Fabry:Sequence-based mutation analysis

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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).
Used abbreviation in this table:
AA: Amino Acid, Pol: Side-chain polarity, Charge: Side-chain charge at pH 7.4, HI: Hydropathy index, RM: Residue Mass, iP: isoelectric point

SNP wt
AA
wt
Pol
wt
Charge
wt
HI
wt
RM
wt
iP
mt
AA
mt
Pol
mt
Charge
mt
HI
mt
RM
mt
iP
change in Pol change in Charge change in HI change in RM change in iP
Q279E Q polar neutral -3.5 128.131 5.65 E polar negative -3.5 129.116 3.15 none neutral to negative 0 0.985 -2.5
N215S N polar neutral -3.5 114.104 5.41 S polar neutral -0.8 87.078 5.68 none none -2.7 -27.026 0.27
I289V I nonpolar neutral 4.5 113.160 6.05 V nonpolar neutral 4.2 99.133 6.00 none none -0.3 -14.027 -0.045
S65T S polar neutral -0.8 87.078 5.68 T polar neutral -0.7 101.105 5.60 none none 0.1 14.027 -0.08
R356W R polar positive -4.5 156.188 10.76 W nonpolar neutral -0.9 186.213 5.89 polar to nonpolar positive to neutral 3.6 30.025 -4.87
V316I V nonpolar neutral 4.2 99.133 6.00 I nonpolar neutral 4.5 113.160 6.05 none none 0.3 14.027 0.05
P323T P nonpolar neutral -1.6 97.117 6.30 T polar neutral -0.7 101.105 5.60 nonpolar to polar none 0.9 3.988 -0.7
P40S P nonpolar neutral -1.6 97.117 6.30 S polar neutral -0.8 87.078 5.68 nonpolar to polar none 0.8 -10.039 -0.62
R118H R polar positive -4.5 156.188 10.76 H polar pos(10%),
neutr(90%)
-3.2 137.142 7.60 none positive to pos(10%),
neutr(90%)
1.3 -19.046 -3.16
A143T A nonpolar neutral 1.8 71.079 6.01 T polar neutral -0.7 101.105 5.60 nonpolar to polar none -2.5 30.026 -0.41

</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.

Secondary Structure

<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, all three substitution matrices

SNP Value
BLOSUM62
Value
PAM1
Value
PAM250
Q279E 3 27 2
N215S 1 20 1
I289V 4 33 4
S65T 2 38 1
R356W -4 8 2
V316I 4 57 4
P323T -2 4 0
P40S -1 12 1
R118H 0 10 2
A143T 0 32 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

SIFT

<figtable id="tab:Sift"> Sift Scores

SNP Prediction Sift Score Sequences represented at this position
P40S AFFECT PROTEIN FUNCTION 0.00 41
S65T AFFECT PROTEIN FUNCTION 0.01 45
R118H be TOLERATED 0.06 48
A143T AFFECT PROTEIN FUNCTION 0.01 48
N215S AFFECT PROTEIN FUNCTION 0.01 48
Q279E AFFECT PROTEIN FUNCTION 0.00 48
I289V AFFECT PROTEIN FUNCTION 0.05 48
V316I be TOLERATED 0.75 48
P323T AFFECT PROTEIN FUNCTION 0.01 48
R356W AFFECT PROTEIN FUNCTION 0.01 47

</figtable>

Median sequence conservation: 2.99

SIFT

Polyphen2

<figtable id="tab:Polyphen"> Polyphen Scores

SNP rs ID Sec Struc Prediction pph2 Class pph2 Prob pph2 FPR pph2 TPR pph2 FDR
Q279E rs28935485 H probably damaging deleterious 0.983 0.0387 0.745 0.0657
N215S rs28935197 . benign neutral 0.048 0.167 0.941 0.194
I289V ? H probably damaging deleterious 0.975 0.0436 0.762 0.072
S65T ? . probably damaging deleterious 0.995 0.0277 0.681 0.0521
R356W ? . probably damaging deleterious 1 0.00026 0.00018 0.0109
V316I ? H benign neutral 0.308 0.113 0.904 0.144
P323T ? T possibly damaging deleterious 0.612 0.091 0.872 0.124
P40S ? . probably damaging deleterious 1 0.00026 0.00018 0.0109
R118H ? H benign neutral 0.015 0.209 0.956 0.229
A143T ? T probably damaging deleterious 1 0.00026 0.00018 0.0109

</figtable>

Polyphen2 [1]

SNAP

    • 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?


<figtable id="tab:Overview"> Overview over all features
Used abbreviation in this table:
AA: Amino Acid, Pol: Side-chain polarity, Charge: Side-chain charge at pH 7.4, HI: Hydropathy index, RM: Residue Mass, iP: isoelectric point

SNP change in Pol change in Charge change in HI change in RM change in iP SecStruc Psipred SecStruc Reprof SecStruc DSSP Value
BLOSUM62
Value
PAM1
Value
PAM250
Sift Score pph2 Class pph2 Prob
A143T nonpolar to
polar
none -2.5 30.026 -0.41 C C C 0 32 1 0.01 deleterious 1
R356W polar to
nonpolar
positive to
neutral
3.6 30.025 -4.87 C C - -4 8 2 0.01 deleterious 1
I289V none none -0.3 -14.027 -0.05 H H C 4 33 4 0.05 deleterious 0.975
V316I none none 0.3 14.027 0.05 H E H 4 57 4 0.75 neutral 0.308
R118H none positive to pos(10%),
neutr(90%)
1.3 -19.046 -3.16 H H H 0 10 2 0.06 neutral 0.015
N215S none none 2.7 -27.026 0.27 H H H 1 20 1 0.01 neutral 0.048
Q279E none neutral to
negative
0 0.99 -2.5 H H H 3 27 2 0.00 deleterious 0.983
P40S nonpolar to
polar
none 0.8 -10.039 -0.62 C C - -1 12 1 0.00 deleterious 1
S65T none none 0.1 14.027 -0.08 H H H 2 38 1 0.01 deleterious 0.995
P323T nonpolar to
polar
none 0.9 3.988 -0.7 C C C -2 4 0 0.01 deleterious 0.612

</figtable>


References

<references/>