AIMC Topic: Antimicrobial Peptides
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ConsAMPHemo: A computational framework for predicting hemolysis of antimicrobial peptides based on machine learning approaches.
Protein science : a publication of the Protein Society
Jul 1, 2025
Many antimicrobial peptides (AMPs) function by disrupting the cell membranes of microbes. While this ability is crucial for their efficacy, it also raises questions about their safety. Specifically, the membrane-disrupting ability could lead to hemol...
Antimicrobial peptide developed with machine learning sequence optimization targets drug resistant Staphylococcus aureus in mice.
The Journal of clinical investigation
Jun 16, 2025
As antimicrobial resistance rises, new antibacterial candidates are urgently needed. Using sequence space information from over 14,743 functional antimicrobial peptides (AMPs), we improved the antimicrobial properties of citropin 1.1, an AMP with wea...
Discovery of naturally inspired antimicrobial peptides using deep learning.
Bioorganic chemistry
Jun 15, 2025
Non-ribosomal peptides (NRPs) are promising lead compounds for novel antibiotics. Bioinformatic mining of silent microbial NRPS gene clusters provide crucial insights for the discovery and de novo design of bioactive peptides. Here, we describe the e...
Lead Informed Artificial Intelligence Mining of Antitubercular Host Defense Peptides.
Biomacromolecules
May 12, 2025
Identifying host defense peptides (HDPs) that are effective against drug-resistant infections is challenging due to their vast sequence space. Artificial intelligence (AI)-guided design can accelerate HDP discovery, but it traditionally requires larg...
Deep-Learning-Based Approaches for Rational Design of Stapled Peptides With High Antimicrobial Activity and Stability.
Microbial biotechnology
Mar 1, 2025
Antimicrobial peptides (AMPs) face stability and toxicity challenges in clinical use. Stapled modification enhances their stability and effectiveness, but its application in peptide design is rarely reported. This study built ten prediction models fo...
IAMPDB: A Knowledgebase of Manually Curated Insects-Derived Antimicrobial Peptides.
Journal of peptide science : an official publication of the European Peptide Society
Mar 1, 2025
Insects, a majority of animal species, rely on innate immunity and antimicrobial peptides (AMPs), which are a part of their innate immunity, to combat diverse parasites and pathogens. These peptides have applications ranging from agriculture to antim...
AI Methods for Antimicrobial Peptides: Progress and Challenges.
Microbial biotechnology
Jan 1, 2025
Antimicrobial peptides (AMPs) are promising candidates to combat multidrug-resistant pathogens. However, the high cost of extensive wet-lab screening has made AI methods for identifying and designing AMPs increasingly important, with machine learning...
SAMP: Identifying antimicrobial peptides by an ensemble learning model based on proportionalized split amino acid composition.
Briefings in functional genomics
Dec 6, 2024
It is projected that 10 million deaths could be attributed to drug-resistant bacteria infections in 2050. To address this concern, identifying new-generation antibiotics is an effective way. Antimicrobial peptides (AMPs), a class of innate immune eff...
De novo synthetic antimicrobial peptide design with a recurrent neural network.
Protein science : a publication of the Protein Society
Aug 1, 2024
Antibiotic resistance is recognized as an imminent and growing global health threat. New antimicrobial drugs are urgently needed due to the decreasing effectiveness of conventional small-molecule antibiotics. Antimicrobial peptides (AMPs), a class of...
Structure-aware deep learning model for peptide toxicity prediction.
Protein science : a publication of the Protein Society
Jul 1, 2024
Antimicrobial resistance is a critical public health concern, necessitating the exploration of alternative treatments. While antimicrobial peptides (AMPs) show promise, assessing their toxicity using traditional wet lab methods is both time-consuming...
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