Prediction of 3-hydroxypyridin-4-one (HPO) log K1 values for Fe(iii)Electronic supplementary information (ESI) available. See DOI: 10.1039/c2dt31254a

• Main Authors: Chen, Yu-Lin, Barlow, Dave J, Kong, Xiao-Le, Ma, Yong-Min, Hider, Robert C
• Format: Journal Article
• Language: English
• Published: 14.08.2012
• ISSN: 1477-9226; 1477-9234
• DOI: 10.1039/c2dt31254a

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 p K 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 p K a values. 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).