深度学习引导IL23/IL23R宏分子抑制剂的发现:一个整合性框架,将虚拟查和实验验证相结合
Abdul Manan1, Hana Seo1, Muhammad Haseeb2
1Department of Molecular Science and Technology, Ajou University, Suwon, 16499, Republic of Korea.
International journal of biological macromolecules
|January 29, 2026
概括
研究人员发现了一种新型抑制剂,Inh-31,该抑制剂准了介乐金-23 (IL23) /IL23受体 (IL23R) 相互作用. 这一发现提供了通过阻断IL23信号传递来治疗慢性炎症疾病的新疗法策略.
科学领域:
- 生物化学 生物化学
- 免疫学 免疫学 免疫学
- 药物发现 药物发现 药物发现
背景情况:
- 干白素-23 (IL23) 信号传递在慢性炎症疾病 (如牛皮) 中至关重要.
- 针对IL23/IL23受体 (IL23R) 蛋白质与蛋白质相互作用 (PPI) 提供了比生物药物更好的治疗优势.
研究的目的:
- 发现和机理性地描述IL23/IL23R相互作用的强效抑制剂.
- 为了识别能够阻止IL23信号传递的新型小分子.
主要方法:
- 使用深度生成模型 (SAFE) 来设计新的p19准支架.
- 采用虚拟查,从商用化合物中识别潜在的候选药物.
- 进行细胞查和全原子分子动力学 (MD) 模拟,以获得机械洞察力.
主要成果:
- 通过细胞查,Inh-31被确定为一种强大的IL23/IL23R抑制剂.
- MD模拟显示,Inh-31与IL23/IL23R接口结合,取代了原生结合相互作用.
- 结合Inh-31会诱导IL23R的全稳定,从而阻止JAK-STAT3级联.
结论:
- 通过使IL23R稳定在非信号状态下,Inh-31有效地抑制IL23信号传递.
- 这一发现为IL23驱动的炎症状况提供了一个有前途的小分子治疗方法.
- 这些发现突显了深度生成模型和MD模拟在药物发现中的潜力.
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