Difference between revisions of "Homology Modeling of ARS A"
(→Proteins used as templates) |
(→Proteins used as templates) |
||
Line 30: | Line 30: | ||
In order to predict the structure, modeller needs pairwise sequence alignments in PIR format. Modeller provides two different methods to calculate pairwise sequence alignments. |
In order to predict the structure, modeller needs pairwise sequence alignments in PIR format. Modeller provides two different methods to calculate pairwise sequence alignments. |
||
− | <code> |
+ | <code> |
− | from modeller import * |
+ | from modeller import * |
+ | env = environ() |
||
+ | aln = alignment(env) |
||
+ | mdl = model(env, file='2VQR', model_segment=('FIRST:@', 'END:')) |
||
+ | aln.append_model(mdl, align_codes='2VQR', atom_files='2VQR') |
||
+ | aln.append(file='1AUK.pir', align_codes='1AUK') |
||
+ | aln.align2d() |
||
+ | aln.check() |
||
+ | aln.write(file='1AUK-2VQR-2d.ali', alignment_format='PIR') |
||
+ | aln.malign() |
||
+ | aln.check() |
||
+ | aln.write(file='1AUK-2VQR.ali', alignment_format='PIR') |
||
+ | </code> |
||
+ | |||
− | env = environ() |
||
+ | We wrote a python script (''align_all.py'') - using the example python script ''aln_append_model.py'' - to achieve this. Then we wrote one Python script (using the example script ''model-default.py'') per protein to build the model, using the alignments and the pdb structures. |
||
− | #env.io.atom_files_directory = ["/apps/modeller9.9/bin/examples/commands/", "/home/student/Desktop/homo_modeller/pdbs"] |
||
− | |||
− | aln = alignment(env) |
||
− | mdl = model(env, file='2VQR', model_segment=('FIRST:@', 'END:')) |
||
− | aln.append_model(mdl, align_codes='2VQR', atom_files='2VQR') |
||
− | aln.append(file='1AUK.pir', align_codes='1AUK') |
||
− | aln.align2d() |
||
− | aln.check() |
||
− | |||
− | aln.write(file='1AUK-2VQR-2d.ali', alignment_format='PIR') |
||
− | |||
− | aln.malign() |
||
− | aln.check() |
||
− | aln.write(file='1AUK-2VQR.ali', alignment_format='PIR') |
||
− | </code> |
||
− | |||
− | We wrote a python script (''align_all.py'') - using the example python script ''aln_append_model.py'' - to achieve this. Then we wrote one Python script (using the example script ''model-default.py'') per protein to build the model, using the alignments and the pdb structures. |
||
We executed the following commands: |
We executed the following commands: |
||
Revision as of 10:42, 9 June 2011
HHpred
We used the webserver and
Modeller
Proteins used as templates
We identified the following proteins (see Alignment TASK) as potential targets for homology modeling:used the following
SeqIdentifier | Seq Identity (from TASK 2) | source | Protein function | True homolog (HSSP) | Seq Identity (pairw. ali.) |
---|---|---|---|---|---|
1P49 | 39.0% | Homo Sapiens | Steryl-Sulfatase | yes | 31.9% |
1FSU | 28.0% | Homo Sapiens | Arylsulfatase B | yes | 26.5% |
2VQR | 20.0% | Rhizobium leguminosarum | Sulfatase | Monoester Hydrolase | 20.3% |
3ED4 | 32.0% | Escherichia coli | Arylsulfatase | yes | 27.7% |
Our potential templates, identified by the database searches contain all homologs with known structure, regarding to HSSP.
In order to predict the structure, modeller needs pairwise sequence alignments in PIR format. Modeller provides two different methods to calculate pairwise sequence alignments.
from modeller import *
env = environ()
aln = alignment(env)
mdl = model(env, file='2VQR', model_segment=('FIRST:@', 'END:'))
aln.append_model(mdl, align_codes='2VQR', atom_files='2VQR')
aln.append(file='1AUK.pir', align_codes='1AUK')
aln.align2d()
aln.check()
aln.write(file='1AUK-2VQR-2d.ali', alignment_format='PIR')
aln.malign()
aln.check()
aln.write(file='1AUK-2VQR.ali', alignment_format='PIR')
We wrote a python script (align_all.py) - using the example python script aln_append_model.py - to achieve this. Then we wrote one Python script (using the example script model-default.py) per protein to build the model, using the alignments and the pdb structures.
We executed the following commands:
/apps/modeller9.9/bin/mod9.9 align_all.py
/apps/modeller9.9/bin/mod9.9 predict1p49.py
/apps/modeller9.9/bin/mod9.9 predict2vqr.py
/apps/modeller9.9/bin/mod9.9 predict1fsu.py
/apps/modeller9.9/bin/mod9.9 predict3ed4.py
We modified the paths and filenames in the scripts such that it matched our proteins of interest.
1P49 | 2VQR | 1FSU | 3ED4 |