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Communication Dans Un Congrès Année : 2023

Unveiling Antimicrobial Peptides in the Plant Seed Peptidome: A Protein Language Modeling Approach

Shuang Peng
  • Fonction : présentateur
Loïc Rajjou

Résumé

Antimicrobial peptides (AMPs) are described as small cationic peptides that play a pivotal role in the innate immune system of plant seeds, defending against pathogenic microorganisms during germination. The accurate prediction of potential AMPs holds significant value in agricultural and pharmaceutical research. Recent advancements in artificial intelligence (AI), including natural language processing, have revealed the prowess of language models (LM) in parsing semantic information from sequence data. In this study, we present a prediction framework leveraging a protein language model (PLM) to train a classifier capable of distinguishing between AMPs and non-AMPs. The protein language model employed in this research, Evolutionary Scale Modeling (ESM), discerns intricate patterns in amino acid sequences, enabling it to capture the phylogenetic and structural characteristics unique to AMPs. Through training on a newly curated dataset of annotated AMPs and non-AMPs, the model demonstrates the ability to generalize predictions to unseen sequences. Our model attains a high predictive accuracy, surpassing existing methods. In summary, our study introduces a pioneering approach for predicting antimicrobial peptides in seeds using protein language models. This methodology demonstrates superior predictive performance, underscoring its potential as a valuable tool in the field of plant physiology and antimicrobial peptide research, serving future prospect for the protection of plants and seeds.
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Dates et versions

hal-04527368 , version 1 (30-03-2024)

Licence

Domaine public

Identifiants

  • HAL Id : hal-04527368 , version 1

Citer

Shuang Peng, Loïc Rajjou. Unveiling Antimicrobial Peptides in the Plant Seed Peptidome: A Protein Language Modeling Approach. Colloque Graines 2023, Nov 2023, Versailles, France. ⟨hal-04527368⟩
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