Evidence map›Paper›PMID 34685724›Full record

ArticleCells2021

BCEPS: A Web Server to Predict Linear B Cell Epitopes with Enhanced Immunogenicity and Cross-Reactivity.

Alvaro Ras-Carmona, Hector F Pelaez-Prestel, Esther M Lafuente, Pedro A Reche

Open access · goldAbstract read
In one paragraph

Article in Cells, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.4field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 34 citations in OpenAlex.

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  13. Multi-perspectives and challenges in identifying B-cell epitopes.Protein science : a publication of the Protein Society · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Alvaro Ras-CarmonaLaboratory of Immunomedicine, Department of Immunology & O2, Faculty of Medicine, University Complutense of Madrid, Ave Complutense S/N, 28040 Madrid, Spain.ORCID 0000-0003-1644-6878
Hector F Pelaez-PrestelLaboratory of Immunomedicine, Department of Immunology & O2, Faculty of Medicine, University Complutense of Madrid, Ave Complutense S/N, 28040 Madrid, Spain.ORCID 0000-0003-1378-883X
Esther M LafuenteLaboratory of Immunomedicine, Department of Immunology & O2, Faculty of Medicine, University Complutense of Madrid, Ave Complutense S/N, 28040 Madrid, Spain.ORCID 0000-0001-8466-1022
Pedro A RecheLaboratory of Immunomedicine, Department of Immunology & O2, Faculty of Medicine, University Complutense of Madrid, Ave Complutense S/N, 28040 Madrid, Spain.ORCID 0000-0003-3966-5838
Universidad Complutense de Madrid · ES

Funding

Comunidad de Madrid IND2020/BMD-17364
6 · The paper itself

Abstract

Prediction of linear B cell epitopes is of interest for the production of antigen-specific antibodies and the design of peptide-based vaccines. Here, we present BCEPS, a web server for predicting linear B cell epitopes tailored to select epitopes that are immunogenic and capable of inducing cross-reactive antibodies with native antigens. BCEPS implements various machine learning models trained on a dataset including 555 linearized conformational B cell epitopes that were mined from antibody-antigen protein structures. The best performing model, based on a support vector machine, reached an accuracy of 75.38% ± 5.02. In an independent dataset consisting of B cell epitopes retrieved from the Immune Epitope Database (IEDB), this model achieved an accuracy of 67.05%. In BCEPS, predicted epitopes can be ranked according to properties such as flexibility, accessibility and hydrophilicity, and with regard to immunogenicity, as judged by their predicted presentation by MHC II molecules. BCEPS also detects if predicted epitopes are located in ectodomains of membrane proteins and if they possess N-glycosylation sites hindering antibody recognition. Finally, we exemplified the use of BCEPS in the SARS-CoV-2 Spike protein, showing that it can identify B cell epitopes targeted by neutralizing antibodies.

Indexed as

Databases, FactualSARS-CoV-2AnimalsAntigensComputational BiologyCOVID-19Cross ReactionsEpitopes, B-LymphocyteGlycosylationHistocompatibility Antigens Class IIHumansHydrophobic and Hydrophilic InteractionsInternetMachine LearningMicePeptidesAntigensEpitopes, B-LymphocyteHistocompatibility Antigens Class IIPeptidesProteinsSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2B cellsepitopesmachine learningpredictionSARS-CoV-2

Identifiers

PMID34685724
PMCPMC8534968
OpenAlexW3207659918

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.