Difference between revisions of "Sequence-based mutation analysis of ARSA"

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==== Discussion ====
 
* ''Mutation 1:'' The scores are high in all substituion matrices. Thus, this substitution is likely to have no effect.
 
* ''Mutation 2:'' All scores are low. Thus, the properties of the amino acids are should differ and a the substitution should rather be neutral than non-neutral.
 
* ''Mutation 3:''
 
* ''Mutation 4:''
 
* ''Mutation 5:''
 
* ''Mutation 6:''
 
* ''Mutation 7:''
 
* ''Mutation 8:''
 
* ''Mutation 9:''
 
* ''Mutation 10:''
 
   
 
=== Secondary Structure ===
 
=== Secondary Structure ===

Revision as of 15:52, 11 August 2011

Introduction

Many mutations in the human genome are suspected to have an impact on protein function. Thus, the prediction of the effects of these mutations on the function - especially for disease causing mutation - is a very important task. In this TASK, we will apply different sequence based methods to predict mutation effects on the protein's function and then try to discriminate neutral from non-neutral mutations.
We randomly picked 10 missense mutations from dbSNP and HGMD. At this point, we act like we did not know which of these mutations is causing the disease and which is not. After having applied the methods and interpreted the results, we are going to lift the curtain and check if our guesses were correct. The mutations, we picked are summarized in the table below:

Nr. mutation position
1 Asp-Asn 29
2 Pro - Ala 136
3 Gln-His 153
4 Trp-Cys 193
5 Thr-Met 274
6 Phe -Val 356
7 Thr-Ile 409
8 Asn-Ser 440
9 Cys-Gly 489
10 Arg-His 496

Substitution Matrices

A first very rough guess on the effect of mutation can be made by looking at the standard substitution matrices, like the BLOSUM and PAM matrices. Low scores in these matrices indicate, that mutations of two amino acids are rarely observed and thus the amino acids should have very different physico-chemical properities. Consequently substitution with low scores might affect structure and/or the function of the protein.
Substitutions with a high score are observed very frequently. Thus the properties of the amino acids are similar and thus the substiotion is not very likely to affect the protein's structure or function.
When doing this analysis, we have to keep in mind, that this is a very inaccurate method to "predict" the impact of a certain mutation, as these matrices are calculated with a lot of proteins, which evens out effects specific to our protein, protein familiy respectively. But it can give a first gues, if the mutations is likely to occur in general or not.
We extracted the scores for our mutations from BLOSUM62, PAM1 and PAM100 and summarized these in the following table. Additionaly, we extracted the lowest score possible for any substitution of the amino acid of interest.


Nr. Substitution BLOSUM62 PAM1 PAM250
1 Asp(D) -> Asn(N) 1 (worst: -4) 36 (worst: 0) 7 (worst: 0)
2 Pro(P) -> Ala(A) -1 (worst: -4) 22 (worst: 0) 11 (worst: 0)
3 Gln(Q) -> His(H) 0 (worst: -3) 20 (worst: 0) 7 (worst: 0)
4 Trp(W) -> Cys(C) -2 (worst: -4) 0 (worst: 0) 1 (worst: 1)
5 Thr((T) -> Met(M) -1 (worst: -3) 2 (worst: 0) 1 (worst: 0)
6 Phe(F) -> Val(V) -1 (worst: -4) 1 (worst: 0) 10 (worst: 1)
7 Thr(T) -> Ile(I) -2 (worst: -3) 7 (worst: 0) 4 (worst: 0)
8 Asn(N) -> Ser(S) 1 (worst: -4) 34 (worst: 0) 8 (worst: 0)
9 Cys(C) -> Gly(G) -3 (worst: -4) 1 (worst: 0) 4 (worst: 0)
10 Arg(R) -> His(H) 0 (worst: -3) 8 (worst: 0) 5 (worst: 1)

Secondary Structure

Sec Struct Mutations ARSA.png

As one can see in the picture above, none of the mutations is in the middle of a secondary structure element. Only the mutations 1,2,4 and 5 are close to or - depending on the prediction method - at the border of secondary structure elements.

