ArticleNature materials2025
De novo design of self-assembling peptides with antimicrobial activity guided by deep learning.
Article in Nature materials, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
What it found
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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.
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Who cites it
41 citing papers in PubMed.
- Artificial intelligence catalyzes antimicrobial peptide design.Synthetic and systems biotechnology · 2027Review
- Artificial intelligence-assisted design of self-assembling peptide hydrogels for neural regeneration: Principles and opportunities.Bioactive materials · 2027Review
- Combating antimicrobial resistance through multimodal data via artificial intelligence.One health (Amsterdam, Netherlands) · 2026Review
- Stimuli-responsive structural transformation of adaptive peptide nanomaterials toward biomedical applications.Materials today. Bio · 2026Review
- Free-standing ultrathin two-dimensional peptide crystals.Nature chemistry · 2026Article
- Assembly delivery of bioactive matters: Advances, challenges, and prospects.Journal of advanced research · 2026Review
- Immunofunctions of Protein and Carbohydrate Assemblies Modulated by Structures Acrossing Scales as Biomaterials.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Bridging stimulus-responsive and dissipative peptide assemblies to build complex interactive biomaterials.Nature reviews. Chemistry · 2026Review
- Time-resolved phenotyping at subcellular resolution reveals shared principles and key trade-offs across antimicrobial peptide activities.bioRxiv : the preprint server for biology · 2026Article
- Unveiling the bioactive landscape of drug inactive ingredients (DIGs) using deep transfer learning.Acta pharmaceutica Sinica. B · 2026Article
- Enzymatic Prenylation of Proteins and Peptides: From Cysteine S-Prenylation to Tryptophan-Selective Biocatalysis.Chemistry (Weinheim an der Bergstrasse, Germany) · 2026Review
- Harnessing Self-Assembling Peptides on γδ T Cells to Enhance Anti-Tumor Immunity.Polymer science & technology (Washington, D.C.) · 2026Article
- Aggregation-State Dynamics Drive Double Cooperativity Between Antimicrobial Peptides LL-37 and HNP1.Angewandte Chemie (International ed. in English) · 2026Article
- Deep learning-driven integrated pipeline for de novo design and synthesis of antimicrobial peptides.npj drug discovery · 2026Article
- In vivo membrane engineering traps Gd-based MRI contrast agents for detecting microhepatocellular carcinoma.Science advances · 2026Article
- Supramolecular engineering of amyloid-inspired tripeptide assemblies enabling tunable piezoelectricity.Nature communications · 2026Article
- Self-Assembling Short Peptide Carriers for Gene Delivery.International journal of molecular sciences · 2026Review
- From Virulence to Therapy: T6SS-Derived Antimicrobial Peptides A7 Combats APEC and MRSA Infections.International journal of molecular sciences · 2026Article
- Research progress of blood-brain barrier penetrating and brain diseases therapy by natural biopolymer - based nanomedicine delivery systems.Materials today. Bio · 2026Review
- Click chemistry-driven tumor theranostics: recent advances, challenges, and future perspectives.Cancer biology & medicine · 2026Review
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Bioinspired materials based on self-assembling peptides are promising for tackling various challenges in biomedical engineering. While contemporary data-driven approaches have led to the discovery of self-assembling peptides with various structures and properties, predicting the functionalities of these materials is still challenging. Here we describe the deep learning-guided de novo design of antimicrobial materials based on self-assembling peptides targeting bacterial membranes to address the emerging problem of bacterial drug resistance. Our approach integrates non-natural amino acids for enhanced peptide self-assembly and effectively predicts the functional activity of the self-assembling peptide materials with minimal experimental annotation. The designed self-assembling peptide leader displays excellent in vivo therapeutic efficacy against intestinal bacterial infection in mice. Moreover, it exhibits an enhanced biofilm eradication capability and does not induce acquired drug resistance. Mechanistic studies reveal that the designed peptide can self-assemble on bacterial membranes to form nanofibrous structures for killing multidrug-resistant bacteria. This work thus provides a strategy to discover functional peptide materials by customized design.
Indexed as
Identifiers
40087536What OpenQuestion holds
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.