Mature Epitope Density - A strategy for target selection based on immunoinformatics and exported prokaryotic proteins

Anderson R Santos, Vanessa Bastos Pereira, Eudes Barbosa, Jan Baumbach, Josch Pauling, Richard Röttger, Meritxell Zurita Turk, Artur Silva, Anderson Miyoshi, Vasco Azevedo

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

BACKGROUND: Current immunological bioinformatic approaches focus on the prediction of allele-specific epitopes capable of triggering immunogenic activity. The prediction of major histocompatibility complex (MHC) class I epitopes is well studied, and various software solutions exist for this purpose. However, currently available tools do not account for the concentration of epitope products in the mature protein product and its relation to the reliability of target selection.

RESULTS: We developed a computational strategy based on measuring the epitope's concentration in the mature protein, called Mature Epitope Density (MED). Our method, though simple, is capable of identifying promising vaccine targets. Our online software implementation provides a computationally light and reliable analysis of bacterial exoproteins and their potential for vaccines or diagnosis projects against pathogenic organisms. We evaluated our computational approach by using the Mycobacterium tuberculosis (Mtb) H37Rv exoproteome as a gold standard model. A literature search was carried out on 60 out of 553 Mtb's predicted exoproteins, looking for previous experimental evidence concerning their possible antigenicity. Half of the 60 proteins were classified as highest scored by the MED statistic, while the other half were classified as lowest scored. Among the lowest scored proteins, ~13% were confirmed as not related to antigenicity or not contributing to the bacterial pathogenicity, and 70% of the highest scored proteins were confirmed as related. There was no experimental evidence of antigenic or pathogenic contributions for three of the highest MED-scored Mtb proteins. Hence, these three proteins could represent novel putative vaccine and drug targets for Mtb. A web version of MED is publicly available online at http://med.mmci.uni-saarland.de/.

CONCLUSIONS: The software presented here offers a practical and accurate method to identify potential vaccine and diagnosis candidates against pathogenic bacteria by "reading" results from well-established reverse vaccinology software in a novel way, considering the epitope's concentration in the mature portion of the protein.

Original languageEnglish
Article numberS4
JournalBMC Genomics
Volume14
Issue numbersuppl. 6
Pages (from-to)1-11
Number of pages11
ISSN1471-2164
DOIs
Publication statusPublished - 2013

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Proteins
Mycobacterium tuberculosis
Computational Biology
Virulence
Reading
Alleles
Pharmaceutical Preparations

Cite this

Santos, Anderson R ; Pereira, Vanessa Bastos ; Barbosa, Eudes ; Baumbach, Jan ; Pauling, Josch ; Röttger, Richard ; Turk, Meritxell Zurita ; Silva, Artur ; Miyoshi, Anderson ; Azevedo, Vasco. / Mature Epitope Density - A strategy for target selection based on immunoinformatics and exported prokaryotic proteins. In: BMC Genomics. 2013 ; Vol. 14, No. suppl. 6. pp. 1-11.
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Santos, AR, Pereira, VB, Barbosa, E, Baumbach, J, Pauling, J, Röttger, R, Turk, MZ, Silva, A, Miyoshi, A & Azevedo, V 2013, 'Mature Epitope Density - A strategy for target selection based on immunoinformatics and exported prokaryotic proteins' BMC Genomics, vol. 14, no. suppl. 6, S4, pp. 1-11. https://doi.org/10.1186/1471-2164-14-S6-S4

Mature Epitope Density - A strategy for target selection based on immunoinformatics and exported prokaryotic proteins. / Santos, Anderson R; Pereira, Vanessa Bastos; Barbosa, Eudes; Baumbach, Jan; Pauling, Josch; Röttger, Richard; Turk, Meritxell Zurita; Silva, Artur; Miyoshi, Anderson; Azevedo, Vasco.

