skip to main content
10.1145/1854776.1854889acmconferencesArticle/Chapter ViewAbstractPublication PagesbcbConference Proceedingsconference-collections
research-article

B-cell epitope prediction for peptide-based vaccine design: towards a paradigm of biological outcomes

Published: 02 August 2010 Publication History

Abstract

Two major obstacles to the development of B-cell epitope prediction for peptide-based vaccine design are (1) the prevailing binary classification paradigm, which mandates the problematic dichotomization of continuous outcome variables, and (2) failure to explicitly model biological consequences of immunization that are relevant to practical considerations of safety and efficacy. The first obstacle is eliminated by redefining the predictive task as quantitative estimation of empirically observable biological effects of antibody-antigen binding, such that prediction is benchmarked using measures of correlation between continuous rather than dichotomous variables; but this alternative approach by itself fails to address the second obstacle even if benchmark data are selected to exclusively reflect functionally relevant cross-reactivity of antipeptide antibodies with protein antigens (as evidenced by antibody-modulated protein biological activity), particularly where only antibody-antigen binding is actually predicted as a surrogate for its biological effects. To overcome the second obstacle, the prerequisite is deliberate effort to predict, a priori, biological outcomes that are of immediate practical significance from the perspective of vaccination. This demands a much broader and deeper systems view of immunobiology than has hitherto been invoked for B-cell epitope prediction. Such a view would facilitate comprehension of many crucial yet largely neglected aspects of the vaccine-design problem. Of these, immunodominance among B-cell epitopes is a central unifying theme that subsumes immune phenomena of tolerance, imprinting and refocusing; but it is meaningful for vaccine design only in the light of disease-specific pathophysiology, which for infectious processes is complicated by host-pathogen coevolution.

