Rs121907979
Contents
General Information
| SNP-id | rs121907979 |
| Codon Number | 39 |
| Mutation Codon | Leu -> Arg |
| Mutation Triplet | CTT -> CGT |
Pysicochemical Properties
First of all, we explored the amino acid properties and compared them for the original and the mutated amino acid. Therefore we concluded the possible effect that the mutation could have on the protein.
| Leu | Arg | consequences |
| aliphatic, hydrophobic, neutral | positive charged, polar, hydrophilic | Leucine is smaller and without a positive charge. Therefore, Arg is too big for the position of Leu, which means that the exchange of Leu to Arg has to cause changes in the 3D structure of the protein. Furthermore, Leu is a hydrophobic amino acid, whereas Arg is hydrophilic. This is the complete contrary and therefore we suggest, that the protein will not function any longer. |
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Visualization of the Mutation
In the next step, we created the visualization of the mutation with PyMol. Therefore we created a picture of the original amino acid (Figure 1), of the new mutated amino acid (Figure 2) and finally of both together in one picture whereas the mutation is white colored (Figure 3). The following pictures display that the mutated amino acid Arginine has a longer chain than Leucine. Contrary Leucine comes to a fork at the end of its rest. This shows that the amino acids have some structural differences that are not drastic, but can be essential.
| picture original amino acid | picture mutated amino acid | combined picture |
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Substitution 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 of the amino acid substitution, the most frequent value for the substitution of the examined amino acid and the rarest substitution value.
In this case, the substitution of Leucine to Arginine has very low values that are near the values for the rarest substitution for PAM1 and PAM250. Furthermore, the value for the most frequent substitution differs also a lot from the value for this certain mutation for both PAMs. Contrary for BLOSUM62 the value for the amino acid substitution Leucine to Arginine is average. This means, the most frequent substitution value is as far away as the rarest substitution value. The difference between the two PAMs and BLOSUM62 can be ascribed to the different preparations of these two kinds of substitutions matrices. The PAM-matrices are evolutionary models, whereas BLOSUM is based on protein families. Therefore, probably this mutation is evolutionary not that unlikely whereas within this protein family it is unusual. According to PAM1 and PAM250 a mutation at this position will almost certainly cause structural changes which can affect functional changes. The value from BLOSSUM62 is not really significant and therefore we are not able to determine effects on the protein.
| PAM 1 | Pam 250 | BLOSOUM 62 | ||||||
| value amino acid | most frequent substitution | rarest substitution | value amino acid | most frequent substitution | rarest substitution | value amino acid | most frequent substitution | rarest substitution |
| 1 | 22 (Ile) | 0 (Asp, Cys) | 4 | 20 (Met) | 2 (Cys) | -2 | 0 (Phe) | -4 (Asp, Gly) |
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PSSM Analysis
Besides, we looked additional at the position specific scoring matrix (PSSM) for our 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 Leucine to Argenine at this position is very low and near the value for the rarest substitution. This means this substitution at this position is likely very uncommon which indicates that this substitution has bad effects as a consequence. Therefore, we concluded that this mutation will probably cause protein structure changes as well as functional changes.
| PSSM | ||
| value amino acid | most frequent substitution | rarest substitution |
| -4 | 3 | -6 |
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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 the conservation level at this position. The regarded mutation is presented by the second colored column in Figure 4. Here we can see, that the most other mammalians have a Leucine at the position. Only three mammalians differ and have an Isoleucine at this position, which is a very similar to Leucine. Therefore, the mutation at this position has probably a structural and functional change as a result.
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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 at which therein the mutation takes place. This can give an overview of how drastic the mutation can be. In this case both tools agree and predict the mutation at the end of a sheet. This means that there is almost certainly the end of the beta sheet. This has a result, that the mutation at this position would not destroy or split the whole beta-sheet. It will probably only change the end of the sheet, but it can also cause a change of the following secondary structure. This can also have functional changes as a consequence, but we think that this is unlikely here.
JPred: CCHHHHHHHHHHHHHCCCCCCCEEEEEEEEEECCCEEEEECCCEEEEECCCCCCC... PsiPred: CHHHHHHHHHHHHHHHCCCCCCCCCCCCEEEECCCEEEEECCCEEEEECCCCCCC...
Comparison with the real Structure:
Afterwards, we also visualized the position of the mutation (red) in the real 3D-structure of [PDB] and compared it with the predicted secondary structure. The visualization can therefore, like above the predicted secondary structure, display if the mutation is in a secondary structure element or in some other regions (Figure 5 and Figure 6).
Here in this case the mutation position agrees with the position of the predicted secondary structure and is at the end of a beta sheet. Like explained above this means a mutation will probably not destroy the whole beta sheet what could have as a result that the structural change is not that drastic.
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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 extracted the result for Arginine which is the real mutation in this case. SNAP showed as result that the exchange from Leucine to Arginine at this position is not neutral with a comparative high accuracy. This means that this certain mutation at this position cause very likely structural and functional changes of the protein.
| Substitution | Prediction | Reliability Index | Expected Accuracy |
| R | Non-neutral | 5 | 87% |
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 mutation position 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 three substitutions that are tolerated: Valine, Isoleucine and Leucine. The substitution to Arginine is not-tolerated at this position, which can be seen in Figure 8. This means that the mutation here is probably not neutral and will cause structural and functional 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.
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Polyphen2 Prediction
Finally, we also regarded the PolyPhen2 prediction for this mutation. This prediction visualizes how strongly damaging the mutation probably is. Therefore it gives the result for two possible cases: HumDiv and HumVar. HumDiv is the preferred model for evaluation rare alleles, dense mapping of regions identified by genome-wide association studies and analysis of neutral selection. In contrast, HumVar is the preferred model for diagnostic of Mendelian diseases which require distinguishing mutations with drastic effects from all remaining human variations including abundant mildly deleterious alleles. We decided to look at both possible models, which agreed in the most cases.
In this case both models predict that the mutation is probably damaging (Figure 9 and Figure 10). This means that the mutation is not neutral and will probably destroy the structure and the function of the protein.
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