Discovery of antimicrobial peptides with notable antibacterial potency by an LLM-based foundation model
Nano Carbon (Poland) · Zhejiang University · +9 more institutions
Abstract
Large language models (LLMs) have shown remarkable advancements in chemistry and biomedical research, acting as versatile foundation models for various tasks. We introduce AMP-Designer, an LLM-based approach, for swiftly designing antimicrobial peptides (AMPs) with desired properties. Within 11 days, AMP-Designer achieved the de novo design of 18 AMPs with broad-spectrum activity against Gram-negative bacteria. In vitro validation revealed a 94.4% success rate, with two candidates demonstrating exceptional antibacterial efficacy, minimal hemotoxicity, stability in human plasma, and low potential to induce resistance, as evidenced by significant bacterial load reduction in murine lung infection experiments. The…
Citation impact
- FWCI
- 61.45
- Percentile
- 100%
- References
- 73
Authors
19Topics & keywords
- Antimicrobial
- Potency
- Foundation (evidence)
- Antimicrobial peptides
- Computational biology
- Microbiology
- Antibacterial peptide
- Medicine