References

[1]
Agarwal, A. and Rao, K. V. 1997. B cell responses to a peptide epitope: iii. differential T helper cell thresholds in recruitment of B cell fine specificities. J. Immunol. 159, 1077--1085.
[2]
Alix, A. J. 1999. Predictive estimation of protein linear epitopes by using the program PEOPLE. Vaccine 18, 311--314.
[3]
Andersen, P. H., Nielsen, M., and Lund, O. 2006. Prediction of residues in discontinuous B-cell epitopes using protein 3D structures. Protein Sci. 15, 2558--2567.
[4]
Balsitis, S. J., Williams, K. L., Lachica, R., Flores, D., Kyle, J. L., Mehlhop, E., Johnson, S., Diamond, M. S., Beatty, P. R., and Harris, E. 2010. Lethal antibody enhancement of dengue disease in mice is prevented by Fc modification. PLoS Pathog. 6, e1000790.
[5]
Belpomme, D., Irigaray, P., Sasco, A. J., Newby, J. A., Howard, V., Clapp, R., and Hardell, L. 2007. The growing incidence of cancer: role of lifestyle and screening detection (review). Int. J. Oncol. 30, 1037--1049.
[6]
Blythe, M. J. and Flower, D. R. 2005. Benchmarking B cell epitope prediction: underperformance of existing methods. Protein Sci. 14, 246--248.
[7]
Brusic, V., Millot, M., Petrovsky, N., Gendel, S. M., Gigonzac, O., and Stelman, S. J. 2003. Allergen databases. Allergy 58, 1093--1100.
[8]
Bull, J. J., Meyers, L. A., and Lachmann, M. 2005. Quasispecies made simple. PLoS Comput. Biol. 1, e61.
[9]
Caoili, S. E. 2006. A structural-energetic basis for B-cell epitope prediction. Protein Pept. Lett. 13, 743--751.
[10]
Caoili, S. E. 2009. Rationalizing the selection of empirical reference data to benchmark B-cell epitope prediction for peptide-based vaccine design. Amino Acids 37, S94.
[11]
Caoili, S. E. 2010. Immunization with peptide-protein conjugates: Impact on benchmarking B-cell epitope prediction for vaccine design. Protein Pept. Lett. 17, 386--398.
[12]
Caoili, S. E. 2010. Benchmarking B-cell epitope prediction for the design of peptide-based vaccines: problems and prospects. J. Biomed. Biotechnol. 2010, 910524.
[13]
Chang, H. T., Liu, C. H., and Pai, T. W. 2008. Estimation and extraction of B-cell linear epitopes predicted by mathematical morphology approaches. J. Mol. Recognit. 21, 431--441.
[14]
Chen, J., Liu, H., Yang, J., and Chou, K. C. 2007. Prediction of linear B-cell epitopes using amino acid pair antigenicity scale. Amino Acids 33, 423--428.
[15]
Claverie, J. M. 2000. From bioinformatics to computational biology. Genome Res. 10, 1277--1279.
[16]
Davies, J. M. 1997. Molecular mimicry: can epitope mimicry induce autoimmune disease? Immunol. Cell. Biol. 75, 113--126.
[17]
De Groot, A. S. and Rappuoli, R. 2004. Genome-derived vaccines. Expert Rev. Vaccines 3, 59--76.
[18]
Deroo, S. and Muller, C. P. 2001. Antigenic and immunogenic phage displayed mimotopes as substitute antigens: applications and limitations. Comb. Chem. High Throughput Screen. 4, 75--110.
[19]
Descotes, J., Ravel, G., and Ruat, C. 2002. Vaccines: predicting the risk of allergy and autoimmunity. Toxicology 174, 45--51.
[20]
Dybwad, A., Bogen, B., Natvig, J. B., Forre, O., and Sioud, M. 1995. Peptide phage libraries can be an efficient tool for identifying antibody ligands for polyclonal antisera. Clin. Exp. Immunol. 102, 438--442.
[21]
Edgcomb, S. P. and Murphy, K. P. 2000. Structural energetics of protein folding and binding. Curr. Opin. Biotechnol. 11, 62--66.
[22]
El-Manzalawy, Y., Dobbs, D., and Honavar, V. 2008. Predicting linear B-cell epitopes using string kernels. J. Mol. Recognit. 21, 243--255.
[23]
Fauci, A. S. 2006. Emerging and re-emerging infectious diseases: influenza as a prototype of the host-pathogen balancing act. Cell 124, 665--670.
[24]
Fedorov, V., Mannino, F., and Zhang, R. 2009. Consequences of dichotomization. Pharm. Stat. 8, 50--61.
[25]
