Antigenicity analysis of Ebola
The Ebola virus is a single-stranded, negative-sense
mini-genome RNA virus. Zaire Ebola virus belong to the filoviridae family and is
responsible for the recent outbreak in West-Africa.
Infectious particle length is 970 nm for Ebola virus and has filamentous form with surface spikes of 10 nm length.
Infectious particle length is 970 nm for Ebola virus and has filamentous form with surface spikes of 10 nm length.
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| The Ebola-Viurs |
Consist of at least five (5) proteins: VP24, VP30,
VP35, VP40, GP, NP.
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| Ebola-Virus-Consist-of-at-least-05-Proteins |
The sequence of Genome of Ebolar-virus was taken from the following bio-project URL.
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| The Zaire Ebolavirus isolate
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An
epitope, also known as antigenic determinant, is the specific part of
an antigen that is recognized by the immune system, specifically by antibodies,
B cells, or T cells. Although epitopes are usually
non-self-proteins, sequences derived from the host that can be recognized (as
in the case of autoimmune diseases) are also epitopes. T cell epitopes are
presented on the surface of an antigen-presenting cell, where they are bound to
MHC molecules. T cell epitopes presented
by MHC class I molecules are typically peptides between 8 and 11 amino
acids in length.Peptides presented in conjunction with class I MHC
molecules are derived from foreign or self-protein antigens that have been
synthesized in the cytoplasm.
Algorithms used to recognize the
T cells epitopes & potential antigenic regions:
- Sette algorithm:
- Rothbard Taylor algorithm finds the recurring patterns of amino-acids in the windows of 04 amino-acids or 05 amino-acids (Charged AA, Hydrophobic AA, Hydrophobic AA, Polar or G AA0.
- Amphipathic helicas:
DNASTAR evaluated the Epitope patterns using the aforementioned algorithms
The MHC II Epitopes (Sette) method predicts peptide antigenic sites which interact with mouse MHC II haplotype proteins, this method finds more than 75% of known epitope sites for each. It can be used to design peptide epitopes when used in conjunction with the T-Cell Epitopes – AMPHI and the T-Cell Epitopes – Rothbard-Taylor methods.Algorithms such as AMPHI, which are based on the periodicity of T cell epitopes, have been reevaluated due to recent crystallographic determination of MHC structures with bound peptides.
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| DNASTAR evaluating the Epitopes from Ebola-virus GP gene |
The T-Cell Epitopes – AMPHI method predict immunodominant helper T-lymphocyte antigenic sites from primary sequence data. The underlying assumption of the AMPHI method is that T-cell antigenic sites are composed of amphipathic helices. The method is useful only for T-cell epitopes and not B-cell epitopes (the latter normally requires greater knowledge of the tertiary structure of the binding site). AMPHI describes a common structural pattern of MHC binding
motifs, since MHC binding motifs appear to exhibit the same periodicity as an
alpha helix.
The
T-Cell Epitopes – Rothbard-Taylor method locates potential
T-lymphocyte antigenic determinants which contain a common sequence motif.
Although Rothbard and Taylor (1988) found that the method predicted 80% of the
antigenic determinants for their peptide database, the presence or absence of
the motif is not sufficient to guarantee antigenicity. Furthermore, the method
is useful only for T-cell epitopes and not B-cell epitopes, which often require
greater knowledge of the tertiary structure of the binding site. For best
results, use this method in combination with the T-Cell Epitopes – AMPHI and
the MHC II Epitopes (Sette) methods.
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| T-Cell Epitpoes-AMPHI Agorithm-L-Gene-of Ebola-virus |
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| T-Cell-Epitpoes-Rothard-Taylor-Method |
The Gene VP-40 of Zaire Ebola-Virus showing the 04 residue windows.
The amino acids selected are D, L, T, S.
D= Aspartic Acid: Charged amino acid.
L= Leucine: Hydrophic and Aliphatic amino acid.
T= Tyrosine: Hydrophic and Hydroxylic amino acid.
S= Serine: Polar and Hydroxylic amino acid.
Rothbard Taylor algorithm finds the recurring patterns
of amino-acids in the windows of 04 amino-acids or 05 amino-acids (Charged AA,
Hydrophobic AA, Hydrophobic AA, Polar or G AA).
The analysis of the Ebola-Virus Genome for the T Cell Epitope Prediction Tools.
The Immune Epitope Database Analysis Resource provides
a collection of tools for the prediction and analysis of immune epitopes. It serves as a companion site to the Immune
Epitope Database (IEDB) a manually curated database of experimentally
characterized immune epitopes. T Cell Epitope Prediction Tools includes MHC class I
& II binding predictions, as well as peptide processing predictions.
The results for alleles HLA-A, HLA-B, HLA-C, HLA-E, HLA-G are shown below. By default prediction result is collapsed to show only the Percentile Rank when either IEDB recommended or Consensus method is used. The expanded table display the individual score of different methods.
The IEDB recommendation is fully expected to change as
the larger benchmarks are performed on datasets to determine the accurate assessment
of prediction quality. The large scale evaluation of the performance of the MHC
class I binding predictions have found that they in general rank as 1) ANN and
2) SMM method. For a given MHC molecule, currently IEDB uses the Consensus method consisting of Artificial
neural network (ANN), Stabilized matrix method (SMM), Combinatorial Peptide
Libraries, SMM with a Peptide: MHC Binding Energy Covariance matrix (SMMPMBEC),
and NetMHCpan.
The expected predicted performance in decreasing order of the
performance methods is: Consensus > ANN > SMM > NetMHCpan >
CombLib. Multiple allele/length pairs of peptides can be
submitted at a time for predictions. The alleles that occur in at least 1% of
the human population are a part of the frequently occurring alleles and by
default "Show only frequently occurring alleles" check-box is checked.
The result of at-least 1% of the human population for NP-Gene of Zaire Ebola-Virus.
Each row in Prediction output table corresponds to one
peptide binding prediction. The columns contain the allele the prediction was
made for, the input sequence number (#), start position and end position of the
peptide, its length, the peptide sequence, 'method used' and 'percentile rank'
for both IEDB recommended and consensus, the predicted affinity and percentile
rank for Ann/Smm and comblib_sidney2008.
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| NP-Gene of Zaire Ebola-Virus-frequently occurring alleles. |
The result of the lowest ranking 06 alleles from all
the alleles is as following.
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| The 06 alleles with their percentile rank |
Allele “HLA-A*03:01” the sequence “RLMRTNFLIK” with method “ Consensus (ann/smm)” had the lowest
percentile rank of “0.1”
Allele “HLA-A*68:01” the sequence “TVAPPAPVYR” with
method “Consensus (ann/smm)” had the second lowest percentile rank of “0.15000000000000002”.
Next I selected 05 allele HLA-A, HLA-B, HLA-C,
HLA-E, HLA-G as shown below
The predicted
output is given in units of IC50nM. Therefore a lower number indicates higher
affinity. As a rough guideline, peptides with IC50 values <50 nM are
considered high affinity, <500 nM intermediate affinity and <5000 nM low
affinity. Most known epitopes have high or intermediate affinity. Some epitopes
have low affinity, but no known T-cell epitope has an IC50 value greater than
5000.
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14 sequences showing the lowest percentile rank.
The sequence with the lowest percentile rank is HLA-C*01:03 "YAPFARLLNL" The method used by the IEDB was "netmhcpan" and the percentile rank was "0.1".
Thus I used IDEB and DNASTAR to determine the T cell anitigenicity of differnet genes of a single patient KM 233041. infected with the ebola virus. |
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