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 <b>12</b>, 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.