Gay, C. G., Zuerner, R., Bannantine, J. P., Lillehoj, H. S., Zhu, J. J., Green, R., and Pastoret, P. P. 2007. Genomics and vaccine development. Rev. Sci. Tech. 26, 49--67.
[26]
Gechtman, Z., Belleli, A., Lechpammer, S., and Shaltiel, S. 1997. The cluster of basic amino acids in vitronectin contributes to its binding of plasminogen activator inhibitor-1: evidence from thrombin-, elastase- and plasmin-cleaved vitronectins and anti-peptide antibodies. Biochem. J. 325, 339--349.
[27]
Graille, M., Stura, E. A., Bossus, M., Muller, B. H., Letourneur, O., Battail-Poirot, N., Sibai, G., Gauthier, M., Rolland, D., Le Du, M. H., and Ducancel, F. 2005. Crystal structure of the complex between the monomeric form of Toxoplasma gondii surface antigen 1 (SAG1) and a monoclonal antibody that mimics the human immune response. J. Mol. Biol. 354, 447--458.
[28]
Greenbaum, J. A., Andersen, P. H., Blythe, M., Bui, H. H., Cachau, R. E., Crowe, J., Davies, M., Kolaskar, A. S., Lund, O., Morrison, S., Mumey, B., Ofran, Y., Pellequer, J. L., Pinilla, C., Ponomarenko, J. V., Raghava, G. P., Van Regenmortel, M. H., Roggen, E. L., Sette, A., Schlessinger, A., Sollner, J., Zand, M., and Peters, B. 2007. Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools. J. Mol. Recognit. 20, 75--82.
[29]
Hans, D., Young, P. R., and Fairlie, D. P. 2006. Current status of short synthetic peptides as vaccines. Med. Chem. 2, 627--646.
[30]
Hileman, R. E., Silvanovich, A., Goodman, R. E., Rice, E. A., Holleschak, G., Astwood, J. D., and Hefle, S. L. 2002. Bioinformatic methods for allergenicity assessment using a comprehensive allergen database. Int. Arch. Allergy. Immunol. 128, 280--291.
[31]
Hopp, T. P. and Woods, K. R. 1981. Prediction of protein antigenic determinants from amino acid sequences. Proc. Natl. Acad. Sci. USA 78, 3824--3828.
[32]
Ivanciuc, O., Schein, C. H., and Braun, W. 2003. SDAP: database and computational tools for allergenic proteins. Nucleic Acids Res. 31, 359--362.
[33]
Kohler, H., Muller, S., and Nara, P. L. 1994. Deceptive imprinting in the immune response against HIV-1. Immunol. Today 15, 475--478.
[34]
Korber, B., LaBute, M., and Yusim, K. 2006. Immunoinformatics comes of age. PLoS Comput. Biol. 2, e71.
[35]
Kulkarni-Kale, U., Bhosle, S., and Kolaskar, A. S. 2005. CEP: a conformational epitope prediction server. Nucleic Acids Res. 33, W168--W171.
[36]
Larsen, J. E., Lund, O., and Nielsen, M. 2006. Improved method for predicting linear B-cell epitopes. Immunome Res. 2, 2.
[37]
Lin, G. and Nara, P. L. 2007. Designing immunogens to elicit broadly neutralizing antibodies to the HIV-1 envelope glycoprotein. Curr. HIV Res. 5, 514--541.
[38]
Lund, O., Nielsen, M., Lundegaard, C., Kesmir, C., and Brunak, S. 2005. Immunological Bioinformatics, 1st ed. MIT Press, Cambridge, MA.
[39]
Macklin, R. 2008. Standard of care: an evolution in ethical thinking. Lancet 372, 284--285.
[40]
Marshall, S. J. 2004. Developing countries face double burden of disease. Bull. World Health Organ. 82, 556.
[41]
Matzinger, P. 1994. Tolerance, danger, and the extended family. Annu. Rev. Immunol. 12, 991--1045.
[42]
Matzinger, P. 2002. The danger model: a renewed sense of self. Science 296, 301--305.
[43]
Muller, S. 2004. Avoiding deceptive imprinting of the immune response to HIV-1 infection in vaccine development. Int. Rev. Immunol. 23, 423--436.
[44]
Mummert, M. E. and Voss, E. W. Jr. 1996. Transition-state theory and secondary forces in antigen-antibody complexes. Biochemistry 35, 8187--8192.
[45]
Murphy, K. P. 1999. Predicting binding energetics from structure: looking beyond ΔG°. Med. Res. Rev. 19, 333--339.
[46]
Murphy, K. P. and Freire, E. 1992. Thermodynamics of structural stability and cooperative folding behavior in proteins. Adv. Protein Chem. 43, 313--361.
[47]
Nakra, P., Manivel, V., Vishwakarma, R. A., and Rao, K. V. 2000. B cell responses to a peptide epitope. x. epitope selection in a primary response is thermodynamically regulated. J. Immunol. 164, 5615--5625.
