ArticleeLife2025
Exploring the repository of de novo-designed bifunctional antimicrobial peptides through deep learning.
Article in eLife, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- Nano-antimicrobial peptides (Nano-AMPs) to combat resistant gram-negative bacteria.Drug delivery and translational research · 2026Review
- Emerging antimicrobial peptides in gastrointestinal disorders: Dual role in immunity and therapy.World journal of gastrointestinal pharmacology and therapeutics · 2026Review
- A unified framework for potency-oriented AMP discovery via multi-modal learning and guided sequence synthesis.PLoS computational biology · 2026Article
- Noncanonical bactericidal activity of teleost type I interferon is conferred by a membrane-targeting C-terminal peptide.PLoS pathogens · 2026Article
- Combating Antibacterial Resistance: The Integrative Role of Artificial Intelligence in Bio-Based Product Development.Antibiotics (Basel, Switzerland) · 2026Review
- Topology-Aware Generation and Activity-Based Filtering: A Computational-Experimental Framework for Data-Scarce Quaternary Ammonium Compound Discovery.Journal of chemical information and modeling · 2026Article
- The rise and future of peptide-based antimicrobials.Journal of microbiology (Seoul, Korea) · 2026Review
- Lab to codes: multimodel advanced AI-driven pipelines to drive antimicrobial peptide design for the post-antibiotic era.Frontiers in cellular and infection microbiology · 2026Review
- Antimicrobial peptides in the era of resistance: integrating AI-driven design, host-microbe interactions, and nanotechnological delivery.Frontiers in microbiology · 2026Review
- Nanosystems for delivery of indolicidin peptide.Frontiers in medical technology · 2026Review
- Harnessing Machine Learning Approaches for the Identification, Characterization, and Optimization of Novel Antimicrobial Peptides.Antibiotics (Basel, Switzerland) · 2025Review
- A novel generative framework for designing pathogen-targeted antimicrobial peptides with programmable physicochemical properties.PLoS computational biology · 2025Article
- Diffusion Models at the Drug Discovery Frontier: A Review on Generating Small Molecules Versus Therapeutic Peptides.Biology · 2025Review
- Painting Peptides With Antimicrobial Potency Through Deep Reinforcement Learning.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- DLFea4AMPGen de novo design of antimicrobial peptides by integrating features learned from deep learning models.Nature communications · 2025Article
- Article
- AI-Driven Antimicrobial Peptide Discovery: Mining and Generation.Accounts of chemical research · 2025Review
- Progress in the Identification and Design of Novel Antimicrobial Peptides Against Pathogenic Microorganisms.Probiotics and antimicrobial proteins · 2025Review
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
Antimicrobial peptides (AMPs) are attractive candidates to combat antibiotic resistance for their capability to target biomembranes and restrict a wide range of pathogens. It is a daunting challenge to discover novel AMPs due to their sparse distributions in a vast peptide universe, especially for peptides that demonstrate potencies for both bacterial membranes and viral envelopes. Here, we establish a de novo AMP design framework by bridging a deep generative module and a graph-encoding activity regressor. The generative module learns hidden 'grammars' of AMP features and produces candidates sequentially pass antimicrobial predictor and antiviral classifiers. We discovered 16 bifunctional AMPs and experimentally validated their abilities to inhibit a spectrum of pathogens in vitro and in animal models. Notably, P076 is a highly potent bactericide with the minimal inhibitory concentration of 0.21 μM against multidrug-resistant
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.