../input|' ../prediction/*.ali
PDBS=( 2GK1 1O7A 3GH5 )
for pdb in "${PDBS[@]}" #Gotta love bash syntax do
echo "$pdb" mkdir -p ../prediction/$pdb/ mkdir -p ../prediction/${pdb}_2D/
./createModel.py ../P06865${pdb}.ali ${pdb} ../prediction/$pdb/ &> ../prediction/$pdb/log ./createModel.py ../P06865${pdb}-2d.ali ${pdb} ../prediction/${pdb}_2D/ &> ../prediction/${pdb}_2D/log
done
mkdir -p ../prediction/3GH5_ED/ ./createModel.py ../P068653GH5_edited.pir 3GH5 ../prediction/3GH5_ED/ &> ../prediction/3GH5_ED/log </source>
Evaluation
6Å RMSD using Pymol
- Load template and model
- For each select active site
- Expand selections by 6Å
- Extract selections into objects
- Align objects