循环结构组合的计算预测和 Keap1 结合器设计的应用
Francini Fonseca Lopez1, Jiayuan Miao1, Jovan Damjanovic1
1Department of Chemistry, Tufts University, Medford, Massachusetts 02155, United States.
Journal of chemical information and modeling
|November 2, 2023
概括
这项研究引入了一种计算方法来设计抑制蛋白质-蛋白质相互作用的循环. 模拟预测预组织,有助于开发选择性抑制剂对癌症等疾病.
科学领域:
- 生物化学 生物化学
- 计算生物学 计算生物学
- 药物发现 药物发现 药物发现
背景情况:
- 核因素红色素2相关因子2 (Nrf2) 是氧化应激反应的关键调节者.
- 凯尔奇类ECH相关蛋白1 (Keap1) 负面调节了Nrf2.2.
- 抑制Nrf2-Keap1相互作用显示了癌症和炎症性疾病的治疗潜力.
研究的目的:
- 开发可靠的计算方法来设计选择性抑制蛋白质-蛋白质相互作用的循环.
- 预测针对Keap1.1.的Nrf2衍生的最佳宏循环化策略.
- 为了将计算预测与实验结合亲和关系和结构数据相关联.
主要方法:
- 利用全原子,明确溶剂分子动力学模拟与增强的采样.
- 模拟并比较了各种循环的溶液相组合.
- 在的宏循环化中使用 bis-thioether "" .
主要成果:
- 成功预测了循环的预组织的相对程度.
- 与实验测量的Keap1结合亲和关系相关的模拟预测.
- 验证的发现与结晶结构的循环结合Keap1.1.
结论:
- 介绍了一种新的计算方法,用于设计循环作为选择性蛋白质-蛋白质相互作用抑制剂.
- 证明模拟合体对预测结合亲和力和指导药物设计的实用性.
- 通过调节Nrf2-Keap1通路,为开发向疗法提供了关键的见解.
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