Discovery of Novel MsbA Inhibitors with a Bivalent Molecular Generative Model

MsbA, a bacterial ABC transporter essential for lipopolysaccharide
(LPS) transport, is a promising target for treating multidrug-resistant
infections. However, developing potent MsbA inhibitors remains challenging.
Recently, cerastecin C, representing a class of bivalent inhibitors
targeting the MsbA dimer interface, demonstrated in vivo efficacy
against multidrug-resistant Gram-negative bacteria, despite high plasma
protein binding, by blocking LPS translocation essential for bacterial
survival. In this study, we developed a bivalent molecular generative
model, BL-INVENT, focusing on linker design to optimize the structure
of cerastecin C. Several generative model designed compounds were
synthesized and exhibited antibacterial activity. Further optimization
led to the identification of compound 12, which showed
enhanced potency and lower plasma protein binding compared with cerastecin
C. These findings demonstrate an effective AI-driven strategy for
the development of next-generation MsbA inhibitors.