Homology Modeling of ARS A

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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 Monoester Hydrolase no 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.

Single template modelling

In order to predict the structure using a single template structure, modeller needs pairwise sequence alignments in PIR format. Modeller provides two different methods to calculate pairwise sequence alignments. alignment.malign() uses classical dynamic programming to align two sequences. alignment.alig2dn() also uses a dynamic programming approach, but includes structural information to optimize the alignment (e.g. tries to place gaps outside of secondary structure elements). We applied both alignment methods and created eight pairwise sequnece alignments of the above templates with the target. The script used for this purpose is shown below:


from modeller import *
env = environ()
aln = alignment(env)
mdl = model(env, file='template_name', model_segment=('FIRST:@', 'END:'))
aln.append_model(mdl, align_codes='template_name', atom_files='template_name')
aln.append(file='1AUK.pir', align_codes='target_name')
aln.align2d()
aln.check()
aln.write(file='target-template-2d.ali', alignment_format='PIR') 
aln.malign()
aln.check()
aln.write(file='target-template.ali', alignment_format='PIR') 


For these alignments we constructed eight models, using the following script:


from modeller import *
from modeller.automodel import *    
log.verbose()   
env = environ() 
a = automodel(env,
             alnfile  = '1AUK-1FSU-2d.ali',   
             knowns   = '1FSU',              
             sequence = '1AUK',
             assess_methods=(assess.DOPE, assess.GA341))
a.starting_model= 1                
a.ending_model  = 1                
a.make()                          

We modified the paths and filenames in the scripts such that it matched our proteins of interest.

Next, we calculated RMSD and TM scores of the models to get a first impression on how much the models deviate from the original structure. The results are depicted in the table below.


Further on, we visualised the models using pymol. We load both structures into the program and performed a structural alignment to superimpose and compare them visually. The pymol commands and the images are shown below:


align 1AUK, MODEL
hide all
show cartoon
# select color of modelled structure via graphical interface
ray
cmd.png("MODEL.png")

Alignment method 1P49 2VQR 1FSU 3ED4
Classical
Dynamic Programming
real structure of 1AUK and structure of 1AUK modelled by modeller with tamplate 1P49, visualized in Pymol
real structure of 1AUK and structure of 1AUK modelled by modeller with tamplate 2VQR, visualized in Pymol
real structure of 1AUK and structure of 1AUK modelled by modeller with tamplate 1FSU, visualized in Pymol
real structure of 1AUK and structure of 1AUK modelled by modeller with tamplate 3ED4, visualized in Pymol
Dynamic Programming
with structural information
from the template
real structure of 1AUK and structure of 1AUK modelled by modeller with tamplate 1P49, visualized in Pymol
real structure of 1AUK and structure of 1AUK modelled by modeller with tamplate 2VQR, visualized in Pymol
real structure of 1AUK and structure of 1AUK modelled by modeller with tamplate 1FSU, visualized in Pymol
real structure of 1AUK and structure of 1AUK modelled by modeller with tamplate 3ED4, visualized in Pymol

3ED4

real structure of 3ED4 visualized in Pymol
Alignment method 3ED4A 3ED4B 3ED4C 3ED4D
Dynamic Programming
with structural information
from the template
real structure of 1AUK and structure of 1AUK modelled by modeller with tamplate 3ED4A, visualized in Pymol
real structure of 1AUK and structure of 1AUK modelled by modeller with tamplate 3ED4B, visualized in Pymol
real structure of 1AUK and structure of 1AUK modelled by modeller with tamplate 3ED4C, visualized in Pymol
real structure of 1AUK and structure of 1AUK modelled by modeller with tamplate 3ED4D, visualized in Pymol

Modification of Alignments

TM-scores and RMSD of the single template models

We downloaded the TMscore FORTRAN source code from http://zhanglab.ccmb.med.umich.edu/TM-score/ and compiled it using


gfortran -static -O3 -ffast-math -lm -o TMscore TMscore.f

TMscores were calculated as follows:


./TMscore MODEL.pdb REAL_STRUCTURE.pdb


PDB Identifier TM-score RMSD
Dynamic Programing with structural information
1P49 0.7960 -
2VQR 0.4825 -
1FSU 0.7146 -
3ED4 0.3881 -
3ED4A 0.7268 -
3ED4B 0.7251 -
3ED4C 0.6518 -
3ED4D 0.7303 -
Dynamic Programing without structural information
1P49 0.7731 -
2VQR 0.3183 -
1FSU 0.7223 -
3ED4 0.3122 -

Multiple Template Modeling

We calculated three models:

  • Model 1 was calculated from a multiple sequence alignment (MSA) of ARS A and the four proteins/chains, which yielded the best TM-score/RMSD in the single template modeling: 1FSU, 1P49, 2VQR, 3ED4D.
  • Model 2 was calculated from a MSA of ARS A and the three proteins/chains, which yielded the best TM-score/RMSD in the single template modeling: 1FSU, 1P49, 3ED4D.
  • Model 3 was calculated from a MSA of ARS A and the two proteins/chains, which yielded the best TM-score/RMSD in the single template modeling: 1P49, 3ED4D.
Model 1 Model 2 Model 3
real structure of 1AUK and structure of 1AUK modelled (Model 1), visualized in Pymol
real structure of 1AUK and structure of 1AUK modelled (Model 2), visualized in Pymol
real structure of 1AUK and structure of 1AUK modelled (Model 3), visualized in Pymol
PDB Identifier TM-score RMSD
model1 0.5409 -
model2 0.6701 -
model3 0.6819 -

Modification of Alignments