ArticleJournal of advanced research2025
Machine learning and genetic algorithm-guided directed evolution for the development of antimicrobial peptides.
Article in Journal of advanced research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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.
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Who cites it
10 citing papers in PubMed, 23 citations in OpenAlex.
- Artificial intelligence catalyzes antimicrobial peptide design.Synthetic and systems biotechnology · 2027Review
- Lipidomic Profile Reconstruction of Therapeutic Membrane Targets Using Physics-Based Optimization with Limited Activity Data.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- AI-driven drug design: a comprehensive review.Journal of computer-aided molecular design · 2026Review
- Heuristic multi-site optimization for protein sequence design using Masked Protein Language Models.PLoS computational biology · 2026Article
- CAMPER: mechanistic artificial intelligence for designing peptides that target MRSA persisters.Nature communications · 2026Article
- A novel fuzzy system-based genetic algorithm for trajectory segment generation in urban global positioning system.Journal of advanced research · 2026Article
- AI-Based D-Amino Acid Substitution for Optimizing Antimicrobial Peptides to Treat Multidrug-Resistant Bacterial Infection.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- DLFea4AMPGen de novo design of antimicrobial peptides by integrating features learned from deep learning models.Nature communications · 2025Article
- Enhancing Antimicrobial Peptide Activity through Modifications of Charge, Hydrophobicity, and Structure.International journal of molecular sciences · 2024Review
- An Engineered Nisin Analogue with a Hydrophobic Moiety Attached at Position 17 Selectively InhibitsACS chemical biology · 2024Article
Corrections and comments
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Authors and funding
12 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionAntimicrobial peptides (AMPs) are valuable alternatives to traditional antibiotics, possess a variety of potent biological activities and exhibit immunomodulatory effects that alleviate difficult-to-treat infections. Clarifying the structure-activity relationships of AMPs can direct the synthesis of desirable peptide therapeutics.
objectivesIn this study, the lipopolysaccharide-binding domain (LBD) was identified through machine learning-guided directed evolution, which acts as a functional domain of the anti-lipopolysaccharide factor family of AMPs identified from Marsupenaeus japonicus.
methodsLBD
resultsThe NMR solution structure showed that LBD
conclusionsThe findings of this study pave the way for the rational drug design of activity-enhanced peptide antibiotics.
Indexed as
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What 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.