AIMC Topic: Antimicrobial Peptides
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AI-Driven Antimicrobial Peptide Discovery: Mining and Generation.
Accounts of chemical research
Jun 3, 2025
ConspectusThe escalating threat of antimicrobial resistance (AMR) poses a significant global health crisis, potentially surpassing cancer as a leading cause of death by 2050. Traditional antibiotic discovery methods have not kept pace with the rapidl...
AMPGen: an evolutionary information-reserved and diffusion-driven generative model for de novo design of antimicrobial peptides.
Communications biology
May 30, 2025
The rapid advancement of artificial intelligence (AI) has enabled de novo design of functional proteins, circumventing the reliance on natural templates or sequencing databases. However, current protein design models are ineffective in generating pro...
Antifungal activity and mechanism of novel peptide antimicrobial peptide (GmAMP) against fluconazole-resistant .
PeerJ
May 20, 2025
BACKGROUND: There is a pressing need to create innovative alternative treatment approaches considering the overuse of antifungal drugs causes the number of clinically isolated fluconazole-resistant species to increase. antimicrobial peptide (GmAMP)...
BERT-AmPEP60: A BERT-Based Transfer Learning Approach to Predict the Minimum Inhibitory Concentrations of Antimicrobial Peptides for and .
Journal of chemical information and modeling
Mar 14, 2025
Antimicrobial peptides (AMPs) are a promising alternative for combating bacterial drug resistance. While current computer prediction models excel at binary classification of AMPs based on sequences, there is a lack of regression methods to accurately...
Exploring the repository of de novo-designed bifunctional antimicrobial peptides through deep learning.
eLife
Mar 13, 2025
Antimicrobial peptides (AMPs) are attractive candidates to combat antibiotic resistance for their capability to target biomembranes and restrict a wide range of pathogens. It is a daunting challenge to discover novel AMPs due to their sparse distribu...
MDTL-ACP: Anticancer Peptides Prediction Based on Multi-Domain Transfer Learning.
IEEE journal of biomedical and health informatics
Mar 6, 2025
Anticancer peptides (ACPs) have emerged as one of the most promising therapeutic agents for cancer treatment. They are bioactive peptides featuring broad-spectrum activity and low drug-resistance. The discovery of ACPs via traditional biochemical met...
Fluorescent sensor array for rapid bacterial identification using antimicrobial peptide-functionalized gold nanoclusters and machine learning.
Talanta
Mar 3, 2025
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...
ML-AMPs designed through machine learning show antifungal activity against C. albicans and therapeutic potential on mice model with candidiasis.
Life sciences
Feb 19, 2025
AIMS: C. albicans resistant strains have led to increasingly severe treatment challenges. Antimicrobial peptides with low resistance-inducing propensity for pathogens have been developed. A series of antimicrobial peptides de novo designed through ma...
Deep Learning for Antimicrobial Peptides: Computational Models and Databases.
Journal of chemical information and modeling
Feb 10, 2025
Antimicrobial peptides are a promising strategy to combat antimicrobial resistance. However, the experimental discovery of antimicrobial peptides is both time-consuming and laborious. In recent years, the development of computational technologies (es...
MSCMamba: Prediction of Antimicrobial Peptide Activity Values by Fusing Multiscale Convolution with Mamba Module.
The journal of physical chemistry. B
Feb 6, 2025
Antimicrobial peptides (AMPs) have important developmental prospects as potential candidates for novel antibiotics. Although many studies have been devoted to the identification of AMPs and the qualitative prediction of their functional activities, f...
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