Discovery of Novel FtsZ Inhibitors With Antimicrobial Activity by Virtual Screening and In Vitro Biological Evaluation
The filamentous temperature-sensitive protein Z (FtsZ) plays a vital role in bacterial division, making it an important antibacterial target. The inhibitor activity targeting the cleft between the H7 helix and the C-terminal substructural domain exhibited superior binding compared to the GTP binding site. This highlights the potential of the cleft as a promising target for further inhibitor discovery. In this study, we established a virtual screening (VS) pipeline using Discovery Studio software and employed FRED for molecular docking and Functional-Class Fingerprints_6 (FCFP_6) for molecular clustering, resulting in the identification of 38 potentially active compounds. These 38 compounds were then subjected to the following FtsZ inhibition assays, resulting in the four active compounds B6, B21, B26, and B31. Further experiments showed that compounds B6 and B26 exhibited antimicrobial activity with minimum inhibitory concentration (MIC) values of 8 and 32 µg/mL. Finally, molecular dynamics (MD) was used to analyze the binding modes of the protein-ligand. In addition, we predicted the physicochemical properties and toxicity of B6 and B26. In summary, our study successfully identified novel FtsZ inhibitors with antimicrobial activity through VS and in vitro biological evaluation, demonstrating their potential for further investigation.
Authors
- Shaojie Ma (ORCID: https://orcid.org/0000-0002-7951-0104)
- Xinxin Si (ORCID: https://orcid.org/0000-0003-0393-4223)
- Jie Xia (ORCID: https://orcid.org/0000-0002-9567-3763)
- zhengyu Zhang
- Hongwei Jin (ORCID: https://orcid.org/0000-0001-6789-5249)
- Chenliang Qian (ORCID: https://orcid.org/0009-0009-6837-5320)
- Aoqi Luo
Institutions
- Jiangsu University (CN)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Peking University (CN)
Publication Details
- Journal
- Chemistry & Biodiversity
- Published
- 2025-02-03
- DOI
- https://doi.org/10.1002/cbdv.202403042
- Citations
- 2
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 3.01