Evidence map›Paper›PMID 33900750›Full record

ArticleJournal of chemical information and modeling2021

MHCEpitopeEnergy, a Flexible Rosetta-Based Biotherapeutic Deimmunization Platform.

Brahm J Yachnin, Vikram Khipple Mulligan, Sagar D Khare, Chris Bailey-Kellogg

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. RankMHC: Learning to Rank Class-I Peptide-MHC Structural Models.Journal of chemical information and modeling · 2024
    Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. 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.

Brahm J YachninDepartment of Chemistry and Chemical Biology and Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854, United States.ORCID 0000-0001-6812-6329
Vikram Khipple MulliganCenter for Computational Biology, Flatiron Institute, 162 Fifth Avenue, New York, New York 10010, United States.ORCID 0000-0001-6038-8922
Sagar D KhareDepartment of Chemistry and Chemical Biology and Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854, United States.ORCID 0000-0002-2255-0543
Chris Bailey-KelloggDepartment of Computer Science, Dartmouth College, Hanover, New Hampshire 03755, United States.ORCID 0000-0003-1860-0912

Funding

Functional Deimmunization of Therapeutic ProteinsR01GM098977 · NIGMS · DARTMOUTH COLLEGE · PI BAILEY-KELLOGG, CHRIS, GRISWOLD, KARL E · 2011 to 2019
$3.4M
Principles for Designing Stimulus-Responsive EnzymesR01GM132565 · NIGMS · RUTGERS, THE STATE UNIV OF N.J. · PI KHARE, SAGAR D · 2019 to 2022
$1.8M
NIGMS NIH HHS R01 GM098977NIGMS NIH HHS R01 GM132565
6 · The paper itself

Abstract

As non-"self" macromolecules, biotherapeutics can trigger an immune response that can reduce drug efficacy, require patients to be taken off therapy, or even cause life-threatening reactions. To enable the flexible and facile design of protein biotherapeutics while reducing the prevalence of T-cell epitopes that drive immune recognition, we have integrated into the Rosetta protein design suite a new scoring term that allows design protocols to account for predicted or experimentally identified epitopes in the optimized objective function. This flexible scoring term can be used in any Rosetta design trajectory, can be targeted to specific regions of a protein, and can be readily extended to work with a variety of epitope predictors. By performing extensive design runs with varied design parameter choices for three case study proteins as well as a larger diverse benchmark, we show that the incorporation of this scoring term enables the effective exploration of an alternative, deimmunized sequence space to discover diverse proteins that are potentially highly deimmunized while retaining physical and chemical qualities similar to those yielded by equivalent nondeimmunizing sequence design protocols.

Indexed as

Computational BiologyProtein EngineeringEpitopes, T-LymphocyteHumansProteinsEpitopes, T-LymphocyteProteins

Identifiers

PMID33900750
PMCPMC8225355

What OpenQuestion holds

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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.