Institute of Pharmaceutical Science, King's College London, Franklin-Wilkins Building, 150 Stamford Street, London, SE1 9NH, UK.
Dalton Trans. 2012 Sep 21;41(35):10784-91. doi: 10.1039/c2dt31254a. Epub 2012 Aug 1.
As a means to aid in the design of 3-hydroxypyridin-4-ones (HPOs) intended for use as therapeutic Fe(3+) chelating agents, a novel methodology has been developed using quantum mechanical (QM) calculations for predicting the iron binding affinities of the compounds (more specifically, their log K(1) values). The reported/measured HPO log K(1) values were verified through their correlation with the corresponding sum of the compounds' ligating group pK(a) values. Using a training set of eleven HPOs with known log K(1) values, reliable predictions are shown to be obtained with QM calculations using the B3LYP/6-31+G(d)/CPCM model chemistry (with Bondi radii, and water as solvent). With this methodology, the observed log K(1) values for the training set compounds are closely matched by the predicted values, with the correlation between the observed and predicted values giving r(2) = 0.9. Predictions subsequently made by this method for a test set of 42 HPOs of known log K(1) values gave predicted values accurate to within ±0.32 log units. In order to further investigate the predictive power of the method, four novel HPOs were synthesised and their log K(1) values were determined experimentally. Comparison of these predicted log K(1) values against the measured values gave absolute deviations of 0.22 (13.87 vs. 14.09), 0.02 (14.31 vs. 14.29), 0.12 (14.62 vs. 14.50), and 0.13 (15.04 vs. 15.17). The prediction methodology reported here is the first to be provided for predicting the absolute log K(1) values of iron-chelating agents in the absence of pK(a) values.
作为一种辅助设计 3-羟基吡啶-4-酮(HPOs)的方法,用于作为治疗性 Fe(3+)螯合剂,开发了一种新的方法,使用量子力学(QM)计算来预测化合物的铁结合亲和力(更具体地说,它们的 log K(1) 值)。报道/测量的 HPO log K(1) 值通过与其配体基团 pK(a) 值的总和的相关性进行验证。使用具有已知 log K(1) 值的十一组 HPO 的训练集,使用 B3LYP/6-31+G(d)/CPCM 模型化学(带 Bondi 半径,以水为溶剂)的 QM 计算可以获得可靠的预测。使用该方法,观察到训练集化合物的 log K(1) 值与预测值非常匹配,观察值与预测值之间的相关性给出 r(2) = 0.9。随后,通过该方法对具有已知 log K(1) 值的 42 组 HPO 的测试集进行预测,预测值准确到±0.32 log 单位。为了进一步研究该方法的预测能力,合成了四个新型 HPO,并通过实验确定了它们的 log K(1) 值。将这些预测的 log K(1) 值与测量值进行比较,得到的绝对偏差为 0.22(13.87 对 14.09),0.02(14.31 对 14.29),0.12(14.62 对 14.50)和 0.13(15.04 对 15.17)。报告的预测方法是第一个在没有 pK(a) 值的情况下预测铁螯合剂绝对 log K(1) 值的方法。