Prediction of effect

SNAP

SNAP uses a neural-network approach to predict effects of single amino acid substitutions on protein function. It uses in silico derived protein information - like secondary structure, conservation, solvent accessibility, etc. - for the prediction. <ref> SNAP: predict effect of non-synonymous polymorphisms on function. Yana Bromberg and Burkhard Rost Nucleic Acids Research, 2007, Vol. 35, No. 11 3823-3835 </ref>
We ran snap using the following command:


snapfun -i ARSA.fasta -m mutants.txt -o snap.out

output:


nsSNP	Prediction	Reliability Index	Expected Accuracy
-----	------------	-------------------	-------------------
D29N	Non-neutral		7			96%
Q153H	 Neutral 		0			53%
T274M	Non-neutral		6			93%
T409I	Non-neutral		1			63%
C489G	Non-neutral		5			87%
W193C	Non-neutral		3			78%
F356V	 Neutral 		1			60%
N440S	Non-neutral		2			70%
R496H	 Neutral 		1			60%
P136A	Non-neutral		4			82%

SNAP predicts three of our proteins to be neutral, the other non-neutral. In order to analyze all possible combinations of amino acid substitutions from the above mutated positions, we used the Generate Mutants tool on http://rostlab.org/services/snap/submit to create all possible exchanges from the following pattern: referenceAminoAcidPosition* . Then we again executed snap:


snapfun -i ARSA.fasta -m all_mutants.txt -o snap_all.out

Next, we wrote a perl script to parse and summarize the SNAP output in the following table, which shows which amino acid substitutions are Non-neutral or Neutral. We consider a residue as important if 66-100 % of all possible substitutions are Non-Neutral, as probably important if 33-66 % of possible substitutions are Non-Neutral and as not important, if 0-33 % of all possible substitutions are Non-Neutral.

ref\mutation important A R N D C Q E G H I L K M F P S T W Y V
D29 yes Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral
Q153 yes Non-neutral Non-neutral Neutral Non-neutral Non-neutral Non-neutral Non-neutral Neutral Non-neutral Non-neutral Non-neutral Neutral Non-neutral Neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral
T274 yes Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral
T409 yes Neutral Non-neutral Neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral
C489 yes Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral
W193 yes Non-neutral Non-neutral Neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral
F356 probably Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Neutral Non-neutral Non-neutral Neutral Neutral Neutral Non-neutral Neutral Non-neutral Non-neutral Non-neutral Non-neutral Neutral Neutral
N440 yes Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral
R496 yes Non-neutral Non-neutral Non-neutral Non-neutral Neutral Non-neutral Non-neutral Neutral Non-neutral Non-neutral Neutral Non-neutral Neutral Non-neutral Non-neutral Non-neutral Non-neutral Neutral Non-neutral
P136 yes Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral Non-neutral

SIFT

SIFT predicts the effect of amino acid substitutions by building a multiple alignment and then calculating the probability of each possible substitution. The score in the SIFT-output is the probability of the substitution. SIFT predicts a substitution as damaging if this probability is <= 0.05 and as tolerated if the probability is > 0.05. The median conservation in the output measures the diversity of the sequences used in the multiple alignment. It should be between 2.75 and 3.25. Higher values indicate that the sequences were too closely related. <ref>http://sift.jcvi.org/www/SIFT_help.html</ref> We used SIFT with the UniProt-TrEMBL 2009 Database and uploaded a file containing our chosen mutations:

D29N
P136A
Q153H
W193C
T274M
F356V
T409I
N440S
C489G
R496H

As median conservation we used the standard parameter 3.00 and we excluded all sequences with a sequence identity higher than 90%.

