Evidence map›Paper›PMID 33425259›Full record

ReviewComputational and structural biotechnology journal2021

Deimmunization of protein therapeutics - Recent advances in experimental and computational epitope prediction and deletion.

Léa V Zinsli, Noël Stierlin, Martin J Loessner, Mathias Schmelcher

Open access · goldAbstract readReview
In one paragraph

Review in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

36 citing papers in PubMed, 58 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. Activation ofACS chemical biology · 2025
    Article
  9. Article
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  12. Toll-like receptor agonists as cancer vaccine adjuvants.Human vaccines & immunotherapeutics · 2024
    Review
  13. Perspectives on Synthetic Protein Circuits in Mammalian Cells.Current opinion in biomedical engineering · 2024
    Article
  14. Review
  15. Review
  16. Review
  17. Review
  18. Reducing Immunogenicity by Design: Approaches to Minimize Immunogenicity of Monoclonal Antibodies.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2024
    Review
  19. Review
  20. Untoward immune effects of modern medication.Journal of biomedical research · 2023
    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

4 authors at 1 institution in 1 country.

Léa V ZinsliInstitute of Food, Nutrition and Health, ETH Zurich, Zurich, Switzerland.
Noël StierlinInstitute of Food, Nutrition and Health, ETH Zurich, Zurich, Switzerland.
Martin J LoessnerInstitute of Food, Nutrition and Health, ETH Zurich, Zurich, Switzerland.
Mathias SchmelcherInstitute of Food, Nutrition and Health, ETH Zurich, Zurich, Switzerland.
ETH Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biotherapeutics, and antimicrobial proteins in particular, are of increasing interest for human medicine. An important challenge in the development of such therapeutics is their potential immunogenicity, which can induce production of anti-drug-antibodies, resulting in altered pharmacokinetics, reduced efficacy, and potentially severe anaphylactic or hypersensitivity reactions. For this reason, the development and application of effective deimmunization methods for protein drugs is of utmost importance. Deimmunization may be achieved by unspecific shielding approaches, which include PEGylation, fusion to polypeptides (e.g., XTEN or PAS), reductive methylation, glycosylation, and polysialylation. Alternatively, the identification of epitopes for T cells or B cells and their subsequent deletion through site-directed mutagenesis represent promising deimmunization strategies and can be accomplished through either experimental or computational approaches. This review highlights the most recent advances and current challenges in the deimmunization of protein therapeutics, with a special focus on computational epitope prediction and deletion tools.

Indexed as

ABR, Antigen-binding regionADA, Anti-drug antibodyANN, Artificial neural networkAnti-drug-antibodyAPC, Antigen-presenting cellBab, Binding antibodyB cell epitopeBCR, B cell receptorCDR, Complementarity determining regionCRISPR, Clustered regularly interspaced short palindromic repeatsDC, Dendritic cellELP, Elastin-like polypeptideEPO, ErythropoietinER, Endoplasmatic reticulumGLK, Gelatin-like proteinHAP, Homo-amino-acid polymerHLA, Human leukocyte antigenHMM, Hidden Markov modelIg, ImmunoglobulinIL, InterleukinImmunogenicityLPS, LipopolysaccharideMHC, Major histocompatibility complexNab, Neutralizing antibodyNMR, Nuclear magnetic resonancePAMP, Pathogen-associated molecular patternPAS, Polypeptide composed of proline, alanine, and/or serinePBMC, Peripheral blood mononuclear cellPD, PharmacodynamicsPEG, Polyethylene glycolPK, PharmacokineticsProtein therapeuticPRR, Pattern recognition receptorPSA, Sialic acid polymersRNN, Recurrent artificial neural networkSVM, Support vector machineTAP, Transporter associated with antigen processingT cell epitopeTCR, T cell receptorTLR, Toll-like receptorXTEN, “Xtended” recombinant polypeptide

Identifiers

PMID33425259
PMCPMC7779837
OpenAlexW3118161098

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.