AIMC Topic: Antimicrobial Peptides

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Identification of antimicrobial peptides from the human gut microbiome using deep learning.

Nature biotechnology
The human gut microbiome encodes a large variety of antimicrobial peptides (AMPs), but the short lengths of AMPs pose a challenge for computational prediction. Here we combined multiple natural language processing neural network models, including LST...

AMPlify: attentive deep learning model for discovery of novel antimicrobial peptides effective against WHO priority pathogens.

BMC genomics
BACKGROUND: Antibiotic resistance is a growing global health concern prompting researchers to seek alternatives to conventional antibiotics. Antimicrobial peptides (AMPs) are attracting attention again as therapeutic agents with promising utility in ...

Accelerating antibiotic discovery through artificial intelligence.

Communications biology
By targeting invasive organisms, antibiotics insert themselves into the ancient struggle of the host-pathogen evolutionary arms race. As pathogens evolve tactics for evading antibiotics, therapies decline in efficacy and must be replaced, distinguish...

HemoNet: Predicting hemolytic activity of peptides with integrated feature learning.

Journal of bioinformatics and computational biology
Quantifying the hemolytic activity of peptides is a crucial step in the discovery of novel therapeutic peptides. Computational methods are attractive in this domain due to their ability to guide wet-lab experimental discovery or screening of peptides...

Machine learning-driven discovery of antimicrobial peptides targeting the GAPDH-TPI protein-protein interaction in Schistosoma mansoni for novel antischistosomal therapeutics.

Computational biology and chemistry
Schistosomiasis, caused by Schistosoma mansoni, remains a significant public health burden, particularly in endemic regions with limited access to effective treatment. The emergence of resistance to praziquantel necessitates the urgent discovery of n...

Fluorescent sensor array for rapid bacterial identification using antimicrobial peptide-functionalized gold nanoclusters and machine learning.

Talanta
Bacterial infectious diseases pose significant challenges to public health, emphasizing the need for rapid and accurate diagnostic tools. Here, we introduced a multichannel fluorescent sensor array based on antimicrobial peptide-functionalized gold n...

Screening and preliminary analysis of antimicrobial peptide genes in Octopussinensis.

Fish & shellfish immunology
Antimicrobial peptides (AMPs) are small molecular peptides that widely exist in organisms to resist external microbial invasion and play a crucial role in the host's immune defense system. Owing to their functions of efficient broad-spectrum killing ...

Optimal Descriptor Subset Search via Chemical Information and Target Activity-Guided Algorithm for Antimicrobial Peptide Prediction.

Journal of chemical information and modeling
Antimicrobial peptides (AMPs) have emerged as a promising alternative to conventional drugs due to their potential applications in combating multidrug-resistant pathogens. Various computational approaches have been developed for AMP prediction, rangi...

ConsAMPHemo: A computational framework for predicting hemolysis of antimicrobial peptides based on machine learning approaches.

Protein science : a publication of the Protein Society
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
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...