Evidence map›Paper›PMID 42476547›Full record

ArticleBriefings in bioinformatics2026

Intelligent antigen design combined with yeast display enhances targeted immune responses.

Yun-Fei Ma, Guang-Hui Yin, Yu Pan, Ye Liu

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yun-Fei MaInstitute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 935, Jiaoling Road, Kunming, Yunnan Province 650118, China.
Guang-Hui YinInstitute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 935, Jiaoling Road, Kunming, Yunnan Province 650118, China.
Yu PanInstitute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 935, Jiaoling Road, Kunming, Yunnan Province 650118, China.
Ye LiuInstitute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 935, Jiaoling Road, Kunming, Yunnan Province 650118, China.ORCID 0000-0001-5581-9046

Funding

CAMS Innovation Fund for Medical Sciences 2024-I2M-TS-030I/2023-I2M-QJ-018National Key Research and Development Program of China 2023YFC2307704Science and Technology Plan-biological medical special project of Yunnan Province 202302AA310005Yunnan Revitalization Talent Support Program
6 · The paper itself

Abstract

Inducing strong and targeted humoral immune responses, a central goal of next-generation vaccine development, involves a complex series of interconnected steps. However, a comprehensive study that addresses and integrates all steps is still missing. Here, we present a study that addresses these steps to elicit precise neutralizing antibody (nAb) responses targeting focused epitope motifs. We present a new protein design model called EpiTopoFold for constructing a topology that precisely accommodates and stabilizes the epitope motif. After ten thousand in silico simulations, we designed a de novo antigen L9, which structurally incorporated three epitope motifs from the receptor-binding domain (RBD) of the coronavirus spike protein. To enhance antigen immunogenicity, we displayed L9 on the surface of yeast (Saccharomyces cerevisiae). In mice, the yeast-displayed L9 induced stronger and broader neutralizing responses than the alum-adjuvanted L9 or commercial RBD protein. Together, this work establishes a proof-of-concept framework that integrates intelligent antigen design with yeast surface display to enable robust and targeted nAb responses for next-generation vaccine development.

Indexed as

Saccharomyces cerevisiaeSpike Glycoprotein, CoronavirusAnimalsAntibodies, NeutralizingCell Surface Display TechniquesEpitopesMiceAntibodies, NeutralizingEpitopesSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2epitope motifintelligent antigen designtargeted immune responseyeast surface display

Identifiers

PMID42476547
PMCPMC13384637

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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.