Difference between revisions of "Tutorial"

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(Evaluate 3D models)
(Evaluate 3D models)
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  model_profile.pdb -1549.1603 -3196.3570   -1.1504 -236.0000 -13.6659
 
  model_profile.pdb -1549.1603 -3196.3570   -1.1504 -236.0000 -13.6659
 
  
  
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  FRST | RAPDF | Solvation | Hydrogen | Torsion
 
  FRST | RAPDF | Solvation | Hydrogen | Torsion
  
 +
 +
For comparison the experimental structure of the target obtains the following energies:
 +
 +
2ANL.pdb (Target) -26691.5315 -8822.3390 -23.3529 -224.0000 -11.8836
  
  
1DP5.pdb -45897.7199 -8866.2600 -17.3132 -237.0000 -76.9300
+
According to these results the profile alignment is worse than the default alignment. Moreover the model generated from the default alignment appears to be more stable of the native structure of the Target protein (PDB id 2ANL), one explanation could be that SwissModel favour stability when generating structures. The general idea is that with Victor you can easily generate different alignments (changing algorithms and/or parameters) and you can effectively test them by evaluating the quality of the 3D models built from these alignments.
2ANL.pdb -26691.5315 -8822.3390 -23.3529 -224.0000 -11.8836
+
  
 
=Build loops=
 
=Build loops=

Revision as of 14:40, 20 August 2014

In the sample folder are available all input and output files used in this tutorial.

Target/Template alignment

Supposing you have already found a template candidate, you need to align it against your target sequence. In this dummy example we take the sequences of two homologous proteins both endowed with 3D structure. That allows us to compare different type of Victor alignments with the "exact" one derived from the structural alignment.

The two proteins are:

  • Target = 2ANL (chain A)
  • Template = 1DP5 (chain A)

The two structure superimpose quite well (RMSD 2.03 A) considering the low level of sequence identity (28.06%). This is the resulting sequence alignment after the 3D alignment done by FATCAT:

3d align.png

Alignment cartoon.png

rigth


The subali application let you choose from very different type of algorithms, strategies and parameters. The fist step is to create a file (i.e. pair.fasta) including both the target and template Fasta sequences together like that:

>2ANL:A Target
SENDVIELDDVANLMFYGEGEVGDNHQKFMLIFDTGSANLWVPSKKCNSIGCSTKHLYDSSKSKSYEKDGTKVEITYGSG
TVRGFFSKDLVTLGYLSLPYKFIEVTDTDDLEPLYTAAEFDGILGLGWKDLSIGSIDPIVVELKNQNKIDQALFTFYLPV
HDKHSGYLTIGGIEEKFYEGELTYEKLNHDLFWQVDLDVNFGKTSMEKANVIVDSGTSTITAPTSFINKFFKDLNVIKVP
FLPFYITTCNNKDMPTLEFKSANNTYTLEPEYYMEPLLDIDDTLCMLYILPVDIDKNTFILGDPFMRKYFTVFDYDKESI
GFAVAKN
>1DP5:A Template
GGHDVPLTNYLNAQYYTDITLGTPPQNFKVILDTGSSNLWVPSNECGSLACFLHSKYDHEASSSYKANGTEFAIQYGTGS
LEGYISQDTLSIGDLTIPKQDFAEATSEPGLTFAFGKFDGILGLGYDTISVDKVVPPFYNAIQQDLLDEKRFAFYLGDTS
KDTENGGEATFGGIDESKFKGDITWLPVRRKAYWEVKFEGIGLGDEYAELESHGAAIDTGTSLITLPSGLAEMINAEIGA
KKGWTGQYTLDCNTRDNLPDLIFNFNGYNFTIGPYDYTLEVSGSCISAITPMDFPEPVGPLAIVGDAFLRKYYSIYDLGN
NAVGLAKAI


Sequence to sequence alignment

Supposing we call the input file with the target and template sequences pair.fasta than by running the following command you obtain a basic alignment with the default parameters (see Features):

subali --in pair.fasta

The resulting alignment is this:

Default align.png


Profile to profile alignment

Most of the time including evolutionary information helps improving the alignment quality. In this example we used command line PsiBlast to calculate profiles both for the target and the template sequences. The profiles have to be generated in a specific format using the option -outfmt 4 (6 in older versions of Blast, see Features). In our case the commands are:

psiblast -num_iterations 3 -db /db/blastdb/nr90 -query 2anl_A.fasta -out 2anl_A.psi -outfmt 4

psiblast -num_iterations 3 -db /db/blastdb/nr90 -query 1dp5_A.fasta -out 1dp5_A.psi -outfmt 4


Then to generate the alignment simply run:

subali --in pair.fasta --pro1 2anl_A.psi --pro2 1dp5_A.psi


Profile align.png

Evaluate 3D models

Based on the alignment created in the previous section we can easily model the target. In our case, for simplicity, we used the SwissModel online service. In the sample folder you can find two files:

  • model_default.pdb - The model obtained from the default sequence-to-sequence alignment.
  • model_profile.pdb - The model obtained from the profile-to-profile alignment.


By using the following commands for the two models:

frst -v -i model_default.pdb
frst -v -i model_profile.pdb


We obtain the following output (last line):

model_default.pdb	-29822.6749	-6266.6390	 -18.1340	-223.0000	 -46.3974
model_profile.pdb	-1549.1603	-3196.3570	  -1.1504	-236.0000	 -13.6659


Where numbers represent the following energies:

FRST | RAPDF | Solvation | Hydrogen | Torsion


For comparison the experimental structure of the target obtains the following energies:

2ANL.pdb (Target)	-26691.5315	-8822.3390	 -23.3529	-224.0000	 -11.8836


According to these results the profile alignment is worse than the default alignment. Moreover the model generated from the default alignment appears to be more stable of the native structure of the Target protein (PDB id 2ANL), one explanation could be that SwissModel favour stability when generating structures. The general idea is that with Victor you can easily generate different alignments (changing algorithms and/or parameters) and you can effectively test them by evaluating the quality of the 3D models built from these alignments.

Build loops