基于量子化学的模拟,以循环德克斯和多糖为基础的基拉尔静止阶段进行对电离分离
Linda Nelles-Ziegler1, Christoph Plett1, Stefan Grimme1
1Mulliken Center for Theoretical Chemistry, Clausius Institute for Physical and Theoretical Chemistry, University of Bonn, Beringstr. 4, 53115, Bonn, Germany.
Chemistry (Weinheim an der Bergstrasse, Germany)
|June 3, 2025
概括
现代量子化学方法在高性能液态染色学 (HPLC) 中准确预测enantioseparation. 这种计算方法成功地确定了性静止相 (CSP) 的实验化顺序 (EEO),有助于药物开发.
科学领域:
- 计算化学的计算化学
- 分析化学 分析化学
- 染色体学 染色体学 是一种染色学.
背景情况:
- 在性静止相 (CSP) 上模拟 enantioseparation 对于在高性能液态染色学 (HPLC) 中分析性化合物至关重要.
- 使用计算方法准确预测实验性化序列 (EEO) 仍然是一个挑战.
研究的目的:
- 评估先进的量子化学方法,特别是密度函数理论 (DFT) 在模拟CSP上的enantioseparation方面的能力.
- 为了将计算的化顺序与常见的CSP上的各种药物类型分子的实验数据进行比较.
主要方法:
- 在自动化计算工作流程中使用最先进的DFT方法.
- 采用分子对接,符合性采样和DFT精细化用于基于集体的协会自由能量计算.
- 在两个常见的CSP上研究了十种药物类型分子,考虑了不同的分子模型.
主要成果:
- 实现了对所有测试的基于环氧的CSP系统的EEO的正确确定.
- 在90%的案例中成功预测了EEO,用于更灵活的基于多糖的CSP.
- 观测到的小差异的结合自由能量 (几个kcal/mol) 之间的enantiomers.
结论:
- 现代的DFT方法与自动化工作流相结合,可以准确地模拟HPLC中CSP上的enantioseparation.
- 计算方法提供了可靠的EEO预测,即使在等离子体之间的能量差异很小.
- 需要进一步的研究来提高大规模选应用的计算效率.
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