Evidence map›Paper›PMID 33321075›Full record

ArticleCell systems2021

Predicted Cellular Immunity Population Coverage Gaps for SARS-CoV-2 Subunit Vaccines and Their Augmentation by Compact Peptide Sets.

Ge Liu, Brandon Carter, David K Gifford

Open access · bronzeAbstract read
In one paragraph

Article in Cell systems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
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

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 52 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Classical HLA Allele and Haplotype Frequency Estimates in US Populations.bioRxiv : the preprint server for biology · 2026
    Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Safety and immunogenicity of the COVID-19 vaccine BNT162b2 in patients undergoing chemotherapy for solid cancer.Journal of infection and chemotherapy : official journal of the Japan Society of Chemotherapy · 2022
    Article
  15. T cell responses to SARS-CoV-2 in humans and animals.Journal of microbiology (Seoul, Korea) · 2022
    Review
  16. Article
  17. Article
  18. Review
  19. Review
  20. 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

3 authors at 1 institution in 1 country.

Ge LiuMIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA; MIT Electrical Engineering and Computer Science, Cambridge, MA, USA.
Brandon CarterMIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA; MIT Electrical Engineering and Computer Science, Cambridge, MA, USA.
David K GiffordMIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA; MIT Electrical Engineering and Computer Science, Cambridge, MA, USA; MIT Biological Engineering, Cambridge, MA, USA. Electronic address: gifford@mit.edu.
IIT@MIT · US

Funding

Deep learning based antibody design using high-throughput affinity testing of synthetic sequencesR01CA218094 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GIFFORD, DAVID K · 2018 to 2024
$2.9M
NCI NIH HHS R01 CA218094
6 · The paper itself

Abstract

Subunit vaccines induce immunity to a pathogen by presenting a component of the pathogen and thus inherently limit the representation of pathogen peptides for cellular immunity-based memory. We find that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) subunit peptides may not be robustly displayed by the major histocompatibility complex (MHC) molecules in certain individuals. We introduce an augmentation strategy for subunit vaccines that adds a small number of SARS-CoV-2 peptides to a vaccine to improve the population coverage of pathogen peptide display. Our population coverage estimates integrate clinical data on peptide immunogenicity in convalescent COVID-19 patients and machine learning predictions. We evaluate the population coverage of 9 different subunits of SARS-CoV-2, including 5 functional domains and 4 full proteins, and augment each of them to fill a predicted coverage gap.

Indexed as

Machine LearningCOVID-19COVID-19 VaccinesForecastingHumansImmunity, CellularVaccines, SubunitCOVID-19 VaccinesVaccines, Subunitcombinatorial optimizationhaplotypemachine learningmajor histocompatibility complexpeptide vaccinepopulation coverageSARS-CoV-2subunitvaccine augmentationvaccine evaluation

Identifiers

PMID33321075
PMCPMC7691134
OpenAlexW3109155574

What OpenQuestion holds

Textmetadata
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.