AVP-GPT2: A Transformer-Powered Platform for De Novo Generation, Screening, and Explanation of Antiviral Peptides.

ABSTRACT: Human respiratory syncytial virus (RSV) remains a significant global health threat, particularly for vulnerable populations. Despite extensive research, effective antiviral therapies are still limited. To address this urgent need, we present AVP-GPT2, a deep-learning model that significantly outperforms its predecessor, AVP-GPT, in designing and screening antiviral peptides. Trained on a significantly expanded dataset, AVP-GPT2 employs a transformer-based architecture to generate diverse peptide sequences. A multi-modal screening approach, incorporating Star-Transformer and Vision Transformer, enables accurate prediction of antiviral activity and toxicity, leading to the identification of potent and safe candidates. SHAP analysis further enhances interpretability by explaining the underlyi

SUBMITTER: Zhao H 

PROVIDER: S-EPMC11768433 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature