经pH和微水分校正的DFT洞察力对黄[7]uril主机-客体热力学:朝着药物纳入预测模型的方向
1Department of Chemistry, Al Al-Bayt University, Mafraq, 25113, Jordan. khaldoun@aabu.edu.jo.
Journal of molecular modeling
|December 9, 2025
概括
预测库库比特[7]uril (CB[7]) 的结合能量是具有挑战性的. 一个新的DFT工作流,包括水化和pH效应,提高了准确性,提供了对主机-客户互动的见解.
科学领域:
- 超分子化学 超分子化学
- 计算化学的计算化学
- 化学热力学化学热力学
背景情况:
- 黄瓜[7]uril (CB[7]) 主机-客户系统表现出强大的结合,但难以准确的热力学预测.
- 含有隐式溶解的标准DFT方法高估了结合的自由能量,这是由于被忽视的因素,如门水和质子平衡等.
研究的目的:
- 开发和验证一个新的DFT工作流程,以准确预测CB[7]主机-客串结合热力学.
- 为管理CB[7]复杂化的驱动力提供化学透明的见解.
主要方法:
- 开发了一个DFT工作流程,其中包含明确的水分子用于门口微水和边缘溶解.
- 用实验 pKa 值对客体质子状态进行了校正,并通过波尔茨曼加权应用了符合平均值.
- 使用RDG/NCI等表面分析非共价相互作用,以了解结合贡献.
主要成果:
- 修正后的DFT模型显著降低了CB[7]客人预测和实验结合的自由能量之间的差异.
- 工作流程成功考虑了微水分,pH效应和形状平均值.
- 分析显示,对于不同类型的客人来说,疏水和静电相互作用的贡献是不同的.
结论:
- 开发的水分和pH意识的DFT协议提供了一个更准确和机械透明的方法来预测CB[7]结合热力学.
- 这个框架可以扩展到更广泛的主机-客户系统和严格的测试.
- 这项研究为CB[7]复杂化中的静电力和疏水力分区提供了有价值的见解.
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