AI-Driven Antimicrobial Peptide Discovery: Mining and Generation
Helmholtz Zentrum München · Warsaw University of Technology · +16 more institutions
Abstract
The escalating threat of antimicrobial resistance (AMR) poses a significant global health crisis, potentially surpassing cancer as a leading cause of death by 2050. Traditional antibiotic discovery methods have not kept pace with the rapidly evolving resistance mechanisms of pathogens, highlighting the urgent need for novel therapeutic strategies. In this context, antimicrobial peptides (AMPs) represent a promising class of therapeutics due to their selectivity toward bacteria and slower induction of resistance compared to classical, small molecule antibiotics. However, designing effective AMPs remains challenging because of the vast combinatorial sequence space and the need to balance efficacy with low…
Citation impact
- FWCI
- 30.58
- Percentile
- 100%
- References
- 113
Authors
8- PSPaulina Szymczak
Helmholtz Zentrum München
- WZWojciech Zarzecki
Warsaw University of Technology, University of Warsaw
- JWJiejing Wang
Chinese Academy of Sciences, Jingdong (China), Czech Academy of Sciences, Institute of Microbiology
- YDYiqian Duan
Fudan University, Shanghai Institute for Science of Science, Shanghai Center for Brain Science and Brain-Inspired Technology, Institute of Science and Technology
- JWJun Wang
Chinese Academy of Sciences, Jingdong (China), Czech Academy of Sciences, Institute of Microbiology
Topics & keywords
- Antimicrobial
- Peptide
- Computational biology
- Drug discovery
- Chemistry
- Biology
- Biochemistry
- Organic chemistry
Funding
- DTDefense Threat Reduction AgencyAwards: HDTRA1-22-10031, HDTRA1-23-1-0001, HDTRA1-21-1-0014
- ARAustralian Research CouncilAward: FT230100724
- BMBeijing Municipal Natural Science FoundationAward: JQ22017
- NINational Institute of General Medical SciencesAward: R35GM138201
- HEH2020 European Research CouncilAward: GA 101125506