Discovery of antimicrobial peptides with notable antibacterial potency by an LLM-based foundation model
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 entire process, from design to validation, concluded in 48 days. AMP-Designer excels in creating AMPs targeting specific strains despite limited data availability, with a top candidate displaying a minimum inhibitory concentration of 2.0 micrograms per milliliter against <i>Propionibacterium acnes</i>. Integrating advanced machine learning techniques, AMP-Designer demonstrates remarkable efficiency, paving the way for innovative solutions to antibiotic resistance.
Authors
- Chang‐Yu Hsieh (ORCID: https://orcid.org/0000-0002-6242-4218)
- Mingyang Wang (ORCID: https://orcid.org/0009-0001-2779-5769)
- Li‐Rong Wen (ORCID: https://orcid.org/0000-0001-7976-0878)
- Guangning Yan
- Zhihui Jiang (ORCID: https://orcid.org/0000-0002-5076-5752)
- Tingjun Hou (ORCID: https://orcid.org/0000-0001-7227-2580)
- Yafeng Deng (ORCID: https://orcid.org/0000-0003-2416-6913)
- Xingcai Zhang (ORCID: https://orcid.org/0000-0001-7114-1095)
- Peichen Pan (ORCID: https://orcid.org/0000-0003-1152-7759)
- Tianyue Wang (ORCID: https://orcid.org/0000-0002-1037-1935)
- Yan Wang (ORCID: https://orcid.org/0000-0002-1257-6635)
- Zhenhua Wu (ORCID: https://orcid.org/0000-0003-4552-883X)
- Yu Kang (ORCID: https://orcid.org/0000-0002-0999-8802)
- Jiameng Yu
- Jike Wang (ORCID: https://orcid.org/0000-0002-8118-8572)
- Huijuan Shi (ORCID: https://orcid.org/0000-0003-0324-2470)
- Xujun Zhang (ORCID: https://orcid.org/0000-0002-5633-1517)
- Jianwen Feng
- Jingxuan Ge (ORCID: https://orcid.org/0009-0006-9835-5660)
Institutions
- Guangzhou University of Chinese Medicine (CN)
- World Health Organization - Pakistan (PK)
- Harvard University (US)
- Third Affiliated Hospital of Southern Medical University (CN)
- General Hospital of Guangzhou Military Command (CN)
- Southern Command Hospital (IN)
- Nano Carbon (Poland) (PL)
- Southern Medical University (CN)
- Dali University (CN)
- Zhejiang University (CN)
- Stanford University (US)
Publication Details
- Journal
- Science Advances
- Published
- 2025-03-05
- DOI
- https://doi.org/10.1126/sciadv.ads8932
- Citations
- 61
- Primary Topic
- Antimicrobial Peptides and Activities
- Type
- article
- Field-Weighted Citation Impact
- 72.16