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Record W4322504625 · doi:10.3390/biom13030446

Residues of Legume AG41 Peptide Crucial to Its Bio-Insecticidal Activity

2023· article· en· W4322504625 on OpenAlexfundno aff
Fatima Diya, Laurence Jouvensal, Isabelle Rahioui, Karine Loth, Catherine Sivignon, Lamis Karaki, Linda Kfoury, Francine Rizk, Pedro Da Silva

Bibliographic record

VenueBiomolecules · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLegume Nitrogen Fixing Symbiosis
Canadian institutionsnot available
FundersInstitut National de Recherche pour l'Agriculture, l'Alimentation et l'EnvironnementInstitut National des Sciences Appliquées de LyonUniversité LibanaiseAgence Universitaire de la FrancophonieIndian National Science Academy
KeywordsBiopesticideBiologyBiotechnologyPEST analysisIntegrated pest managementBeneficial insectsPesticideInsectRed flour beetlePest controlPeptideToxicologyBiological pest controlEcologyBotanyBiochemistry

Abstract

fetched live from OpenAlex

Currently, crop protection relies heavily on chemical treatments, which ultimately leads to environmental contamination and pest resistance. Societal and public policy considerations urge the need for new eco-friendly solutions. In this perspective, biopesticides are effective alternatives to chemical insecticides for the control of various insect pests. Legumes contain numerous insecticidal proteins aimed at protecting their high nitrogen content from animal/insect predation. Investigating one such protein family at genome scale, we discovered a unique diversity of the albumin 1 family in the (model) barrel medic genome. Only some members retained very high insecticidal activity. We uncovered that AG41 peptide from the alfalfa roots displays an outstanding insecticidal activity against several pests such as aphids and weevils. Here we report the 3D structure and activity of AG41 peptide. Significant insights into the structural/functional relationships explained AG41 high insecticidal activity. Such observations pave the way for the development of bio-insecticides, with AG41 peptide as the lead compound.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.254
Teacher spread0.226 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations4
Published2023
Admission routes1
Has abstractyes

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