位置预测准确性的比较评估在RNA-基体对接中
Rupesh Agarwal1,2, Rajitha Rajeshwar T1,2, Jeremy C Smith1,2
1UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6309, United States.
Journal of chemical information and modeling
|November 16, 2023
概括
这项研究评估了RNA-小分子对接的准确性,用于药物发现. 目前的方法表现出有限的成功,突出需要改进的RNA对接协议来识别新的治疗方法.
科学领域:
- 计算化学计算化学
- 药物发现 药物发现 药物发现
- 结构生物学 结构生物学
背景情况:
- 基于结构的虚拟查对于早期药物发现至关重要.
- RNA已经成为小分子药物的重要目标类别.
- 现有的对接程序主要是针对蛋白质目标进行验证,而不是RNA.
研究的目的:
- 评估RNA-小分子复合体的三个领先的对接协议的姿势预测准确度.
- 为了比较AutoDock4,AutoDock Vina和rDock在RNA目标上的性能.
主要方法:
- 评估了三个对接程序:AutoDock4 (AD4),AutoDock Vina (Vina) 和rDock. 这三种对接程序都进行了评估.
- 在173个RNA小分子晶体结构上测试了协议.
- 在具有和没有已知的联结结构的场景中分析了性能.
主要成果:
- 自动Dock4表现出不佳的性能.
- 在有针对性的查 (已知的联体结合结构) 中,rDock (48%) 和Vina (63%) 显示中等成功.
- 在一般查 (结构不明) 中,rDock和Vina的成功率都很低 (约27%).
- 维纳对某些连接体的物理化学性质有偏见,而rDock在所有性质上表现一致.
结论:
- 与蛋白质相比,当前最先进的对接方法对RNA点的准确性有限.
- 当没有先前的带-标结构可用时,Vina和rDock都适用.
- 需要进一步完善对接协议,以加强针对RNA的药物发现工作.
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