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Revision as of 10:51, 30 June 2011 by Uskat (talk | contribs) (SCWRL Prediction)

General Information

SNP-id rs121907982
Codon 436
Mutation Codon Ile -> Val
Mutation Triplt ATA -> GTA

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Sequence-based Mutation Analysis

Pysicochemical Properities

First of all, we explored the amino acid properties and compared them for the original and the mutated amino acid. Therefore we created the possible effect that the mutation could have on the protein.

Ile Val consequences
aliphatic, hydrophobic, neutra aliphatic, hydrophobic, neutral In this case, the pysicochemical properties are equal. Furthermore, they almost agree in their size. Therefore, we suggest, that there is no big effect on the 3D structure of the protein and therefore, also no big effect on the protein function.

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Visualisation of the Mutation

In the next step, we created the visualization of the muation with PyMol. Therefore we created a picture for the original amino acid, for the new mutated amino acid and finally for both together in one picture whereas the mutation is white colored. The following pictures display the mutation from Isoleucine to Valine. Isoleucine is longer than Valine and one part spreads in the other direction than this of Valine. Valine is small and forks at its end. All in all, the differencesof both amino acids is not so drastical and therefore the protein will probably not have a strutural and functional change.

picture original aa picture mutated aa combined picture
Amino acid Isoleucine
Amino acid Valin
Picture which visualize the mutation

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Subsitution Matrices Values

Afterwards, we looked at the values of the substitution matrices PAM1, PAM250 and BLOSSUM62. Therefore we looked detailed at the three values: the value for accoding amino acid substitution, the most frequent value for the substitution of the examined amino acid and the rarest substitution.

In this case, the substitution of Isoleucine to Valine has very high values that agree with the most frequent value for all three substitution matrices. Therefore, according to all matrices a mutation at this position will probably not cause structural changes which can affect functional changes.

PAM 1 Pam 250 BLOSOUM 62
value aa most frequent substitution rarest substitution value aa most frequent substitution rarest substitution value aa most frequent substitution rarest substitution
33 33 (Val) 0 (Gly, Pro, Trp) 9 9 (Val) 1 (Trp) 3 3 (Val) -4 (Gly)

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PSSM Analysis

Besides, we looked additional at the position specific scoring matrix (PSSM) for ouer sequence. In contrast to PAM and BLOSOUM, the PSSM contains a specific substitution rate for each position in the sequence. Therefore, the PSSM is more position specific than PAM or BLOSOUM. We extracted the substitution value for the underlying mutation, the value for the most frequent substitution and the rarest substitution.

In this case the substitution rate for Asparagine to Aspartic acid at this position is in the middle between the value for the rarest substitution and the value for the most frequent substitution. Therefore, the value from PSSM is not realy significant and we are not able to determine effects on the protein.

value aa most frequent substitution rarest substitution
-4 3 -6

Conservation Analysis with Multiple Alignments

As a next step we created a multiple alignment which contains the HEXA sequence and 9 other mammalian homologous sequences from uniprot. Afterwards we looked at the position of the different mutations and looked at the conservation level on this position. The regarded mutation is presented by the second colored column. Here we can see, that almost all other mammalians have another amino acid on this position. Therefore, the mutation on this position is not highly conserved and a mutation there will cause probably no huge structural and functional changes for the protein.

Mutation in the multiple alignment

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Secondary Structure Mutation Analysis

As a next step we compared the different results of the secondary structure prediction tools JPred and PsiPred. Afterwards we can examine in which secondary structure element and where therein the mutation takes place. This can give an overview of how drastical the mutation can be. In this case both tools agree and predict at the position of the mutation a coil. This has a result, that the mutation at this position would not destroy or split a secondary structure element. It will probably only changes the coil between two secondary structure elements, but this can sometimes also cause a change of the the following secondary structure. We think that a drastical change of the protein structure and its function is unlikly because the mutation does not affect a secondary struture element. The change of the coil will probably only take places between two secondary structure elements which will probably not changes the protein.


Comparison with the real Structure:

Afterwards we also visualize the position of the muation (red) in the real 3D-structure of PDB and compare it with the predicted secondary structure. The visualisation can therefore like above the predicted secondary structure display if the mutation is in a secondary structure element or in some other regions.

Here in this case the mutationposition almost agree with the position of the predicted secondary structure and is within a coil. Like explained above this means a mutation will probably not destroy a secondary structure element which affects no drastical structural change. Otherwise it can cause a change of the position of the two nearest secondary structure element which can has a functional loose as a consequence. We think that a structural change is unlikely, because it is not within a secondary structure element and will therefore not cause extrem changes of the protein.

Mutation at position 436
Mutation at position 436 - detailed view

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SNAP Prediction

Next, we looked at the result of the SNAP prediction. For this prediction we took the amino acid of the certain position and checked every possible amino acid mutation. Afterwards we extract the result for Aspartic acid which is the real mutation in this case. SNAP has a result that the exhange from Asparagine to Aspartic acid at this position is neutral with an average accuracy of only 53%. The low accuracy is critical for this prediction, but we suppose that it is right and the mutation at this position is neutral which means it likely causes no structural and functional changes of the protein.

Substitution Prediction Reliability Index Expected Accuracy
V Neutral 0 53%

A detailed list of all possible substitutions can be found here]

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SIFT Prediction

Next, we used SIFT Prediction which displays if a mutation is neutral or not. Therefore, it first shows a row which contains a score for the particular mutationposition to a certain amino acid. The amino acid which are not tolerated at this position are colored red. Besides, it also constructs a table which lists the amino acids that are predicted as tolerated and not-tolerated.

In this case, there are only two substitutions that are not tolerated: Tryptophan and Cysteine. The substitution to Valine is tolerated at this position. This means that this mutation at this position is probably neutral and will not cause any structural and function changes of the protein.

SIFT Matrix:
Each entry contains the score at a particular position (row) for an amino acid substitution (column). Substitutions predicted to be intolerant are highlighted in red.

Sift legend.png
436 sift.png.png

SIFT Table
Threshold for intolerance is 0.05.
Amino acid color code: nonpolar, uncharged polar, basic, acidic.
Capital letters indicate amino acids appearing in the alignment, lower case letters result from prediction.

Predict Not ToleratedPositionSeq RepPredict Tolerated

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PolyPhen2 Prediction

Finally, we also regarded the PolyPhen2 prediction for this muation. This prediction visualizes have strongly demaging the mutation probably will be. Therefore it gives the result for two possible cases: HumDiv and HumVar. HumDiv is a prefered model for evaluation rare allels, dense mapping of regions identified by genome-wide assiociation studies and analysis of neutral selection. In contrast, HumVar is a prefered model for diagnostic of Mendelian diseases which require distinguishing mutations with drastic effects from all remaining human variations including abundant mildly deleterious allels. We decided to look at both possible models, which are agrees in the most cases.

In this case both models predict that the mutation is benign. This means that the mutation is neutral and will probably not damage the structure and the function of the protein.

HumDiv prediction
HumVar prediction

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Structure-based Mutation Analysis

SCWRL Prediction

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