Systematic Platform for Antimicrobial peptide Database with Evaluation
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The abuse of antibiotics is continuously enhancing bacterial resistance, triggering frequent microbiota imbalances and adverse reactions.
It also causes a massive waste of medical resources, as a silent crisis spreads.
Antimicrobial peptides, these natural small molecular peptides, with their unique bacteriostatic mechanisms, hardly induce drug resistance and can repair immune damage, bringing new hope to break the deadlock.
The website is also equipped with a machine learning-based regression model, which can predict antibacterial efficacy, half-life and cytotoxicity, providing strong assistance for design.
The innovative scoring mechanism quantifies the multi-dimensional characteristics of generated peptide sequences through a reinforcement learning reward function, guiding the model to explore towards high activity and low toxicity.
This not only provides a non-traditional solution to the problems of antibiotic abuse and drug resistance, but also improves the convenience of antimicrobial peptide retrieval, accelerating their research and development through big data and computational models.