Mutation NR Substitution predicted score median conservation comment
1 D29N AFFECT PROTEIN FUNCTION 0.00 3.04
2 P136A AFFECT PROTEIN FUNCTION 0.00 3.07
3 Q153H TOLERATED 0.29 3.04
4 W193C AFFECT PROTEIN FUNCTION 0.04 3.04
5 T274M AFFECT PROTEIN FUNCTION 0.00 3.04
6 F356V TOLERATED 0.81 3.04
7 T409I AFFECT PROTEIN FUNCTION 0.02 3.48 low confidence
8 N440S TOLERATED 0.07 3.08
9 C489G AFFECT PROTEIN FUNCTION 0.00 3.56 low confidence
10 R496H TOLERATED 0.28 3.56

PolyPhen

PolyPhen predicts wether a mutation is damaging or not by using a Naïve-Bayes-approach. The score is the posterior probability that the mutation is damaging.<ref>http://genetics.bwh.harvard.edu/pph2/dokuwiki/overview</ref> We used PolyPhen with standard parameters. The results are shown below.

Mutation NR Substitution HumDiv HumVar Link (expires in September)
predicted score predicted score
1 D29N probably damaging 1.000 probably damaging 0.999 http://genetics.bwh.harvard.edu/ggi/pph2/6b8e887bab2c4971aff12f9579630878eaaed666/479962.html
2 P136A probably damaging 1.000 probably damging 0.999 http://genetics.bwh.harvard.edu/ggi/pph2/6b8e887bab2c4971aff12f9579630878eaaed666/479963.html
3 Q153H possibly damaging 0.945 possibly damaging 0.520 http://genetics.bwh.harvard.edu/ggi/pph2/6b8e887bab2c4971aff12f9579630878eaaed666/479964.html
4 W193C probably damaging 0.977 possibly damaging 0.633 http://genetics.bwh.harvard.edu/ggi/pph2/6b8e887bab2c4971aff12f9579630878eaaed666/479965.html
5 T274M probably damaging 1.000 probably damaging 1.000 http://genetics.bwh.harvard.edu/ggi/pph2/6b8e887bab2c4971aff12f9579630878eaaed666/479966.html
6 F356V benign 0.000 benign 0.001 http://genetics.bwh.harvard.edu/ggi/pph2/6b8e887bab2c4971aff12f9579630878eaaed666/479967.html
7 T409I probably damaging 0.961 benign 0.432 http://genetics.bwh.harvard.edu/ggi/pph2/6b8e887bab2c4971aff12f9579630878eaaed666/479968.html
8 N440S possibly damaging 0.834 benign 0.255 http://genetics.bwh.harvard.edu/ggi/pph2/6b8e887bab2c4971aff12f9579630878eaaed666/479969.html
9 C489G damaging 0.999 probably damaging 0.906 http://genetics.bwh.harvard.edu/ggi/pph2/6b8e887bab2c4971aff12f9579630878eaaed666/479970.html
10 R496H benign 0.003 benign 0.000 http://genetics.bwh.harvard.edu/ggi/pph2/6b8e887bab2c4971aff12f9579630878eaaed666/479971.html

Comparison of results

To compare the results of the different prediction methods we created the table below. If a mutation was predicted to have an effect, a "X" was set, if a mutation was predicted to have no effect, a "-" was set. For PolyPhen "X" means "damaging" or "probably damaging", a "/" means "possibly damaging" and a "-" means "benign".

Mutation NR Substitution SNAP SIFT PolyPhen
HumDiv HumVar
1 D29N X X X X
2 P136A X X X X
3 Q153H - - / /
4 W193C X X X /
5 T274M X X X X
6 F356V - - - -
7 T409I X X X -
8 N440S X - / -
9 C489G X X X X
10 R496H - - - -

Multiple sequence alignments

First, we downloaded the HSSP file for ARSA to get all proteins, which are homologuous to it. Then we downloaded all mammalian protein sequences from Uniprot. This was achieved by searching for the term taxonomy:40674, which codes for all mammalian protein sequences. We saved all sequences in one multiple fasta file. Then we extracted all homologuous mammalian proteins to human ARSA by mapping the ids from the HSSP file to sequence ids in the multi fasta file. This yielded 75 homologuous mammalian sequences to human ARSA.
Next, we calculated a multiple sequence alignments of these proteins (including ARSA) with Muscle. The Jalview image of the alignment is shown below.

