Tuesday, July 14, 2026

Machine learning-guided discovery of covalent sortase A inhibitors targeting MRSA virulence

Xu-liang Xu, Ti-ti Ying, Xiao-wen Wu, Yun-jun Chen, Gang-ao Hu, Yu-tian Guan, Shi-yi Liu, He Wang, Mohamed Seif, Mahmoud Emam, Hong Wang, Wei Hou, Bin Wei,

European Journal of Medicinal Chemistry, 2026119139,

https://doi.org/10.1016/j.ejmech.2026.119139

The global rise of methicillin-resistant Staphylococcus aureus (MRSA) has highlighted the urgent need for alternative therapeutic strategies beyond conventional bactericidal antibiotics. Targeting bacterial virulence rather than viability represents a promising approach to mitigate selective pressure and delay resistance development. Sortase A (SrtA), a membrane-associated transpeptidase responsible for anchoring virulence-associated surface proteins, is an attractive anti-virulence target due to its non-essential role in bacterial survival. Here, we report a machine learning-guided strategy for the discovery of novel covalent SrtA inhibitors based on a 1,2-benzoselenazol-3-one (BSEA) scaffold featuring a tunable electrophilic Se–N bond. A scaffold-aware classification model with a Tanimoto similarity constraint trained on 529 SrtA inhibitors enabled prospective virtual screening of over 35,000 BSEA and BTA derivatives, leading to a high hit rate of 89% upon experimental validation. Representative compounds exhibited submicromolar SrtA inhibition (IC50 = 0.84–1.04 μM) while showing minimal effects on bacterial growth (MIC = 8–32 μM), indicating effective functional decoupling of virulence and viability. Mechanistic studies demonstrated time-dependent irreversible inhibition kinetics, supported by jump dilution assays and Nano-LC-MS/MS identification of covalent modification at the catalytic residue Cys184. These inhibitors effectively disrupted MRSA biofilm formation at sub-inhibitory concentrations and significantly improved host survival in a Galleria mellonella infection model. Collectively, this study establishes a data-driven framework integrating machine learning and covalent chemistry for anti-virulence drug discovery and provides promising lead compounds targeting SrtA to combat MRSA infections.

An enantioselective covalent inhibitor of BAX confers cytoprotection in vivo

Peiwen Shi, Bruno Melillo, Matthew W. McHenry, Christina M. Camara, Ka Yang, Evert Njomen, Marina Godes, Maria F. Pazyra-Murphy, Mary Rose B...