Wang Luqi, Geng Zhiyuan, Liu Yuhang, Cao Linhui, Liu Yao, Zhang Hourui, Bi Yi, Lu Jing
School of Pharmacy, Key Laboratory of Molecular Pharmacology and Drug Evaluation (Yantai University), Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai 264005, China.
Molecules. 2025 Apr 29;30(9):1983. doi: 10.3390/molecules30091983.
Fusidic acid (FA), a tetracyclic triterpenoid, has been approved to treat methicillin-resistant Staphylococcus aureus (MRSA) infections. However, there are few reports about FA derivatives with high efficacy superior to FA, manifesting the difficulty of discovering the derivatives based on experience-based drug design. In this study, we employed a stepwise method to discover novel FA derivatives. First, molecular dynamics (MD) simulations were performed to identify the molecular mechanism of FA against elongation factor G (EF-G) and drug resistance. Then, we utilized a scaffold decorator to design novel FA derivatives at the 3- and 21-positions of FA. The ligand-based and structure-based screening models, including Chemprop and RTMScore, were employed to identify promising hits from the generated set. Ten generated FA derivatives with high efficacy in the Chemprop and RTMScore models were synthesized for in vitro testing. Compounds and demonstrated a 2-fold increase in potency against MRSA strains compared to FA. This study highlights the significant impact of AI-based methods on the design of novel FA derivatives with drug efficacy, which provides a new approach for drug discovery.
夫西地酸（FA）是一种四环三萜类化合物，已被批准用于治疗耐甲氧西林金黄色葡萄球菌（MRSA）感染。然而，关于疗效优于FA的FA衍生物的报道很少，这表明基于经验性药物设计发现这些衍生物具有难度。在本研究中，我们采用逐步方法来发现新型FA衍生物。首先，进行分子动力学（MD）模拟以确定FA对抗延伸因子G（EF - G）的分子机制及耐药性。然后，我们利用骨架修饰器在FA的3位和21位设计新型FA衍生物。基于配体和基于结构的筛选模型，包括Chemprop和RTMScore，被用于从生成的化合物集中识别有前景的命中物。合成了在Chemprop和RTMScore模型中具有高效能的10种生成的FA衍生物用于体外测试。化合物 和 对MRSA菌株的效力相比FA提高了2倍。本研究突出了基于人工智能的方法对设计具有药物疗效的新型FA衍生物的重大影响，为药物发现提供了一种新方法。