Multiple sequence alignments of all 75 homologuous sequences using muscle

The following table shows the conservation of the original amino acid in the reference sequence and their mutations at the respective positions.

pos conservation - reference conservation - mutant
29 0.86 0
153 0.14 0
274 0.87 0
409 0.35 0.16
489 0.80 0.05
193 0.13 0
356 0.15 0
440 0.15 0
496 0.14 0.01
136 0.93 0

PSI-BLAST

To infer the position specific sequence profile, we executed PSI-BLAST with the following command:


blastpgp -i ARSA.fasta -d /data/blast/nr/nr -e 10E-6 -j 5 -Q psiblast.mat -o psiblast_eval10E_6.it.5.new.txt

The graphic shows the relevant lines of the profile matrix regarding our mutated positions. The scores of interest - which score our mutation substitutions - are highlighted in green.


Last position-specific scoring matrix computed, weighted observed percentages rounded down, information per position, and relative weight of gapless real matches to pseudocounts
          A  R  N  D  C  Q  E  G  H  I  L  K  M  F  P  S  T  W  Y  V   A   R   N   D   C   Q   E   G   H   I   L   K   M   F   P   S   T   W   Y   V
  29 D   -5 -5 -2  8 -7 -3 -1 -4 -4 -6 -7 -4 -6 -7 -5 -3 -4 -7 -6 -6    0   0   0 100   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0  2.49 1.56
 153 Q    3  2 -1  4 -4 -1 -1 -2  0 -2 -3 -3  4 -2 -3 -1 -2 -3 -2 -2   26  10   3  23   0   3   3   3   2   2   1   1  13   2   1   3   2   0   1   2  0.53 1.48
 274 T   -3 -4 -3 -4 -2 -4 -4 -5 -5 -4 -4 -4 -3 -5 -4  1  8 -6 -5 -3    0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   7  92   0   0   0  1.94 1.62
 409 T   -1  0  0 -1 -2 -1 -1  0 -1 -1 -1  0 -1 -1  3  0  1  6  0 -1    5   5   5   4   1   3   4   8   1   3   6   5   1   2  13   6   8  11   3   4  0.26 0.95
 489 C    2 -1  1 -4  8 -4 -4 -2 -1 -1 -2 -3 -1 -4 -4  0  0  5 -1 -3   15   4   8   0  36   0   0   2   1   3   3   1   1   0   0   6   5   9   2   0  0.99 1.22
 440 N   -5 -3  6  5 -6 -2 -1 -4 -3 -6 -6 -3 -6 -6  2 -2 -3 -6 -6 -5    0   1  46  36   0   1   2   0   0   0   0   1   0   0  10   1   1   0   0   0  1.48 1.67
 356 F   -3 -1 -5 -5 -3  0 -1 -6  1  3  0 -1  0  2 -6 -3 -2 -3  5  3    1   4   0   0   1   5   4   0   3  18   8   5   2   8   0   1   2   0  20  20  0.59 1.62
 193 W   -2  4  2  3 -5  0  0 -2  0 -3 -4  1 -3 -1 -2 -1 -2  1  1 -3    3  25  11  16   0   4   5   3   2   2   1   7   0   2   2   4   2   2   5   2  0.46 1.45
 136 P   -3 -5 -5 -5 -6 -4 -4 -5 -5 -6 -6 -4 -6 -7  9 -4 -4 -7 -6 -5    1   0   0   0   0   0   0   0   0   0   0   0   0   0  98   0   0   0   0   0  3.03 1.61
 496 R   -3  1  0 -3 -4  1  1 -1  1 -3  1  1 -2  2  4  0 -3 -1 -1 -3    1   7   4   1   0   5  10   4   3   1  16   9   0   9  20   8   1   1   1   1  0.34 0.96


Summary and Discussion

The mutations are listed below, together with a pymol mutagenesis image and a description of the properties of the mutations. We also included short summary tables of the methods we applied and added a short discussion/interpretation of the results. For a detailed descitption of the summary tables, please read the individual sections.

