MétaCan
Menu
Back to cohort
Record W4409197918 · doi:10.1016/j.crfs.2025.101048

Analysis of epitopes and structural responses in egg allergen Gal d 1 using bioinformatic tools and molecular dynamics simulation

2025· article· en· W4409197918 on OpenAlexaff
Tao Wang, Lili Zhang, Vijaya Raghavan, Yan Liu, Jin Wang

Bibliographic record

VenueCurrent Research in Food Science · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTransgenic Plants and Applications
Canadian institutionsMcGill University
FundersFundamental Research Funds for the Central UniversitiesNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsAllergenEpitopeComputational biologyBiologyDynamics (music)Molecular dynamicsEvolutionary biologyChemistryImmunologyPhysicsAntigenAllergy

Abstract

fetched live from OpenAlex

Egg allergy is a growing concern worldwide. Investigating the allergenic and molecular characteristics of egg allergen Ovomucoid (Gal d 1) can enhance our understanding of egg allergies. In this study, the B-cell linear epitopes of Gal d 1 were predicted by using different bioinformatic tools, based on the primary sequence properties of Gal d 1, and obtained 10 potential B-cell linear epitopes. Meanwhile, we conducted molecular dynamics (MD) simulations to apply thermal and an oscillating electric field treatments to Gal d 1 in order to comprehend the structural alterations of Gal d 1 intuitively. The results indicated that Gal d 1 was a thermally stable protein, while the secondary structure and surface characteristics of Gal d 1 were obviously influenced by the combination of thermal stress and electric field, which finally resulted in conformational changes. This study provided a new way to understand the development of hypoallergenic egg products.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.099
GPT teacher head0.446
Teacher spread0.347 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Research in Food ScienceSame topicTransgenic Plants and ApplicationsFrench-language works237,207