使用最先进的方法将RNA与小分子向,提供了对 рибо开关抑制剂的高度预测性亲缘关系
Narjes Ansari1, Chengwen Liu2,3, Florent Hédin2
1Qubit Pharmaceuticals, 75014, Paris, France. narjesa@qubit-pharmaceuticals.com.
Communications biology
|October 1, 2025
概括
通过小分子向RNA开发新药是有希望的. 我们的新计算方法准确地预测了结合 afinities,减少了药物发现失败率.
科学领域:
- 计算化学是一种计算化学.
- 药物发现 药物发现
- RNA生物学的RNA生物学
背景情况:
- 用小分子准RNA是一种有前途的药物设计策略.
- 对RNA系统和小分子结合缺乏准确的计算模型.
- 预测结合亲和关系对于RNA向药物发现至关重要.
研究的目的:
- 开发一种计算方法,用于对RNA结合小分子的绝对结合自由能量计算.
- 解决模拟RNA系统和预测结合亲缘关系方面的挑战.
- 为了使自由能量模拟在RNA向药物发现中的常规应用.
主要方法:
- 使用了AMOEBA极化力场.
- 实施了一种新的lambda-Adaptive偏差力方案,用于高效采样.
- 结合基于机器学习的集体变量与增强的采样模拟来克服RNA结构变化.
主要成果:
- 开发了用于RNA-小分子结合自由能量计算的最先进的计算协议.
- 实现了复杂的Riboswitch样RNA标的定量预测.
- 证明了该协议在RNA结构变化中捕获自由能量障碍的能力.
结论:
- 开发的计算协议能够准确地预测RNA-小分子结合的自由能量.
- 这种方法显著提高了RNA向药物发现的效率并降低了失败率.
- 在开发基于RNA的新型治疗中,为自由能量模拟的常规使用铺平了道路.
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