在NMR,X射线晶体学和机器学习的指导下,概括Nrf2对KEAP1的结合 afinity
Journal of the American Chemical Society
|March 8, 2021
概括
宏环可以有效地向蛋白-蛋白相互作用 (PPI),如KEAP1-Nrf2相互作用. 优化循环形状,而不是残留物,显著增强了KEAP1的结合亲和力.
科学领域:
- 生物化学
- 结构生物学
- 医学化学
背景情况:
- 蛋白与蛋白相互作用 (PPI) 在细胞过程中至关重要.
- 针对Kelch类ECH相关蛋白-1 (KEAP1) 和核因子 (红色素衍生2) 类2 (Nrf2) 的PPI是一个治疗挑战.
- 宏环为调节PPI提供了一个有前途的策略.
研究的目的:
- 开发一种针对KEAP1-Nrf2相互作用的高亲和度宏环.
- 研究构造优化在增强结合亲和度中的作用.
- 了解联体受体系统中的形状预组织和应变之间的相互作用.
主要方法:
- 用X射线结晶学和NMR光谱进行结构确定.
- 计算建模和机器学习用于分析连接体应变和构造.
- 合成和亲和度测量 (K_D).
主要成果:
- 一个循环的7-mer,c[(D) -β-homoAla-DPETGE,实现了对KEAP1的20nM结合亲和力,比线性 (4.3μM) 有显著的改善.
- 构造优化,包括普林替代和改变残留物几何,增强结合而不改变KEAP1相互作用的残留物.
- 对X射线结构的机器学习分析确定了与结合亲和关系相关的菌株模式,突出了ETGE动机中形状预组织和减少菌株的重要性.
结论:
- 通过构造优化进行宏环设计是实现高亲和度PPI向的可行策略.
- 在优化结合方面,了解和最小化连接体应变,以及构造前组织,是关键因素.
- 这种方法为剖析其他联体受体相互作用中的构造效应提供了洞察力.
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