p计算器:一个pK a预测器用于C-H债券
Rasmus M Borup1, Nicolai Ree1, Jan H Jensen1
1Department of Chemistry, University of Copenhagen, Copenhagen, DK-2100, Denmark.
Beilstein journal of organic chemistry
|July 30, 2024
概括
本研究介绍了pKalculator,这是一个量子化学工作流程,可以自动计算C-H酸度 (pKa). 由此产生的机器学习模型准确预测pKa值,并识别有机分子中的反应部位.
科学领域:
- 有机化学 有机化学
- 计算化学计算化学
- 机器学习 机器学习
背景情况:
- 预测C-H酸度 (pKa) 对于合成化学家来说至关重要,但随着分子复杂性的增加,变得具有挑战性.
- 准确的pKa值指导着在有机合成中预测活性位点.
研究的目的:
- 开发一个使用量子化学 (QM) 来计算C-H pKa值的自动化工作流程 (pKalculator).
- 为了生成一个强大的数据集来训练机器学习 (ML) 模型来预测C-H pKa.
- 评估模型在预测pKa和识别反应部位方面的表现.
主要方法:
- 一个基于QM的工作流,pCalculator,已开发用于自动化C-H pKa计算.
- 质量管理工作流程与DMSO中的695个实验C-H pKa值进行了验证.
- 在一个包含3910个C-H位的775个分子数据集上训练了一种ML模型.
主要成果:
- 对于C-H pKa预测,ML模型实现了1.24的平均绝对误差 (MAE) 和2.15 pKa单位的根平均平方误差 (RMSE).
- 该模型成功地确定了1043个pKa依赖反应 (阿尔多尔,克莱森,迈克尔) 的反应部位,其马修相关系数 (MCC) 为0.82.
结论:
- pCalculator提供了一种有效和准确的方法来确定C-H pKa值.
- 开发的ML模型显示了C-H酸度和反应部位识别的高预测能力.
- 这种方法促进了复杂有机分子中的合成规划和反应预测.
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