1. Academic Validation
  2. Discovery of Novel MsbA Inhibitors with a Bivalent Molecular Generative Model

Discovery of Novel MsbA Inhibitors with a Bivalent Molecular Generative Model

  • J Chem Inf Model. 2025 Nov 24;65(22):12179-12188. doi: 10.1021/acs.jcim.5c01426.
Haodi Qiu 1 2 Lei Wang 3 Baiqing Li 2 Song Wu 3 Yadong Chen 1 Ting Ran 2 Jie Xia 3 Hongming Chen 4 2
Affiliations

Affiliations

  • 1 Laboratory of Molecular Design and Drug Discovery, School of Science, China Pharmaceutical University, Nanjing 211198, China.
  • 2 Division of Drug and Vaccine Research, Guangzhou National Laboratory, Guangzhou, Guangdong 510005, China.
  • 3 State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.
  • 4 School of Pharmaceutical Sciences, Guangzhou Medical University, Guangzhou 511436, China.
Abstract

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.

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