Pea and lentil 7S globulin crystal structures with comparative immunoglobulin epitope mapping
Bibliographic record
Abstract
Legumes represent an affordable high protein, nutrient dense food source. However, the vast majority of legume crops contain proteins that are known allergens for susceptible individuals. These include proteins from the 7S globulin family, which comprise a vast majority of seed storage proteins. Here, the crystal structures of 7S globulins from Pisum sativum L. (pea) and Lens culinaris Medicus (lentil) are presented for the first time, including pea vicillin and convicilin, and lentil vicilin. All three structures maintain the expected 7S globulin fold, with trimeric quaternary structure and monomers comprised of β-barrel N- and C-modules. The potential impact of sequence differences on structure and packing in the different crystal space groups is noted, with potential relevance to packing upon seed deposition. Mapping on the obtained crystal structures highlights significant Ig epitope overlap between pea, lentil, peanut and soya bean and significant coverage of the entire seed storage protein, emphasizing the challenge in addressing food allergies. How recently developed biologicals might be refined to be more effective, or how these seed storage proteins might be modified in planta to be less immuno-reactive remain challenges for the future. With legumes representing an affordable, high protein, nutrient dense food source, this work will enable important research in the context of global food security and human health on an ongoing basis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".