QSPR Prediction of the Stability Constants of Gadolinium(III) Complexes for Magnetic Resonance Imaging

Gadolinium­(III) complexes constitute the largest class of compounds used as contrast agents for Magnetic Resonance Imaging (MRI). A quantitative structure–property relationship (QSPR) machine-learning based method is applied to predict the thermodynamic stability constants of these complexes (log K GdL), a property commonly associated with the toxicity of such organometallic pharmaceuticals. In this approach, the log K GdL value of each complex is predicted by a graph machine, a combination of parametrized functions that encodes the 2D structure of the ligand. The efficiency of the predictive model is estimated on an independent test set; in addition, the method is shown to be effective (i) for estimating the stability constants of uncharacterized, newly synthesized polyamino−polycarboxylic compounds and (ii) for providing independent log K GdL estimations for complexants for which conflicting or questionable experimental data were reported. The exhaustive database of log K GdL values for 158 complexants, reported for potential application as contrast agents for MRI and used in the present study, is available in the Supporting Information (122 primary literature sources).