Nr. mutation position reference mutation both
1 Asp-Asn 29
29 arsa asp.png
29 arsa asn.png
29 arsa both.png
Description of Asp-Asn
Aspartic acid (Asp)
Asparagine (Asn)
BLOSUM62 PAM1 PAM250 PSI-BLAST SNAP Polyphen (HumDiv) Polyphen (HumVar) SIFT Residue Importance Conservation in MSA Disrupting SS
1 (worst: -4) 36 (worst: 0) 7 (worst: 0) -5 X X X X important 0.86 yes (at the border)

Aspartic acid is an acidic amino acid while Asparagine is a hydrophilic amino acid. So the mutation changes the behaviour towards water as well as the pH. The lysosomal enzyme exhibits a very low pH value, thus acidic amino acids are preferred in this environment. Consequently the effect could be deleterious. This hypothesis is supported by all predictions and also the substitution matrices show rather low values. The mutations is located at the border of a beta sheet, which is also an indicator for a possible deleterious effect. Also the conservtion of the amino acid is very high in the MSA of related sequences, which indicates, that the residue is quite important. Furthermore it is classified as important residue by our analysis of all possible mutants, i.e. most of the substitutions lead to a deleterious effect. This effect is not introduced by a structural change of the aminpo acid itself - structures are very similar (see abbove) - but through the drastic change of the amino acid property. Regarding to our analysis we classify this mutation as deleterious.
This is supported by the Uniprot annotation, which associates it to infantile-onset Metachromatic leukodystrophy. It causes a severe reduction of enzyme activity.

2 Pro - Ala 136
136 arsa PRO.png
136 arsa ALA.png
136 arsa both.png
Description of Pro-Ala
Proline (Pro)
Alanine (Ala)
BLOSUM62 PAM1 PAM250 PSI-BLAST SNAP Polyphen (HumDiv) Polyphen (HumVar) SIFT Residue Importance Conservation in MSA Disrupting SS
-1 (worst: -4) 22 (worst: 0) 11 (worst: 0) -3 X X X X important 0.93 yes (at the border)

Proline and Alanine are both hydrophobic amino acids. In contrast to mutation 1, the behaviour towards water does not change. As Proline is a cyclic amino acid, it can "break" alpha-helices and is structural very important. It is even located at the border of an alpha-helix. Thus, the change to the smallest amino acid Alanine could introduced a big structural change, despite the similarity, regariding to their chemical properties.
For this mutation, all predictions yield damaging effects and the substitution matrices indicate, that a substitution from Pro to Ala is very unlikely. Again the conservtion of the amino acid is very high in the MSA of related sequences, which indicates, that the residue is quite important.
Furthermore it is classified as important residue by our analysis of all possible mutants, i.e. most of the substitutions lead to a deleterious effect.
Regarding to HGMD, this mutation leads to the outbreak of the disease.

