Quantitative Prediction of Linear B-Cell Epitopes

Raul Isea

doi:doi:10.11648/j.bsi.20170201.11

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Quantitative Prediction of Linear B-Cell Epitopes

Raul Isea

Published in Biomedical Statistics and Informatics (Volume 2, Issue 1)

Received: 7 December 2016 Accepted: 26 December 2016 Published: 21 January 2017

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Abstract

In scientific literature, there are many programs that predict linear B-cell epitopes from a protein sequence. Each program generates multiple B-cell epitopes that can be individually studied. This paper defines a function called <C > that combines results from five different prediction programs concerning the linear B-cell epitopes (ie., BebiPred, EPMLR, BCPred, ABCPred and Emini Prediction) for selecting the best B-cell epitopes. We obtained 17 potential linear B cells consensus epitopes from Glycoprotein E from serotype IV of the dengue virus for exploring new possibilities in vaccine development. The direct implication of the results obtained is to open the way to experimentally validate more epitopes to increase the efficiency of the available treatments against dengue and to explore the methodology in other diseases.

Published in	Biomedical Statistics and Informatics (Volume 2, Issue 1)
DOI	10.11648/j.bsi.20170201.11
Page(s)	1-3
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Epitope, B-Cell, Prediction, Dengue, Venezuela

References

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[2]	R. Isea, “Mapeo computacional de epítopos de células B presentes en el virus del dengue”, Rev. Inst. Nac. Hig. Vol. 44, pp. 25-28, 2013.
[3]	R. Isea, E. Montes, A. J. Rubio-Montero. J. D. Rosales, M. A. Rodríguez-Pascual, R. Mayo-García, “Characterization of antigenetic serotypes from the dengue virus in Venezuela by means of Grid Computing,” Stud. Health Technol. Inform. Vol. 159, pp. 234-238, 2010.
[4]	R. Isea, “The Present-Day Meaning of the Word Bioinformatics,” Global Journal of Advanced Research. Vol. 2, pp. 70-73, 2015.
[5]	O. Ilzins, R. Isea, J. Hoebeke, “Can Bioinformatics Be Considered as an Experimental Biological Science?,” Open Science Journal of Bioscience and Bioengineering, vol. 2, pp. 60-62, 2015.
[6]	R. Isea, J. Hoebeke, R. Mayo-García, “Designing a peptide-dendrimer for use as a synthetic vaccine against Plasmodium falciparum 3D7”, Am. J. Bioinform. Comput. Biol vol. 1, pp. 1-8, 2013.
[7]	R. Isea, J. Hoebeke, R. Mayo-García, In Handbook on Human Papillomavirus: Prevalence, Detection and Management. Edited by Harris B. Smith. NOVA Publishers, pp. 433-444, 2013.
[8]	R. Isea, “Predicción de epítopos consensos de células B lineales en Plasmodium falciparum 3D7”, VacciMonitor, vol. 22, pp. 43-46, 2013.
[9]	R. Isea, “Mapeo computacional de epítopos de células B presentes en el virus del dengue B-cell epitopes mapping of dengue virus”, VacciMonitor. Vol. 19, pp. 15-19, 2010.
[10]	S. Bhardwaj, M. Holbrook, R. E. Shope, A. D. Barrett, S. J. Watowich, “Biophysical characterization and vector-specific antagonist activity of domain III of the tick-borne flavivirus envelope protein”,. J Virol. Vol. 75, pp. 4002-4007, 2001.
[11]	I. Staropoli, M. P. Frenkiel, F. Megret, V. Deubel, “Affinity-purified dengue-2 virus envelope glycoprotein induces neutralizing antibodies and protective immunity in mice,” Vaccine, vol. 15, pp. 1946-1954, 1997.
[12]	J. E. Larsen, O. Lund, M. Nielsen, “Improved method for predicting linear B-cell epitopes,” Immunome Res. Vol. 24, pp. 2, 2006
[13]	Y. Lian, M. Ge, X. M. Pan, “EPMLR: sequence-based linear B-cell epitope prediction method using multiple linear regression”, BMC Bioinformatics. Vol. 15, pp. 414, 2014.
[14]	J. Chen, H. Liu, J. Yang, K. Chou, “Prediction of linear B-cell epitopes using amino acid pair antigenicity scale”, Amino Acids. Vol. 33, pp. 423-428, 2007.
[15]	S. Saha, G. P. S. Raghava, “BcePred: prediction of continuous B-cell epitopes in antigenic sequences using physico-chemical properties,” Proteins, vol. 65, pp. 197-204, 2004.
[16]	E. A. Emini, J. V. Hughes, D. S. Perlow, J. J. Boger, “Induction of hepatitis A virus-neutralizing antibody by a virus-specific synthetic peptide”, Virol. Vol. 55, pp. 836-839, 1985.
[17]	R. Vita, J. A. Overton, J. A. Greenbaum, J. Ponomarenko, J. D. Clark, J. R. Cantrell, D. K. Wheeler, J. L. Gabbard, D. Hix, A. Sette A, B. Peters B, “The immune epitope database (IEDB) 3.0”, Nucleic Acids Res. Vol. 43, pp. D405-D412, 2015.

