发现新型MsbA抑制剂与双对应分子生成模型的发现
Haodi Qiu1,2, Lei Wang3, Baiqing Li2
1Laboratory of Molecular Design and Drug Discovery, School of Science, China Pharmaceutical University, Nanjing 211198, China.
Journal of chemical information and modeling
|November 3, 2025
概括
研究人员开发了一种人工智能模型来设计针对细菌MsbA的新药,MsbA是脂多糖 (LPS) 的关键载体. 这导致了化合物12,一种具有减少蛋白质结合的强效抑制剂,提供了对抗多药耐药性感染的新策略.
科学领域:
- 微生物学 微生物学
- 药物发现 药物发现 药物发现
- 计算化学计算化学
背景情况:
- MsbA是脂聚糖体 (LPS) 运输的关键细菌ABC载体,是对抗多药耐药性感染的关键目标.
- 开发有效的MsbA抑制剂是具有挑战性的,原因是诸如高血蛋白结合等因素,这些因素与诸如素C等化合物观察到.
研究的目的:
- 使用双价分子生成模型BL-INVENT优化素C的结构,重点是链接器设计.
- 识别具有增强功效和改善药物动力学特性的新型MsbA抑制剂,例如减少血蛋白结合.
主要方法:
- 开发一种双价分子生成模型,BL-INVENT,用于设计新型MsbA抑制剂.
- 通过BL-INVENT模型生成的化合物的合成和抗菌活性评估.
- 结构-活动关系研究和优化,导致组合12.
主要成果:
- 几种由生成模型设计的合成化合物表现出抗菌活性.
- 与素C相比,化合物12对抗多药耐药细菌具有更强的功效.
- 化合物12显示血蛋白结合的程度明显低于素C.
结论:
- 人工智能驱动的BL-INVENT模型对于设计下一代MsbA抑制剂是有效的.
- 优化的双价抑制剂,如化合物12,为治疗多药耐药的格拉姆阴性细菌感染提供了有希望的策略.
- 降低血蛋白结合是一种可行的方法来提高MsbA抑制剂的疗效.
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