AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
Findings support bat gut bacteria as an underexplored source of AMP candidates and candidate bacteriocins from the gut bacteria of the Asian particolored bat Vespertilio sinensis.
The utility of deep learning for prioritizing novel AMP candidates while highlighting the importance of experimental validation is demonstrated and the identified candidates provide a valuable resource for future functional studies and the development of peptide-based antimicrobial therapeutics.
A stability-centric computational discovery pipeline to identify and characterize novel antimicrobial peptides with potent and selective bactericidal activity against ESKAPE pathogens and to validate the lead candidates through experimental in vitro assays provided a generally applicable strategy for accelerating the d...
It is argued that the realistic near-term contribution of animal-derived AMPs lies in combination therapy with existing antibiotics and in topical or localised indications with direct clinical evidence, while their use as stand-alone systemic agents remains a preclinical and early-clinical prospect rather than an estab...
Overall, this hybrid strategy effectively uncovers the antimicrobial complexity of BS4, revealing 'cryptic' peptide candidates with therapeutic potential.
The rapid rise of multidrug-resistant pathogens, poses a serious global threat, highlighting the need for new antimicrobial solutions. In this context, antimicrobial peptides (AMPs) have emerged as strong therapeutic candidates. Among potential targets, the MurT ligase, an ATP-dependent and highly conserved enzyme in G...
This study provides an experimental assessment of model-guided AMP discovery and a reproducible route from computational prediction to validated antimicrobial candidates, while revealing biases and generalizability limits of AI-based AMP inference.
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