In: BMC Genomics, Vol. 14, No. suppl. 6, S4, 2013, p. 1-11.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Mature Epitope Density - A strategy for target selection based on immunoinformatics and exported prokaryotic proteins

AU - Santos, Anderson R

AU - Pereira, Vanessa Bastos

AU - Barbosa, Eudes

AU - Baumbach, Jan

AU - Pauling, Josch

AU - Röttger, Richard

AU - Turk, Meritxell Zurita

AU - Silva, Artur

AU - Miyoshi, Anderson

AU - Azevedo, Vasco

PY - 2013

Y1 - 2013

N2 - BACKGROUND: Current immunological bioinformatic approaches focus on the prediction of allele-specific epitopes capable of triggering immunogenic activity. The prediction of major histocompatibility complex (MHC) class I epitopes is well studied, and various software solutions exist for this purpose. However, currently available tools do not account for the concentration of epitope products in the mature protein product and its relation to the reliability of target selection.RESULTS: We developed a computational strategy based on measuring the epitope's concentration in the mature protein, called Mature Epitope Density (MED). Our method, though simple, is capable of identifying promising vaccine targets. Our online software implementation provides a computationally light and reliable analysis of bacterial exoproteins and their potential for vaccines or diagnosis projects against pathogenic organisms. We evaluated our computational approach by using the Mycobacterium tuberculosis (Mtb) H37Rv exoproteome as a gold standard model. A literature search was carried out on 60 out of 553 Mtb's predicted exoproteins, looking for previous experimental evidence concerning their possible antigenicity. Half of the 60 proteins were classified as highest scored by the MED statistic, while the other half were classified as lowest scored. Among the lowest scored proteins, ~13% were confirmed as not related to antigenicity or not contributing to the bacterial pathogenicity, and 70% of the highest scored proteins were confirmed as related. There was no experimental evidence of antigenic or pathogenic contributions for three of the highest MED-scored Mtb proteins. Hence, these three proteins could represent novel putative vaccine and drug targets for Mtb. A web version of MED is publicly available online at http://med.mmci.uni-saarland.de/.CONCLUSIONS: The software presented here offers a practical and accurate method to identify potential vaccine and diagnosis candidates against pathogenic bacteria by "reading" results from well-established reverse vaccinology software in a novel way, considering the epitope's concentration in the mature portion of the protein.

AB - BACKGROUND: Current immunological bioinformatic approaches focus on the prediction of allele-specific epitopes capable of triggering immunogenic activity. The prediction of major histocompatibility complex (MHC) class I epitopes is well studied, and various software solutions exist for this purpose. However, currently available tools do not account for the concentration of epitope products in the mature protein product and its relation to the reliability of target selection.RESULTS: We developed a computational strategy based on measuring the epitope's concentration in the mature protein, called Mature Epitope Density (MED). Our method, though simple, is capable of identifying promising vaccine targets. Our online software implementation provides a computationally light and reliable analysis of bacterial exoproteins and their potential for vaccines or diagnosis projects against pathogenic organisms. We evaluated our computational approach by using the Mycobacterium tuberculosis (Mtb) H37Rv exoproteome as a gold standard model. A literature search was carried out on 60 out of 553 Mtb's predicted exoproteins, looking for previous experimental evidence concerning their possible antigenicity. Half of the 60 proteins were classified as highest scored by the MED statistic, while the other half were classified as lowest scored. Among the lowest scored proteins, ~13% were confirmed as not related to antigenicity or not contributing to the bacterial pathogenicity, and 70% of the highest scored proteins were confirmed as related. There was no experimental evidence of antigenic or pathogenic contributions for three of the highest MED-scored Mtb proteins. Hence, these three proteins could represent novel putative vaccine and drug targets for Mtb. A web version of MED is publicly available online at http://med.mmci.uni-saarland.de/.CONCLUSIONS: The software presented here offers a practical and accurate method to identify potential vaccine and diagnosis candidates against pathogenic bacteria by "reading" results from well-established reverse vaccinology software in a novel way, considering the epitope's concentration in the mature portion of the protein.

U2 - 10.1186/1471-2164-14-S6-S4

DO - 10.1186/1471-2164-14-S6-S4

M3 - Journal article

VL - 14

SP - 1

EP - 11

JO - B M C Genomics

JF - B M C Genomics

SN - 1471-2164

IS - suppl. 6

M1 - S4

ER -