[48]
Nara, P. L. 1999. Deceptive imprinting: insights into mechanisms of immune evasion and vaccine development. Adv. Vet. Med. 41, 115--134.
[49]
Nara, P. L. and Garrity, R. 1998. Deceptive imprinting: a cosmopolitan strategy for complicating vaccination. Vaccine 16, 1780--1787.
[50]
Nayak, B. P., Tuteja, R., Manivel, V., Roy, R. P., Vishwakarma, R. A., and Rao, K. V. 1998. B cell responses to a peptide epitope. v. kinetic regulation of repertoire discrimination and antibody optimization for epitope. J. Immunol. 161, 3510--3519.
[51]
Neurath, A. R., Strick, N., and Lee, E. S. 1990. B cell epitope mapping of human immunodeficiency virus envelope glycoproteins with long (19- to 36-residue) synthetic peptides. J. Gen. Virol. 71, 85--95.
[52]
Novotny, J. and Bajorath, J. 1996. Computational biochemistry of antibodies and T-cell receptors. Adv. Protein Chem. 49, 149--260.
[53]
Novotny, L. A. and Bakaletz, L. O. 2003. The fourth surface-exposed region of the outer membrane protein P5-homologous adhesin of nontypable Haemophilus influenzae is an immunodominant but nonprotective decoying epitope. J. Immunol. 171, 1978--1983.
[54]
Odorico, M., and Pellequer, J. L. 2003. BEPITOPE: predicting the location of continuous epitopes and patterns in proteins. J. Mol. Recognit. 16, 20--22.
[55]
Partidos, C. D. 2000. Peptide mimotopes as candidate vaccines. Curr. Opin. Mol. Ther. 2, 74--79.
[56]
Partidos, C. D. and Steward, M. W. 2002. Mimotopes of viral antigens and biologically important molecules as candidate vaccines and potential immunotherapeutics. Comb. Chem. High Throughput Screen. 5, 15--27.
[57]
Pellequer, J. L., Westhof, E., and Van Regenmortel, M. H. 1991. Predicting location of continuous epitopes in proteins from their primary structures. Methods Enzymol. 203, 176--201.
[58]
Pirofski, L. A. and Casadevall, A. 2008. The damage-response framework of microbial pathogenesis and infectious diseases. Adv. Exp. Med. Biol. 635, 135--146.
[59]
Purcell, A. W., McCluskey, J., and Rossjohn, J. 2007. More than one reason to rethink the use of peptides in vaccine design. Nat. Rev. Drug Discov. 6, 404--414.
[60]
Querec, T. D., Akondy, R. S., Lee, E. K., Cao, W., Nakaya, H. I., Teuwen, D., Pirani, A., Gernert, K., Deng, J., Marzolf, B., Kennedy, K., Wu, H., Bennouna, S., Oluoch, H., Miller, J., Vencio, R. Z., Mulligan, M., Aderem, A., Ahmed, R., and Pulendran, B. 2009. Systems biology approach predicts immunogenicity of the yellow fever vaccine in humans. Nat. Immunol. 10, 116--125.
[61]
Rao, K. V. 1999. Selection in a T-dependent primary humoral response: new insights from polypeptide models. APMIS 107, 807--818.
[62]
Rubinstein, N. D., Mayrose, I., and Pupko, T. 2009. A machine-learning approach for predicting B-cell epitopes. Mol. Immunol. 46, 840--847.
[63]
Saha, S., and Raghava, G. P. 2007. Prediction methods for B-cell epitopes. Methods Mol. Biol. 409, 387--394.
[64]
Schmidt, M. A., Raupach, B., Szulczynski, M., and Marzillier, J. 1991. Identification of linear B-cell determinants of pertussis toxin associated with the receptor recognition site of the S3 subunit. Infect. Immun. 59, 1402--1408.
[65]
Simon, P. L., Kumar, V., Lillquist, J. S., Bhatnagar, P., Einstein, R., Lee, J., Porter, T., Green, D., Sathe, G., and Young, P. R. 1993. Mapping of neutralizing epitopes and the receptor binding site of human interleukin 1 beta. J. Biol. Chem. 268, 9771--9779.
[66]
Sioud, M., Forre, O., and Dybwad, A. 1996. Selection of ligands for polyclonal antibodies from random peptide libraries: potential identification of (auto)antigens that may trigger B and T cell responses in autoimmune diseases. Clin. Immunol. Immunopathol. 79, 105--114.
[67]
