AIMC Topic: Antimicrobial Peptides

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Potential application of Healitide-GP1, a novel antibacterial peptide, in wound healing: in vitro studies.

Scientific reports
Wound healing is a complex process that can be compromised by bacterial infections, leading to delayed healing and an increased risk of complications. The aim of this study was to design and develop a novel antibacterial peptide, Healitide-GP1, which...

Design, characterization, and application of novel antimicrobial peptides against Bacillus cereus.

International journal of food microbiology
Foodborne pathogens such as Bacillus cereus threaten food safety, necessitating novel antimicrobial solutions. Antimicrobial peptides (AMPs) offer broad-spectrum activity and potential applications in food preservation. In this study, we designed a l...

AMPGP: Discovering Highly Effective Antimicrobial Peptides via Deep Learning.

Journal of chemical information and modeling
Antimicrobial peptides (AMPs) have emerged as vital candidates in the fight against antibiotic resistance. The traditional processes for AMP design and discovery are often time-consuming and inefficient. Here, we propose the AMPGP model, which employ...

AAGP integrates physicochemical and compositional features for machine learning-based prediction of anti-aging peptides.

Scientific reports
Aging is a natural phenomenon characterized by the loss of normal morphology and physiological functioning of the body, causing wrinkles on the skin, loss of hair, and compromised immune systems. Peptide therapies have emerged as a promising approach...

Computational exploration of global venoms for antimicrobial discovery with Venomics artificial intelligence.

Nature communications
The rise of antibiotic-resistant pathogens, particularly gram-negative bacteria, highlights the urgent need for novel therapeutics. Drug-resistant infections now contribute to approximately 5 million deaths annually, yet traditional antibiotic discov...

Antimicrobial Peptides Design Using Deep Learning and Rational Modifications: Activity in Bacteria, Candida albicans, and Cancer Cells.

Current microbiology
Resistance to antimicrobial agents has become a global threat, estimated to cause 10-million deaths annually by 2050. Antimicrobial peptides are emerging as an alternative and offer advantages over traditional antibiotics. Antimicrobial peptides gene...

Deep Learning in Antimicrobial Peptide Prediction.

Journal of chemical information and modeling
Antimicrobial peptides (AMPs) have garnered significant attention from researchers as effective alternatives to antibiotics. In recent years, deep learning has demonstrated unique advantages in AMP prediction, surpassing traditional machine learning ...

AI-Accelerated Identification of Novel Antimicrobial Peptides for Inhibiting .

Journal of agricultural and food chemistry
Fusarium head blight caused by threatens global wheat production, causing substantial yield reduction and mycotoxin accumulation. This study harnessed machine learning to accelerate the discovery of antifungal peptides targeting this phytopathogen. ...

Discovery of milk-derived antimicrobial peptides in human milk by DeepMAMP based on peptidomics technology and deep learning method.

Food chemistry
Milk-derived antimicrobial peptides (MAMPs) in human milk (HMAMPs) play an important role in the nutrition and the immune system construction of newborns. Current AMP prediction models cannot accurately predict HMAMPs, thus high-throughput and target...

Disruption of Hsp70.14-BAG2 Protein-Protein interactions using deep Learning-Driven peptide design and molecular simulations.

Computers in biology and medicine
Protein-protein interactions (PPIS) are critical in proteostasis, stress response, and disease progression. Targeting the interaction between Hsp70.14 and BAG2, a co-chaperone implicated in oncogenic survival, offers a promising therapeutic approach....