Prediction of transmembrane alpha-helices and signal peptides A4 HUMAN

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TMHMM

We analysed this protein with TMHMM.

Figure 1: Prediction of TMHMM for the transmembrane helices of A4_HUMAN


start position end position location
1 700 outside
701 723 TM Helix
724 770 inside

TMHMM predicts one transmembrane helix at the end of the protein, which can be seen in Figure 1. As we already know is A4_HUMAN a single-spanning transmembrane protein and therefore the numbers of transmembrane helices is right predicted.

Comparison with the real structure of the protein:

Figure 2: Comparison between real occurring transmembrane helices and the TMHMM result.

The result of the TMHMM prediction is pretty well (compare Figure 2). Except of the first residues at the beginning and the exact start position of the transmembrane helix, the prediction is correct.

Back to [sequence-based prediction]

Phobius and PolyPhobius

Next we used Phobius and PolyPhobius to predict the transmembrane helices and the signal peptide of this protein.

Figure 3: Prediction of Phobius for the transmembrane helices and signal peptides of A4_HUMAN
Figure 4: Prediction of PolyPhobius for the transmembrane helices and signal peptides of A4_HUMAN
Phobius PolyPhobius
start position end position prediction start position end position prediction
Signal peptide prediction
1 1 N-Region 1 3 N-Region
2 12 H-Region 4 12 H-Region
13 17 C-Region 13 17 C-Region
Summary signal peptide
1 17 secretory signal peptide 1 17 secretory signal peptide
Transmembrane helices prediction
18 700 outside 18 700 outside
701 723 TM helix 701 723 TM helix
724 770 inside 724 770 inside

The results of both methods are quite equal, which can be seen on Figure 3 and Figure 4.

Comparison with the real structure of the protein:

Figure 5: Comparison between the prediction of Phobius and the real protein
Figure 6: Comparison between the prediction of PolyPhobius and the real protein

Both results of the prediction methods are equal (compare Figure 5 and Figure 6) and furthermore, they are equal to the real protein.

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OCTOPUS and SPOCTOPUS

We also used OCTOPUS and SPOCTOPUS to predict the transmembrane helices and the signal peptides.

Figure 7: Prediction of OCTOPUS for the transmembrane helices of A4_HUMAN
Figure 8: Prediction of SPOCTOPUS for the transmembrane helices of A4_HUMAN
OCTOPUS SPOCTOPUS
start position end position prediction start position end position prediction
1 5 outside 1 4 N-terminal of signal peptide
6 11 R 5 18 Signal peptide
12 701 outside 19 701 outside
702 722 TM helix 702 722 TM helix
723 770 inside 723 770 inside

As before by HEXA_HUMAN and RET4_HUMAN, OCTOPUS predicts a transmembrane helix (Figure 7), whereas SPOCTOPUS predicts the signal peptide (Figure 8).

Comparison with the real structure of the protein:

Figure 9: Comparison between the prediction of OCTOPUS and the real protein
Figure 10: Comparison between the prediction of SPOCTOPUS and the real protein

Both prediction results are very similar and they are also very similar to the real occurring structure (compare Figure 9 and Figure 10). Back to [sequence-based prediction]

TargetP

All of our proteins are proteins from human and archaea, so therefore we only use the non-plant option of TargetP.


Location Probability
mitochondrial targeting SP 0.035
secretory pathway SP 0.937
other 0.084

Because A4_HUMAN is a transmembrane protein, the prediction for the secretory pathway signal peptide is wrong.

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SignalP

For our analysis we used the Hidden Markov Model based and also the neuronal network based prediction.
The prediction with the Hidden Markov Model used three different scores. The S-score which is the score for the signal peptide, the C-score which is the score for the cleavage site and the Y-score which is a combination of the S-score and the C-score and is used to predict the cleavage site, because the Y-score is more precise than the C-score.

Result of the neuronal network

Signal peptide Cleavage site
start position end position start position end position prediction
1 17 17 18 signal peptide

Result of the Hidden Markov Model

prediction signal peptide probability signal anchor probability cleavage site start cleavage site end
signal peptide 1.000 0.000 17 18
Figure 11: Result of the SignalP method based on the neuronal network for A4_HUMAN
Figure 12: Result of the SignalP method based on the hidden markov model for A4_HUMAN

Both methods predict a signal peptide for A4_HUMAN, which is not correct, because A4_HUMAN is a transmembrane protein (compare Figure 11 and Figure 12).

Back to [sequence-based prediction]