Sollner, J. 2006. Selection and combination of machine learning classifiers for prediction of linear B-cell epitopes on proteins. J. Mol. Recognit. 19, 209--214.
[68]
Sollner, J., Grohmann, R., Rapberger, R., Perco, P., Lukas, A., and Mayer, B. 2008. Analysis and prediction of protective continuous B-cell epitopes on pathogen proteins. Immunome Res. 4, 1.
[69]
Sollner, J., and Mayer, B. 2006. Machine learning approaches for prediction of linear B-cell epitopes on proteins. J. Mol. Recognit. 19, 200--208.
[70]
Swets, J. A. 1988. Measuring the accuracy of diagnostic systems. Science 240, 1285--1293.
[71]
Tobin, G. J., Trujillo, J. D., Bushnell, R. V., Lin, G., Chaudhuri, A. R., Long, J., Barrera, J., Pena, L., Grubman, M. J., and Nara, P. L. 2008. Deceptive imprinting and immune refocusing in vaccine design. Vaccine 26, 6189--6199.
[72]
van Oss, C. J. 1997. Kinetics and energetics of specific intermolecular interactions. J. Mol. Recognit. 10, 203--216.
[73]
Van Regenmortel, M. H. 1995. Transcending the structuralist paradigm in immunology-affinity and biological activity rather than purely structural considerations should guide the design of synthetic peptide epitopes. Biomed. Pept. Proteins Nucleic Acids 1, 109--116.
[74]
Van Regenmortel, M. H. 1996. Mapping epitope structure and activity: From one-dimensional prediction to four-dimensional description of antigenic specificity. Methods 9, 465--472.
[75]
Van Regenmortel, M. H. 2001. Pitfalls of reductionism in the design of peptide-based vaccines. Vaccine 19, 2369--2374.
[76]
Van Regenmortel, M. H. 2002. Reductionism and the search for structure-function relationships in antibody molecules. J. Mol. Recognit. 15, 240--247.
[77]
Van Regenmortel, M. H. 2004. Biological complexity emerges from the ashes of genetic reductionism. J. Mol. Recognit. 17, 145--148.
[78]
Van Regenmortel, M. H. 2006. Immunoinformatics may lead to a reappraisal of the nature of B cell epitopes and of the feasibility of synthetic peptide vaccines. J. Mol. Recognit. 19, 183--187.
[79]
Van Regenmortel, M. H. 2009. What is a B-cell epitope? Methods Mol. Biol. 524, 3--20.
[80]
Van Regenmortel, M. H. 2009. Synthetic peptide vaccines and the search for neutralization B cell epitopes. Open Vaccine J. 2, 33--44.
[81]
Van Regenmortel, M. H. and Pellequer, J. L. 1994. Predicting antigenic determinants in proteins: looking for unidimensional solutions to a three-dimensional problem? Pept. Res. 7, 224--228.
[82]
Verdier, F. 2002. Non-clinical vaccine safety assessment. Toxicology 174, 37--43.
[83]
Vita, R., Peters, B., and Sette, A. 2008. The curation guidelines of the Immune Epitope Database and Analysis Resource. Cytometry A 73, 1066--1070.
[84]
Zhang, Q., Wang, P., Kim, Y., Haste-Andersen, P., Beaver, J., Bourne, P. E., Bui, H. H., Buus, S., Frankild, S., Greenbaum, J., Lund, O., Lundegaard, C., Nielsen, M., Ponomarenko, J., Sette, A., Zhu, Z., and Peters, B. 2008. Immune Epitope Database Analysis Resource (IEDB-AR). Nucleic Acids Res. 36, W513--W518.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
BCB '10: Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology
August 2010
705 pages
ISBN:9781450304382
DOI:10.1145/1854776
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 August 2010

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. B-cell epitope prediction
  2. binary classification paradigm
  3. functionally relevant cross-reactivity
  4. host-pathogen coevolution
  5. immunodominance
  6. peptide-based vaccine design

Qualifiers

  • Research-article

Conference

BCB'10
Sponsor:

Acceptance Rates

Overall Acceptance Rate 254 of 885 submissions, 29%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 137
    Total Downloads
  • Downloads (Last 12 months)3
  • Downloads (Last 6 weeks)1
Reflects downloads up to 17 Jan 2025

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media