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Raul Isea. (2017). Quantitative Prediction of Linear B-Cell Epitopes. Biomedical Statistics and Informatics, 2(1), 1-3. https://doi.org/10.11648/j.bsi.20170201.11

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ACS Style

Raul Isea. Quantitative Prediction of Linear B-Cell Epitopes. Biomed. Stat. Inform. 2017, 2(1), 1-3. doi: 10.11648/j.bsi.20170201.11

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AMA Style

Raul Isea. Quantitative Prediction of Linear B-Cell Epitopes. Biomed Stat Inform. 2017;2(1):1-3. doi: 10.11648/j.bsi.20170201.11

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@article{10.11648/j.bsi.20170201.11,
  author = {Raul Isea},
  title = {Quantitative Prediction of Linear B-Cell Epitopes},
  journal = {Biomedical Statistics and Informatics},
  volume = {2},
  number = {1},
  pages = {1-3},
  doi = {10.11648/j.bsi.20170201.11},
  url = {https://doi.org/10.11648/j.bsi.20170201.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.bsi.20170201.11},
  abstract = {In scientific literature, there are many programs that predict linear B-cell epitopes from a protein sequence. Each program generates multiple B-cell epitopes that can be individually studied. This paper defines a function called <C > that combines results from five different prediction programs concerning the linear B-cell epitopes (ie., BebiPred, EPMLR, BCPred, ABCPred and Emini Prediction) for selecting the best B-cell epitopes. We obtained 17 potential linear B cells consensus epitopes from Glycoprotein E from serotype IV of the dengue virus for exploring new possibilities in vaccine development. The direct implication of the results obtained is to open the way to experimentally validate more epitopes to increase the efficiency of the available treatments against dengue and to explore the methodology in other diseases.},
 year = {2017}
}

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TY  - JOUR
T1  - Quantitative Prediction of Linear B-Cell Epitopes
AU  - Raul Isea
Y1  - 2017/01/21
PY  - 2017
N1  - https://doi.org/10.11648/j.bsi.20170201.11
DO  - 10.11648/j.bsi.20170201.11
T2  - Biomedical Statistics and Informatics
JF  - Biomedical Statistics and Informatics
JO  - Biomedical Statistics and Informatics
SP  - 1
EP  - 3
PB  - Science Publishing Group
SN  - 2578-8728
UR  - https://doi.org/10.11648/j.bsi.20170201.11
AB  - In scientific literature, there are many programs that predict linear B-cell epitopes from a protein sequence. Each program generates multiple B-cell epitopes that can be individually studied. This paper defines a function called <C > that combines results from five different prediction programs concerning the linear B-cell epitopes (ie., BebiPred, EPMLR, BCPred, ABCPred and Emini Prediction) for selecting the best B-cell epitopes. We obtained 17 potential linear B cells consensus epitopes from Glycoprotein E from serotype IV of the dengue virus for exploring new possibilities in vaccine development. The direct implication of the results obtained is to open the way to experimentally validate more epitopes to increase the efficiency of the available treatments against dengue and to explore the methodology in other diseases.
VL  - 2
IS  - 1
ER  -

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Author Information

Raul Isea

Fundacion IDEA, Edif. Bolivar, Hoyo de la Puerta, Baruta, Venezuela

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APA Style

Raul Isea. (2017). Quantitative Prediction of Linear B-Cell Epitopes. Biomedical Statistics and Informatics, 2(1), 1-3. https://doi.org/10.11648/j.bsi.20170201.11

Copy | Download

ACS Style

Raul Isea. Quantitative Prediction of Linear B-Cell Epitopes. Biomed. Stat. Inform. 2017, 2(1), 1-3. doi: 10.11648/j.bsi.20170201.11

Copy | Download

AMA Style

Raul Isea. Quantitative Prediction of Linear B-Cell Epitopes. Biomed Stat Inform. 2017;2(1):1-3. doi: 10.11648/j.bsi.20170201.11

Copy | Download

@article{10.11648/j.bsi.20170201.11,
  author = {Raul Isea},
  title = {Quantitative Prediction of Linear B-Cell Epitopes},
  journal = {Biomedical Statistics and Informatics},
  volume = {2},
  number = {1},
  pages = {1-3},
  doi = {10.11648/j.bsi.20170201.11},
  url = {https://doi.org/10.11648/j.bsi.20170201.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.bsi.20170201.11},
  abstract = {In scientific literature, there are many programs that predict linear B-cell epitopes from a protein sequence. Each program generates multiple B-cell epitopes that can be individually studied. This paper defines a function called <C > that combines results from five different prediction programs concerning the linear B-cell epitopes (ie., BebiPred, EPMLR, BCPred, ABCPred and Emini Prediction) for selecting the best B-cell epitopes. We obtained 17 potential linear B cells consensus epitopes from Glycoprotein E from serotype IV of the dengue virus for exploring new possibilities in vaccine development. The direct implication of the results obtained is to open the way to experimentally validate more epitopes to increase the efficiency of the available treatments against dengue and to explore the methodology in other diseases.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Quantitative Prediction of Linear B-Cell Epitopes
AU  - Raul Isea
Y1  - 2017/01/21
PY  - 2017
N1  - https://doi.org/10.11648/j.bsi.20170201.11
DO  - 10.11648/j.bsi.20170201.11
T2  - Biomedical Statistics and Informatics
JF  - Biomedical Statistics and Informatics
JO  - Biomedical Statistics and Informatics
SP  - 1
EP  - 3
PB  - Science Publishing Group
SN  - 2578-8728
UR  - https://doi.org/10.11648/j.bsi.20170201.11
AB  - In scientific literature, there are many programs that predict linear B-cell epitopes from a protein sequence. Each program generates multiple B-cell epitopes that can be individually studied. This paper defines a function called <C > that combines results from five different prediction programs concerning the linear B-cell epitopes (ie., BebiPred, EPMLR, BCPred, ABCPred and Emini Prediction) for selecting the best B-cell epitopes. We obtained 17 potential linear B cells consensus epitopes from Glycoprotein E from serotype IV of the dengue virus for exploring new possibilities in vaccine development. The direct implication of the results obtained is to open the way to experimentally validate more epitopes to increase the efficiency of the available treatments against dengue and to explore the methodology in other diseases.
VL  - 2
IS  - 1
ER  -

Copy | Download