Evidence map›Paper›PMID 35893479›Full record

ArticleChembiochem : a European journal of chemical biology2022

Improved Antibody-Specific Epitope Prediction Using AlphaFold and AbAdapt.

Zichang Xu, Ana Davila, Jan Wilamowski, Shunsuke Teraguchi, Daron M Standley

Abstract read
In one paragraph

Article in Chembiochem : a European journal of chemical biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
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

19 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Improving B-cell epitope prediction.Drug discovery today · 2025
    Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. Engineering therapeutic monoclonal antibodies.The Journal of allergy and clinical immunology · 2024
    Review
  10. Article
  11. Article
  12. Review
  13. Recent Progress in Antibody Epitope Prediction.Antibodies (Basel, Switzerland) · 2023
    Review
  14. Article
  15. Review
  16. Improved Antibody-Specific Epitope Prediction Using AlphaFold and AbAdapt.Chembiochem : a European journal of chemical biology · 2022
    Article
  17. Review
  18. Review
  19. Article
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

5 authors.

Zichang XuDepartment of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, Suita, 565-0871, Japan.ORCID 0000-0003-1940-6898
Ana DavilaDepartment of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, Suita, 565-0871, Japan.
Jan WilamowskiDepartment of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, Suita, 565-0871, Japan.
Shunsuke TeraguchiDepartment of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, Suita, 565-0871, Japan.
Daron M StandleyDepartment of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, Suita, 565-0871, Japan.ORCID 0000-0003-4078-0817

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibodies recognize their cognate antigens with high affinity and specificity, but the prediction of binding sites on the antigen (epitope) corresponding to a specific antibody remains a challenging problem. To address this problem, we developed AbAdapt, a pipeline that integrates antibody and antigen structural modeling with rigid docking in order to derive antibody-antigen specific features for epitope prediction. In this study, we systematically assessed the impact of integrating the state-of-the-art protein modeling method AlphaFold with the AbAdapt pipeline. By incorporating more accurate antibody models, we observed improvement in docking, paratope prediction, and prediction of antibody-specific epitopes. We further applied AbAdapt-AF in an anti-receptor binding domain (RBD) antibody complex benchmark and found AbAdapt-AF outperformed three alternative docking methods. Also, AbAdapt-AF demonstrated higher epitope prediction accuracy than other tested epitope prediction tools in the anti-RBD antibody complex benchmark. We anticipate that AbAdapt-AF will facilitate prediction of antigen-antibody interactions in a wide range of applications.

Indexed as

AntibodiesAntigensAntibody SpecificityBinding Sites, AntibodyEpitopesAntibodiesAntigensEpitopesAlphaFoldantibody-antigen dockingantibody-specific epitope predictionreceptor binding domainSARS-CoV-2

Identifiers

PMID35893479
PMCPMC9543094

What OpenQuestion holds

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Registered trials

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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.