3 Gln-His 153
153 arsa GLN.png
153 arsa HIS.png
153 arsa both.png
Description of Gln-His
Glutamine (Gln)
Histidine (His)
BLOSUM62 PAM1 PAM250 PSI-BLAST SNAP Polyphen (HumDiv) Polyphen (HumVar) SIFT Residue Importance Conservation in MSA Disrupting SS
0 (worst: -3) 20 (worst: 0) 7 (worst: 0) 0 - / / - important 0.14 no

Glutamine is a hydrophilic amino acid while Histidine is a basic amino acid. So the behaviour towards water changes as well as the charge of the amino acid. Also Gln and His are very different in structure, so His needs much more space than Gln, which should have a big influence on the structure of ARSA (see above pymol images).
In this case the mutations is not located within a secondary structure element and it is also not conserved in the MSA. Further on, the values in PAM and the PSSM are quite high. The value in the BLSOUM62 matrix however is low. These factors indicate, that the mutation should not have a severe effect.
The predictions made by SNAP, SIFT and Polyphen are not consistent. Whereas SIFT and SNAP predict a neutral effect, Polyphen predicts a benign effect. Regarding to the above results, we tend to classify this mutation as neutral.
This is however not the case. HGMD states, that the mutation is associated to Metachromatic Leukodystrophy.

4 Trp-Cys 193
193 arsa TRP.png
193 arsa CYS.png
193 arsa both.png
Description of Trp-Cys
Tryptophan (Trp)
Cysteine (Cys)
BLOSUM62 PAM1 PAM250 PSI-BLAST SNAP Polyphen (HumDiv) Polyphen (HumVar) SIFT Residue Importance Conservation in MSA Disrupting SS
-2 (worst: -4) 0 (worst: 0) 1 (worst: 1) -5 X X / X important 0.13 no

Tryptophan is a hydrophobic, aromatic amino acid while Cysteine is a hydrophilic amino acid. So the behaviour towards water changes dramatically. Also, Trp is the largest amino acid while Cys is a rather small amino acid. So the space needed for the amino acid changes also. This should have a huge influence on the structure of ARSA.
Again the residue is not conserved across the homologs to ARSA and it is not located within a secondary structure element. This could indicate a neutral substitution. However, all substitution matrices yield very low values for the given substitution and the predictions of SNAP, SIFT and Polyphen suggest a damaging effect. Regarding these results we would assign this mutation a deleterious effect.
However, HGMD does not contain this mutation and dbSNP does not assign a deleterious effect. The mutation is a single nucleotide polymorphism (SNP), which - by defintion - occurs in a certain part of the population. As Metachromatic leukodystrophy is not very widespread this mutation should be a non-damaging natural variant.

5 Thr-Met 274
274 arsa THR.png
274 arsa MET.png
274 arsa both.png
Description of Thr-Met
Threonine (Thr)
Methionine (Met)
BLOSUM62 PAM1 PAM250 PSI-BLAST SNAP Polyphen (HumDiv) Polyphen (HumVar) SIFT Residue Importance Conservation in MSA Disrupting SS
-1 (worst: -3) 2 (worst: 0) 1 (worst: 0) -3 X X X X important 0.87 yes (at the border)

Threonine is a hydrophilic amino acid while Methionine is a hydrophobic amino acid. So the behaviour towards water changes. Also, Methionine has a very long sidechain while Threonine does not. So the structure of ARSA should be altered by this mutation.
Besides these properties, the mutation is located within a secondary structure element, the residue (Thr) is highly conserved across homologs and all prediction tools predict a deleterious effect on the enzyme's function. Further on, the values in the substitution matrices are very low, indicating a deleterious effect. Reagrding to this, the mutation should have a severe effect on the structure and the function.
HGMD assigns a deleterious effect to the mutation.

6 Phe -Val 356
356 arsa PHE.png
356 arsa VAL.png
356 arsa both.png
Description of Phe-Val
Phenylalanine (Phe)
Valine (Val)
BLOSUM62 PAM1 PAM250 PSI-BLAST SNAP Polyphen (HumDiv) Polyphen (HumVar) SIFT Residue Importance Conservation in MSA Disrupting SS
-1 (worst: -4) 1 (worst: 0) 10 (worst: 1) 3 - - - - probably important 0.15 no

Phenylalanine and Valine are both hydrophobic amino acids. So the only impact on structure could come frome the structural differences between Phe and Val. Phe has a aromatic ring and due to that needs more space than Val. While looking at the substitution-matrices, one can notice that the scores are not great but also not really bad. The prediction methods all agree, that this mutation should have no harmful effect and due to the fact that the conservation in the MSA is very low and the mutation is not disrupting a secondary structure element, we believe that this mutation should be neutral. dbSNP classifies this mutation as SNP, so it should not be harmful.

