Recently, the high proportion of methicillin-resistant Staphylococcus aureus infections worldwide has highlighted the urgent need for novel antibiotics to combat this crisis. The recent progress in computational techniques for use in health and medicine, especially artificial intelligence (AI), has created new and potential approaches to combat antibiotic-resistant bacteria, such as repurposing existing drugs, optimizing current agents, and designing novel compounds. Halicin was previously used as a diabetic medication, acting as a c-Jun N-terminal protein kinase (JNK) inhibitor, and has recently demonstrated unexpected antibacterial activity. Although previous efforts have highlighted halicin's potential as a promising antibiotic, evidence regarding its effectiveness against clinical strains remains limited, with insufficient proof of its clinical applicability. In this study, we sought to investigate the antibacterial activity of halicin against MRSA clinical strains to validate its clinical applicability, and a C. elegans model infected by MRSA was employed to evaluate the in vivo effect of halicin against MRSA. Our findings revealed the antibacterial activity of halicin against methicillin-resistant S. aureus clinical strains with MICs ranging from 2 to 4 µg/mL. Our study is also the first work to evaluate the in vivo effect of halicin against S. aureus using a C. elegans model, supporting its further development as an antibiotic.
Keywords: Caenorhabditis elegans; halicin; in vivo evaluation; methicillin-resistant Staphylococcus aureus.