medigraphic.com
ISSN 1025-0298 (Electronic)
ISSN 1025-028X (Print)

2015, Number 2

<< Back

VacciMonitor 2015; 24 (2)

In silico quantitative prediction of B-cell epitope

Isea R

Language: Spanish
References: 17
Page: 93-97
PDF size: 266.40 Kb.


ABSTRACT

This paper shows a computational approach for quantitative prediction of B cell epitopes. The function was defined, which reflects the average value of B epitopes, according to eight predictors of different B epitopes, as well as structural and energetic considerations of the origin protein. The proposed methodology could be useful to develop both dengue and chikungunya vaccines.


REFERENCES

  1. Yang X, Yu X. An introduction to epitope prediction methods and software. Rev Med Virol. 2009;19(2):77-96.

  2. Isea, R. Designing a peptide-dendrimer for use as a synthetic vaccine against Plasmodium falciparum. Am J Bioinform Comput Biol. 2013;1:1-8.

  3. Isea, R. Vacunología inversa aplicada en malaria: del genoma a los antígenos. En: De la Iglesia D, Aguiló J, Freire A, López V, Pazos A, editores. Tecnologías NBIC en salud: El papel protagonista de la Nanociencia. Aplicación de especial interés al cáncer colorrectal. España: CYTED; 2012: p. 34-40.

  4. EL-Manzalawy Y, Honavar V. Recent advances in B-cell epitope prediction methods. Immunome Res. 2010;6(Suppl 2):S2. Disponible en: doi: 10.1186/1745-7580-6-S2-S2

  5. Sun P, Ju H, Liu Z, Ning Q, Zhang J, Zhao X et al. Bioinformatics Resources and Tools for Conformational B-Cell Epitope Prediction. Comput Math Methods Med. 2013; 943636. Disponible en: doi: 10.1155/2013/943636

  6. Petersen B, Petersen TN, Andersen P, Nielsen M, Lundegaard C. A generic method for assignment of reliability scores applied to solvent accessibility predictions. BMC Structural Biology 2009;9(51):1-10.

  7. Willard L, Ranjan A, Zhang H, Monzavi H, Boyko RF, Sykes BD et al. VADAR: a web server for quantitative evaluation of protein structure quality. Nucleic Acids Res. 2003;31(13):3316-9.

  8. Kwasigroch JM, Gilis D, Dehouck Y, Rooman M. PoPMuSiC, rationally designing point mutations in protein structures. Bioinformatics 2002;18(12):1701-2.

  9. Isea R. Predicción de epítopos consenso de células B lineales en Plasmodium falciparum 3D7. Vaccimonitor 2013; 22(1):43-6.

  10. Kringelum JV, Lundegaard C, Lund O, Nielsen M. Reliable B cell epitope predictions: impacts of method development and improved benchmarking. PLoSComput Biol. 2012;8(12):e1002829. Disponible en: doi: 10.1371/journal.pcbi.1002829

  11. Gilis D, Rooman M. PoPMuSiC, an algorithm for predicting protein mutant stability changes. Application to prion proteins. Protein Eng. 2000;13(12):849-56.

  12. Frappier V, Najmanovich RJ. A Coarse-Grained Elastic Network Atom Contact Model and Its Use in the Simulation of Protein Dynamics and the Prediction of the Effect of Mutations. PLoSComput Biol. 2014;10(4):e1003569. Disponible en: doi: 10.1371/journal.pcbi.1003569

  13. Jain T, Jayaram B. Anall atom energy based computational protocol for predicting binding affinities of protein-ligand complexes. FEBS Lett. 2005;579:6659-66.

  14. Suhre K, Sanejouand YH. ElNémo: a normal mode web server for protein movement analysis and the generation of templates for molecular replacement. Nucleic Acids Res. 2004;32(suppl 2) 610-4: disponible en: doi: 10.1093/nar/gkh368

  15. Hollup SM, Salensminde G, Reuter N. WEBnm@: a web application for normal mode analyses of proteins. BMC Bioinformatics 2005;6(52):1-8.

  16. Nevis A, Reyes F, Calero R, Camacho F, Acosta A. Predicción de epítopos T y B de la proteína NS4b del virus dengue tipo 3. Vaccimonitor 2013;22(3):14-21.

  17. Isea R. Mapeo computacional de epítopos de células B presentes en el virus del dengue. INHRR 2013;44(1):25-9.




2020     |     www.medigraphic.com