利用杆绑定构成元动力学来优化对三个不同的配体的目标捕捞预测及其真正的目标
Mei Qian Yau1,2, Angeline J Wan1, Aaron S H Tiong1
1School of Pharmacy, Faculty of Health & Medical Sciences, Taylor's University, Subang Jaya, Selangor, Malaysia.
绑定姿势元动力学通过重新排名初始预测来改善计算目标捕鱼. 这种先进的模拟方法提高了药物发现中的目标识别效率,完善了连接物-目标关联.
科学领域:
- 计算化学是一种计算化学.
- 药物发现 药物发现
- 生物信息学是一种生物信息学.
背景情况:
- 计算目标捕鱼辅助药物发现中的目标识别.
- 目前用于预测联结体-标相互作用的方法可能会产生不一致的排名.
研究的目的:
- 评估绑定姿势元力学是否可以从初始预测中改善目标排名.
- 评估元动力学对改进药物发现预测的影响.
主要方法:
- 应用药测绘用于初始目标预测.
- 利用结合姿势元动力学来重新排列潜在的联结物-目标相互作用.
- 评估了三种配体和六种已知的目标的排名改进.
主要成果:
- 最初的预测没有在前50名中排名任何真正的目标.
- 绑定姿势元力学改善了六个真实目标中的四个目标的排名.
- 修订后的预测包括两个目标在前50名,其他目标在前250名.
结论:
- 绑定姿势元动力学可以改进基于结构的目标捕捞的预测.
- 这种方法提高了药物发现中目标识别的效率.
- 超动力学为提高计算药物发现工作的准确性提供了一个有价值的工具.
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