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预测柔性多碱四氮杂大环化合物的p值。

Predicting p of flexible polybasic tetra-aza macrocycles.

作者信息

Harvey Tatum K, Pota Kristof, Mekhail Magy M, Freire David M, Agbaglo Donatus A, Janesko Benjamin G, Green Kayla N

机构信息

Department of Chemistry & Biochemistry, Texas Christian University 2800 S. University Dr. Fort Worth TX 76129 USA

Department of Chemistry, University of California Irvine USA

出版信息

RSC Adv. 2025 Apr 7;15(14):10663-10670. doi: 10.1039/d5ra01015b. eCollection 2025 Apr 4.

Abstract

We present physics-based p predictions for a library of tetra-aza macrocycles. These flexible, polybasic molecules exhibit highly charged states and substantial prototropic tautomerism, presenting a challenge for p prediction. Our computational protocol combines CREST/xTB conformational sampling, density functional theory (DFT) refinement in continuum solvent, and a linear empirical correction (LEC). This approach predicts known tetra-aza macrocycle p to within a root-mean-square deviation 1.2 log units. This approach also provides reasonable predictions for the most stable protomers at different pH. We use this protocol to predict p values for four novel, synthetically achievable, previously un-synthesized tetra-aza macrocycles, providing new leads for future experiments.

摘要

我们展示了基于物理的四氮杂大环化合物库的pKₐ预测。这些灵活的多碱分子呈现出高电荷状态和显著的质子互变异构现象,这给pKₐ预测带来了挑战。我们的计算方案结合了CREST/xTB构象采样、连续介质溶剂中的密度泛函理论(DFT)优化以及线性经验校正(LEC)。该方法预测已知四氮杂大环化合物的pKₐ,其均方根偏差在1.2个对数单位以内。此方法还能对不同pH下最稳定的质子异构体提供合理预测。我们使用该方案预测了四种新型、可合成获得但此前未合成的四氮杂大环化合物的pKₐ值,为未来的实验提供了新线索。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2d92/11973477/b2ff87e96de6/d5ra01015b-f1.jpg

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