Antimicrobial Peptides and Activities

This study introduces AMP-Diffusion, a generative model for designing antimicrobial peptides, which produces candidates with broad-spectrum antibacterial activity and low toxicity.

The paper develops a peptide-based therapy that targets intracellular Pseudomonas aeruginosa and synergizes with obsolete antibiotics to reduce bacterial reservoirs.

This paper identifies digitiferin, an antimicrobial peptide from coral Acropora digitifera, which exhibits bactericidal activity against Vibrio coralliilyticus under low-salt conditions.

This study uses deep learning to analyze archaeal proteomes, identifying 12,623 potential antimicrobial molecules, with 93% showing in vitro activity and one candidate effective in vivo against bacterial infections.

This paper introduces MPOGAN, a generative adversarial network for designing antimicrobial peptides with multiple desired properties, showing improved performance in antimicrobial activity and reduced cytotoxicity.

This paper discovers a novel antibiotic, paenimycin, that targets multiple-drug-resistant bacteria through a dual-binding mechanism and shows no detectable resistance.

The paper characterizes antimicrobial peptides in lizards, identifying and comparing AMPs across species to understand their evolution and diversity.

This study investigates psoriasin as a natural food preservative, showing its antimicrobial activity and potential for cost-effective production.

This paper introduces AMP-D3, a framework for designing diverse and druggable antimicrobial peptides using diffusion and multimodal deep learning, achieving high accuracy in prediction and validation.

This study identifies 53 potent antimicrobial venom-derived peptides using computational methods and experimental validation, showing promise for combating antibiotic-resistant infections.

This study evaluates the antimicrobial and wound healing properties of epinecidin-1 and its variants, showing synergistic effects with antibiotics against nosocomial pathogens.

This paper introduces LLAMP, an AI model that predicts antimicrobial peptide activity against specific species, identifying key amino acid residues for antibiotic development.

This study identifies 12-hydroxystearic acid as a stimulator of antimicrobial peptide secretion from keratinocytes, enhancing skin immunity against pathogens.

This study evaluates an antibiotic-free antimicrobial combination of bacteriocins and a peptidoglycan hydrolase for treating bovine mastitis, showing effectiveness against mastitis-causing bacteria in vitro and in vivo.

The paper optimizes arginine-rich peptides by introducing D-amino acids and cyclization, enhancing their stability and antimicrobial activity while maintaining cytocompatibility.

This study compares the efficacy of the host defense peptide DMS-DA6 with the antibiotic linezolid in treating N. brasiliensis-induced actinomycetoma in mice, finding DMS-DA6 more effective at lower doses and fewer injections.

The paper investigates how phenylalanine and lysine repeats affect peptide binding to VIM-2 metallo-beta-lactamase, finding that F repeats stabilize complexes and enhance binding when balanced with K residues.

This study shows apamin, a honeybee venom peptide, has antimicrobial effects in Drosophila by targeting harmful bacteria and promoting beneficial ones, improving gut health and barrier integrity.

The paper isolates and analyzes cyclotide genes from Solanaceae plants, showing high sequence identity with reference sequences and providing insights for future cyclotide research.

This study uses molecular dynamics simulations to show that melittin's pore-forming ability depends on initial configuration and membrane composition, with lysine-7 playing a key role in pore formation.

The paper investigates how mutations in protegrin-1 affect its antimicrobial activity against colistin-resistant Klebsiella pneumoniae, finding structural changes have a greater impact than charge reduction.

This paper introduces AMP-SEMiner, an AI framework for discovering antimicrobial peptides from metagenomes, identifying over 1.6 million candidates and validating their antimicrobial activity.

This study shows LL-37 and its citrullinated form suppress IL-17A/F-induced LCN-2 production in bronchial epithelial cells, reducing neutrophil migration and airway inflammation.

This study shows that helicity and membrane permeabilization are not universal requirements for cathelicidin-mediated killing of gram-negative bacteria, and identifies lead compounds with improved selectivity.

The paper demonstrates that adding an N-terminal biphenyl motif from LL-37 to short cathelicidin peptides significantly enhances their antibacterial activity against gram-negative bacteria.

The paper identifies LL-37 variants that kill gram-negative bacteria without membrane disruption and bacteria that are permeabilized without being killed, suggesting alternative mechanisms of antibacterial activity.

This study examines how metal ion environments affect the antimicrobial activity of PrAMPs against Pseudomonas aeruginosa and Escherichia coli, revealing ion-dependent changes in their mode of action.

This study shows human antimicrobial peptides like LL-37 activate bacterial PhoQ-PhoP signaling independently of their bactericidal effects, revealing a new mechanism of bacterial response to host peptides.

PepSeek identifies functional peptides using a combination of large language models and specialized models, achieving high accuracy in antimicrobial peptide discovery.