Immunoinformatics may lead to a reappraisal of the nature of B cell epitopes and of the feasibility of synthetic peptide vaccines

Regenmortel, M.H.V. Van

doi:10.1002/jmr.768

Cited by 102 publications

(68 citation statements)

References 51 publications

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“…It was noted that researchers classify epitopes as either continuous or discontinuous (Figure 2), but many so-called discontinuous epitopes consist of stretches of several consecutive amino acids that could, in some cases, be considered continuous epitopes in their own right (van Regenmortel, 2006). Further, the distinction between linear and conformational epitopes is problematic, since linear peptides necessarily adopt a particular three-dimensional conformation that is recognized by their cognate antibody.…”

Section: B-cell Epitope Terminologymentioning

confidence: 96%

Towards a consensus on datasets and evaluation metrics for developing B‐cell epitope prediction tools

Greenbaum¹,

Andersen²,

Blythe³

et al. 2007

J of Molecular Recognition

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224

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A B-cell epitope is the three-dimensional structure within an antigen that can be bound to the variable region of an antibody. The prediction of B-cell epitopes is highly desirable for various immunological applications, but has presented a set of unique challenges to the bioinformatics and immunology communities. Improving the accuracy of B-cell epitope prediction methods depends on a community consensus on the data and metrics utilized to develop and evaluate such tools. A workshop, sponsored by the National Institute of Allergy and Infectious Disease (NIAID), was recently held in Washington, DC to discuss the current state of the B-cell epitope prediction field. Many of the currently available tools were surveyed and a set of recommendations was devised to facilitate improvements in the currently existing tools and to expedite future tool development. An underlying theme of the recommendations put forth by the panel is increased collaboration among research groups. By developing common datasets, standardized data formats, and the means with which to consolidate information, we hope to greatly enhance the development of B-cell epitope prediction tools.

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Section: B-cell Epitope Terminologymentioning

confidence: 96%

Towards a consensus on datasets and evaluation metrics for developing B‐cell epitope prediction tools

Greenbaum¹,

Andersen²,

Blythe³

et al. 2007

J of Molecular Recognition

Self Cite

224

219

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“…Linear B cell epitopes vary greatly in length and range from 5 to 22 amino acids (38,39), with an average of 15 amino acids (40). In order to define the amino acid sequence within UL128 that constitutes the 13B5 epitope, we evaluated the binding of 13B5 to N-terminally and C-terminally truncated sequences of peptide 40 of the UL128 peptide library via an ELISA.…”

Section: Figmentioning

confidence: 99%

Identification of a Continuous Neutralizing Epitope within UL128 of Human Cytomegalovirus

Chiuppesi

Kaltcheva

Zhao

et al. 2017

J Virol

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As human cytomegalovirus (HCMV) is the most common infectious cause of fetal anomalies during pregnancy, development of a vaccine that prevents HCMV infection is considered a global health priority. Although HCMV immune correlates of protection are only poorly defined, neutralizing antibodies (NAb) targeting the envelope pentamer complex (PC) composed of the subunits gH, gL, UL128, UL130, and UL131A are thought to contribute to the prevention of HCMV infection. Here, we describe a continuous target sequence within UL128 that is recognized by a previously isolated potent PC-specific NAb termed 13B5. By using peptide-based scanning procedures, we identified a 13-amino-acid-long target sequence at the UL128 C terminus that binds the 13B5 antibody with an affinity similar to that of the purified PC. In addition, the 13B5 binding site is universally conserved in HCMV, contains a previously described UL128/gL interaction site, and interferes with the 13B5 neutralizing function, indicating that the 13B5 epitope sequence is located within the PC at a site of critical importance for HCMV neutralization. Vaccination of mice with peptides containing the 13B5 target sequence resulted in the robust stimulation of binding antibodies and, in a subset of immunized animals, in the induction of detectable NAb, supporting that the identified 13B5 target sequence constitutes a PC-specific neutralizing epitope. These findings provide evidence for the discovery of a continuous neutralizing epitope within the UL128 subunit of the PC that could be an important target of humoral immune responses that are involved in protection against congenital HCMV infection.IMPORTANCE Neutralizing antibodies (NAb) targeting the human cytomegalovirus (HCMV) envelope pentamer complex (PC) are thought to be important for preventing HCMV transmission from the mother to the fetus, thereby mitigating severe developmental disabilities in newborns. However, the epitope sequences within the PC that are recognized by these potentially protective antibody responses are only poorly defined. Here, we provide evidence for the existence of a highly conserved, continuous, PC-specific epitope sequence that appears to be located within the PC at a subunit interaction site of critical importance for HCMV neutralization. These discoveries provide insights into a continuous PC-specific neutralizing epitope, which could be an important target for a vaccine formulation to interfere with congenital HCMV infection.

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“…Therefore, we suggest that the performance in surface residue prediction might form a theoretical upper limit for the performance in B cell epitope residue prediction. As a B cell epitope is a context dependent immunological entity [38,40,41], a new paradigm for B cell epitope prediction may emerge, shifted from an "all B cell epitopes model" to a "single B cell epitope model", and from an "only antigen sequence based model" to a "multiple information based model." Besides the antigen sequence information, other information such as antigen structure [29], antibody sequence or mimotopes [42] are needed in the new generation of B cell epitope prediction methods.…”

Section: The Relationship Between Surface Residues and B Cell Epitopementioning

confidence: 99%

Predicting B Cell Epitope Residues With Network Topology Based Amino Acid Indices

Huang

Honda

Kanehisa

2007

Genome Informatics 2007

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We evaluate the performance of six amino acid indices in B cell epitope residue prediction using the classical sliding window method on five data sets. Four of the indices: i.e. relative connectivity, clustering coefficient, closeness and betweenness are newly derived from the topological parameters of residue networks. The other two are Parker's hydrophilicity and Levitt's index, known as the best indices so far for B cell epitope prediction. On four of the data sets, the performance of all the indices was comparable and poor in general. When applied to one well-annotated data set, the performances improved and the 4 network based indices showed better performance than that of Parker's hydrophilicity and Levitt's index. When using the relative connectivity index on this data set, the prediction accuracy, sensitivity and specificity reached 73.6%, 73.0% and 75.0% respectively, with an area under the curve about 0.796. Thus, we suggested that this index is a good choice for B cell epitope prediction. It also indicates that the low performance of B cell epitope prediction is not only due to the methods and amino acid indices used, but also the data set as well. Interestingly, on the well-annotated data set, the performance of B cell epitope residue prediction is very similar to that of protein surface residue prediction, especially at the 10 and 20 Å 2 cutoffs. It is suggested that the performance in surface residue prediction might form a theoretical upper limit for the performance of B cell epitope residue prediction methods.

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Immunoinformatics may lead to a reappraisal of the nature of B cell epitopes and of the feasibility of synthetic peptide vaccines

Cited by 102 publications

References 51 publications

Towards a consensus on datasets and evaluation metrics for developing B‐cell epitope prediction tools

Towards a consensus on datasets and evaluation metrics for developing B‐cell epitope prediction tools

Identification of a Continuous Neutralizing Epitope within UL128 of Human Cytomegalovirus

Predicting B Cell Epitope Residues With Network Topology Based Amino Acid Indices

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