7 Thr-Ile 409
409 arsa THR.png
409 arsa ILE.png
409 arsa both.png
Description of Thr-Ile
Threonine (Thr)
Isoleucine (Ile)
BLOSUM62 PAM1 PAM250 PSI-BLAST SNAP Polyphen (HumDiv) Polyphen (HumVar) SIFT Residue Importance Conservation in MSA Disrupting SS
-2 (worst: -3) 7 (worst: 0) 4 (worst: 0) -1 X X - X important 0.35 no

Threonine is a hydrophilic amino acid while Isoleucine is a hydrophobic amino acid. So the behaviour towards water changes. All prediction methods except the HumVar-Mode of PolyPhen assign a functional change to this mutation. The conservation in the MSA is relatively high but the mutation does not disrupt a secondary structure element and the scores in the substitution matrices are not that bad. The mutation is known to cause Metachromatic Leukodystrophy.

8 Asn-Ser 440
440 arsa ASN.png
440 arsa SER.png
440 arsa both.png
Description of Asn-Ser
Asparagine (Asn)
Serine (Ser)
BLOSUM62 PAM1 PAM250 PSI-BLAST SNAP Polyphen (HumDiv) Polyphen (HumVar) SIFT Residue Importance Conservation in MSA Disrupting SS
1 (worst: -4) 34 (worst: 0) 8 (worst: 0) -2 X / - - important 0.15 no

Asparagine and Serine are both hydrophilic amino acids. Also they are almost of the same size. So the mutation should not have a very dramatic effect. The scores in the substitution matrices for this mutation are very high, the conservation in the MSA is very low and the mutation is not disrupting a secondary structure elemtent but nevertheless the prediction methods do not agree on the effect of the mutation. DbSNP classifies this mutation as SNP, so it should not be harmful.

9 Cys-Gly 489
489 arsa CYS.png
489 arsa GLY.png
489 arsa both.png
Description of Cys-Gly
Cystein (Cys)
Glycine (Gly)
BLOSUM62 PAM1 PAM250 PSI-BLAST SNAP Polyphen (HumDiv) Polyphen (HumVar) SIFT Residue Importance Conservation in MSA Disrupting SS
-3 (worst: -4) 1 (worst: 0) 4 (worst: 0) -2 X X X X important 0.80 no

Cystein and Glycine are both hydrophilic amino acids. One difference is the size: Gly is the smallest of the amino acids while Cys is a little bigger. But more important Cystein contains sulfur which is important for building sulfur bridges. So function should be changed by this mutation. The conservation of Cystein is very high in the MSA and the scores in the substitution matrices are very low. Also, all 4 methods agree that this mutation changes the function of the Arylsulfatase A. This mutation causes Metachromatic leukodystrophy.

10 Arg-His 496
496 arsa ARG.png
496 arsa HIS.png
496 arsa both.png
Description of Arg-His
Arginine (Arg)
Histidine (His)
BLOSUM62 PAM1 PAM250 PSI-BLAST SNAP Polyphen SIFT (HumDiv) Polyphen (HumVar) Residue Importance Conservation in MSA Disrupting SS
0 (worst: -3) 8 (worst: 0) 5 (worst: 1) 1 - - - - important 0.14 no

Arginine and Histidine are both basic amino acids so the only effect could come from the difference in size of the two. The conservation of Arginine in the MSA is very low and all 4 methods agree in the fact that this mutation is not disease-causing. Also the fact that the mutation does not disrupt a secondary structure element supports this idea. The mutation is classified as SNP and due to that not disease-causing.

References

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