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Antimicrobial Peptides

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AmpClass: an Antimicrobial Peptide Predictor Based on Supervised Machine Learning.

Anais da Academia Brasileira de Ciencias
In the last decades, antibiotic resistance has been considered a severe problem worldwide. Antimicrobial peptides (AMPs) are molecules that have shown potential for the development of new drugs against antibiotic-resistant bacteria. Nowadays, medicin...

Machine Learning-Driven Discovery and Evaluation of Antimicrobial Peptides from Mucus Proteome.

Marine drugs
Marine antimicrobial peptides (AMPs) represent a promising source for combating infections, especially against antibiotic-resistant pathogens and traditionally challenging infections. However, traditional drug discovery methods face challenges such a...

Protein Language Models and Machine Learning Facilitate the Identification of Antimicrobial Peptides.

International journal of molecular sciences
Peptides are bioactive molecules whose functional versatility in living organisms has led to successful applications in diverse fields. In recent years, the amount of data describing peptide sequences and function collected in open repositories has s...

Discovery of AMPs from random peptides via deep learning-based model and biological activity validation.

European journal of medicinal chemistry
The ample peptide field is the best source for discovering clinically available novel antimicrobial peptides (AMPs) to address emerging drug resistance. However, discovering novel AMPs is complex and expensive, representing a major challenge. Recent ...

PepNet: an interpretable neural network for anti-inflammatory and antimicrobial peptides prediction using a pre-trained protein language model.

Communications biology
Identifying anti-inflammatory peptides (AIPs) and antimicrobial peptides (AMPs) is crucial for the discovery of innovative and effective peptide-based therapies targeting inflammation and microbial infections. However, accurate identification of AIPs...

Enhanced prediction of hemolytic activity in antimicrobial peptides using deep learning-based sequence analysis.

BMC bioinformatics
Antimicrobial peptides (AMPs) are a promising class of antimicrobial drugs due to their broad-spectrum activity against microorganisms. However, their clinical application is limited by their potential to cause hemolysis, the destruction of red blood...

Novel active Trp- and Arg-rich antimicrobial peptides with high solubility and low red blood cell toxicity designed using machine learning tools.

International journal of antimicrobial agents
BACKGROUND: Given the rising number of multidrug-resistant (MDR) bacteria, there is a need to design synthetic antimicrobial peptides (AMPs) that are highly active, non-hemolytic, and highly soluble. Machine learning tools allow the straightforward i...

SAMP: Identifying antimicrobial peptides by an ensemble learning model based on proportionalized split amino acid composition.

Briefings in functional genomics
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...

Machine learning accelerates the discovery of epitope-based dual-bioactive peptides against skin infections.

International journal of antimicrobial agents
OBJECTIVES: Skin injuries and infections are an inevitable part of daily human life, particularly with chronic wounds, becoming an increasing socioeconomic burden. In treating skin infections and promoting wound healing, bioactive peptides may hold s...

Functional antimicrobial peptide-loaded 3D scaffolds for infected bone defect treatment with AI and multidimensional printing.

Materials horizons
Infection is the most prevalent complication of fractures, particularly in open fractures, and often leads to severe consequences. The emergence of bacterial resistance has significantly exacerbated the burden of infection in clinical practice, makin...