ArticleNature microbiology2025
A generative artificial intelligence approach for the discovery of antimicrobial peptides against multidrug-resistant bacteria.
Article in Nature microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
29 citing papers in PubMed.
- Antibiotic-Free Strategies for Managing Antimicrobial-Resistant Infections.Pharmaceutics · 2026Review
- Next-Generation Antimicrobial Peptides for Biofilm-Associated Infections: Engineering, Biomaterial Delivery and AI-Assisted Discovery.Antibiotics (Basel, Switzerland) · 2026Review
- Emerging antimicrobial peptides in gastrointestinal disorders: Dual role in immunity and therapy.World journal of gastrointestinal pharmacology and therapeutics · 2026Review
- Reframing Antimicrobial Peptides beyond Direct Antimicrobial Activity toward Host-Directed Functions and Disease-Specific Therapeutic Applications.Journal of microbiology and biotechnology · 2026Review
- Artificial Intelligence-Driven Antimicrobial Peptide Discovery: Prediction, Generation, Mining and Optimization.Probiotics and antimicrobial proteins · 2026Review
- Towards Safer Antimicrobial Peptide Therapeutics: A Predictive-Generative Framework Targeting ESKAPE Pathogens.Probiotics and antimicrobial proteins · 2026Article
- Printing to Fight Antimicrobial Resistance Through Nano/Microstructured Platforms.Chemical record (New York, N.Y.) · 2026Review
- Topical strategies for antimicrobial delivery of peptide medicines for the management of chronic wounds.Discover nano · 2026Review
- Antimicrobial peptides in anti-infective and immunomodulatory applications: Mechanisms, challenges, and emerging computational design.Zoological research · 2026Review
- Integrated Genome Mining, Bacterial Co-Culture Activation, and Peptidomic Analyses Identify Antimicrobial Peptide Candidates from South American Bacteria.Antibiotics (Basel, Switzerland) · 2026Article
- Peptides as programmable molecular scaffolds: from chemical synthesis and engineering to translational medicine.RSC chemical biology · 2026Review
- A Comprehensive Review of Antimicrobial Peptides and Smart Biomaterials in Chronic Wound Therapy: Overcoming Biofilms, Resistance, and Translational Barriers.International journal of molecular sciences · 2026Review
- PepMCP: a graph-based membrane contact probability predictor for membrane-lytic antimicrobial peptides.Bioinformatics (Oxford, England) · 2026Article
- Decoding the Gut-Fat-Heart Axis: From Molecular Communication Networks to Clinical Translation Strategies.International journal of molecular sciences · 2026Review
- Current State of the Fight Against Antimicrobial Resistance: What Are the Different Strategies for Tomorrow?Antibiotics (Basel, Switzerland) · 2026Review
- Harnessing artificial intelligence for antimicrobial discovery and optimization.Current opinion in microbiology · 2026Review
- Pharmaceutical Peptides: From Synthesis and Mechanistic Pharmacology to Future Biologic Therapeutics.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Antimicrobial peptides for bacterial infections and their biomedical applications.Discover nano · 2026Review
- Artificial Intelligence-Driven Discovery and Optimization of Antimicrobial Peptides Targeting ESKAPE Pathogens and Multidrug-Resistant Fungi.Microorganisms · 2026Review
- Artificial intelligence-driven discovery of bioactive peptides: Computational approaches and future perspectives.aBIOTECH · 2026Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
The discovery of novel antimicrobial peptides (AMPs) against clinical superbugs is urgently needed to address the ongoing antibiotic resistance crisis. AMPs are promising candidates due to their broad-spectrum activity, rapid bactericidal mechanisms and reduced likelihood of inducing resistance compared with conventional antibiotics. Here, a pre-trained protein large language model (LLM), ProteoGPT, was established and further developed into multiple specialized subLLMs to assemble a sequential pipeline. This pipeline enables rapid screening across hundreds of millions of peptide sequences, ensuring potent antimicrobial activity and minimizing cytotoxic risks. Through transfer learning, we endowed the LLMs with different domain-specific knowledge to achieve high-throughput mining and generation of AMPs within a unified methodological framework. Notably, both mined and generated AMPs exhibited reduced susceptibility to resistance development in ICU-derived carbapenem-resistant Acinetobacter baumannii (CRAB) and methicillin-resistant Staphylococcus aureus (MRSA) in vitro. The AMPs also showed comparable or superior therapeutic efficacy in in vivo thigh infection mouse models compared with clinical antibiotics, without causing organ damage and disrupting gut microbiota. The mechanisms of action of these AMPs involve disruption of the cytoplasmic membrane and membrane depolarization. Overall, this study presents a generative artificial intelligence approach for the discovery of novel antimicrobials against multidrug-resistant bacteria, enabling efficient and extensive exploration of AMP space.
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