Fabry:Sequence-based mutation analysis

From Bioinformatikpedia
Revision as of 23:16, 12 June 2012 by Rackersederj (talk | contribs) (Substitution matrices)

Fabry Disease » Sequence-based mutation analysis


The following analyses were performed on the basis of the α-Galactosidase A sequence. Please consult the journal for the commands used to generate the results.

Dataset preparation

Q279E
N215S
I289V
S65T
R356W
V316I
P323T
P40S
R118H
A143T

Amino acid properties

<figtable id="tab:aaProp"> Physicochemical properties of the chosen SNPs and changes of properties between wildtype (wt) and mutant (mt)

SNP wt
AA
wt
Side-chain polarity
wt
Side-chain charge (pH 7.4)
wt
Hydropathy index
wt
Residue Mass
mt
AA
mt
Side-chain polarity
mt
Side-chain charge (pH 7.4)
mt
Hydropathy index
mt
Residue Mass
change in polarity change in charge change in hydropathy change in residue mass
Q279E Q polar neutral −3.5 128.131 E polar negative −3.5 129.116 none neutral to negative −3.5-−3.5 0.985000000000014
N215S N polar neutral −3.5 114.104 S polar neutral −0.8 87.078 none none −0.8-−3.5 -27.026
I289V I nonpolar neutral 4.5 113.160 V nonpolar neutral 4.2 99.133 none none 4.2-4.5 -14.027
S65T S polar neutral −0.8 87.078 T polar neutral −0.7 101.105 none none −0.7-−0.8 14.027
R356W R polar positive −4.5 156.188 W nonpolar neutral −0.9 186.213 polar to nonpolar positive to neutral −0.9-−4.5 30.025
V316I V nonpolar neutral 4.2 99.133 I nonpolar neutral 4.5 113.160 none none 4.5-4.2 14.027
P323T P nonpolar neutral −1.6 97.117 T polar neutral −0.7 101.105 nonpolar to polar none −0.7-−1.6 3.988
P40S P nonpolar neutral −1.6 97.117 S polar neutral −0.8 87.078 nonpolar to polar none −0.8-−1.6 -10.039
R118H R polar positive −4.5 156.188 H polar pos(10%),neutr(90%) −3.2 137.142 none positive to pos(10%),neutr(90%) −3.2-−4.5 -19.046
A143T A nonpolar neutral 1.8 71.079 T polar neutral −0.7 101.105 nonpolar to polar none −0.7-1.8 30.026

</figtable>

Simple structural analysis

  • Now take into consideration where in the protein the mutation occurs and document: Create a picture with PyMOL showing the original and mutated residue in the protein. Use PyMOL for this. More thorough structural analyses will be introduced in the next task.

Location

<figtable id="tab:Location"> Physicochemical properties of the chosen SNPs and changes of properties between wildtype (wt) and mutant (mt)

SNP SecStruc Psipred SecStruc Psipred
long
SecStruc Reprof SecStruc Reprof
long
SecStruc DSSP SecStruc DSSP
long
Q279E H CCCCCCCHHHHHHHHHHHHHH H EECCCCCCHHHHHHHHHHHHH H CCCCC--HHHHHHHHHHHHHC
N215S H CCCCCCCCCCHHHHHCCCCCC H CECCCCCCCCHHHHHHHHHHH H HHHCCCC---HHHHCCC-CEE
I289V H HHHHHHHHHHHCCCEEEECCC H HHHHHHHHHHHHHCHHCCCCC C HHHHHHHHHHCC--EEE-C-C
S65T H CCCCCCCCCCHHHHHHHHHHH H CCCCCCCHHHHHHHHHHHHHH H CCC-CCCC-CHHHHHHHHHHH
R356W C CCEEEEEEECCCCCCEEEEEE C HHHHHHHHHHCCCCCCCCHHH - CEEEEEEEE---CCC-EEEEE
V316I H HHHCCCCHHHHHHCCCCCCCC E HHHHCCCCCEEEECCCCCCCC H HHHHHH-HHHHHHHC-CC---
P323T C HHHHHHCCCCCCCCCEEEEEC C CCEEEECCCCCCCCCCEECCC C HHHHHHHC-CC----EEEE-C
P40S C CCCCCCCCCCCCCCCCCCCCC C HHCCCCCCCCCCCHHHHHHEE - ---CC--CC--EEEECHHHHC
R118H H CCCCCCCCHHHHHHHHHHCCC H CCCCCCHHHHHHHHHHHCCCC H -CCC-CCHHHHHHHHHHHCC-
A143T C EECCCCCCCCCCCCCCCCHHH C EEECCCCCCCCCCCCCCCCCC C EEECCCE-CCCCE--CCCHHH

</figtable>

Substitution matrices

<figtable id="tab:Subsmatr"> Substitution values for all SNPs, both substitution matrices

SNP Value
BLOSUM62
Value
PAM250
Q279E 2 2
N215S 1 1
I289V 3 4
S65T 1 1
R356W -3 2
V316I 3 4
P323T -1 0
P40S -1 1
R118H 0 2
A143T 0 1

</figtable>


PSSM

  • Getting a bit closer to evolution you will have to create a PSSM (position specific scoring matrix) for your protein sequence using PSI-BLAST (5 iterations). How conserved are the WT residues in your mutant positions? How is the frequency of occurrence (conservation) for the mutant residue type? Anything interesting?

Multiple sequence alignment

  • And another step close to evolution: Identify all mammalian homologous sequences. Create a multiple sequence alignment for them with a method of your choice. Using this you can now calculate conservation for WT and mutant residues again. Compare this to the matrix- and PSSM-derived results.

Scoring methods

  • Finally, we use three different approaches to score our mutants.
    • SIFT
    • Polyphen2
    • SNAP is installed on the VirtualBox and should be used command-line only. -- As blast is the bottleneck of SNAP, and you are doing that anyway, we might as well look at all possible substitutions in the position of our mutations. This way we can learn much more about the nature of the given mutation: Is our mutation problematic because we introduce an unwanted effect, or because the WT residue is essential and by mutating we remove that?

Results and Conclusion

  • Compare ALL results and create an overview table.
  • Try to come up with a consensus between all the findings requested above.
  • Check whether you are right in the HGMD – were you able to predict a change?