Evidence map›Paper›PMID 35962028›Full record

ArticleScientific reports2022

Prediction of B cell epitopes in proteins using a novel sequence similarity-based method.

Alvaro Ras-Carmona, Alexander A Lehmann, Paul V Lehmann, Pedro A Reche

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
3.6field-weighted citation impact, top 6% 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

22 citing papers in PubMed, 45 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Improving B-cell epitope prediction.Drug discovery today · 2025
    Review
  10. Review
  11. Review
  12. Article
  13. Article
  14. Review
  15. Review
  16. Article
  17. An immunoinformatics approach for design and validation of multi-subunit vaccine againstJournal of parasitic diseases : official organ of the Indian Society for Parasitology · 2024
    Article
  18. Article
  19. Article
  20. Recent Progress in Antibody Epitope Prediction.Antibodies (Basel, Switzerland) · 2023
    Review
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 2 institutions in 1 country.

Alvaro Ras-CarmonaLaboratory of Immunomedicine, Department of Immunology, Faculty of Medicine, University Complutense of Madrid, Pza Ramón y Cajal, s/n, 28040, Madrid, Spain.
Alexander A LehmannLaboratory of Immunomedicine, Department of Immunology, Faculty of Medicine, University Complutense of Madrid, Pza Ramón y Cajal, s/n, 28040, Madrid, Spain.
Paul V LehmannResearch and Development Department, Cellular Technology Limited (CTL), Shaker Heights, OH, 44122, USA.
Pedro A RecheLaboratory of Immunomedicine, Department of Immunology, Faculty of Medicine, University Complutense of Madrid, Pza Ramón y Cajal, s/n, 28040, Madrid, Spain. parecheg@med.ucm.es.
Instituto Cajal · ESUniversidad Complutense de Madrid · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prediction of B cell epitopes that can replace the antigen for antibody production and detection is of great interest for research and the biotech industry. Here, we developed a novel BLAST-based method to predict linear B cell epitopes. To that end, we generated a BLAST-formatted database upon a dataset of 62,730 known linear B cell epitope sequences and considered as a B cell epitope any peptide sequence producing ungapped BLAST hits to this database with identity ≥ 80% and length ≥ 8. We examined B cell epitope predictions by this method in tenfold cross-validations in which we considered various types of non-B cell epitopes, including 62,730 peptide sequences with verified negative B cell assays. As a result, we obtained values of accuracy, specificity and sensitivity of 72.54 ± 0.27%, 81.59 ± 0.37% and 63.49 ± 0.43%, respectively. In an independent dataset incorporating 503 B cell epitopes, this method reached accuracy, specificity and sensitivity of 74.85%, 99.20% and 50.50%, respectively, outperforming state-of-the-art methods to predict linear B cell epitopes. We implemented this BLAST-based approach to predict B cell epitopes at http://imath.med.ucm.es/bepiblast .

Indexed as

Epitopes, B-LymphocytePeptidesAmino Acid SequenceAntigensAntigensEpitopes, B-LymphocytePeptides

Identifiers

PMID35962028
PMCPMC9374694
OpenAlexW4290975501

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.