ABSTRACT
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 KGdL), a property commonly associated with the toxicity of such organometallic pharmaceuticals. In this approach, the log KGdL 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 KGdL estimations for complexants for which conflicting or questionable experimental data were reported. The exhaustive database of log KGdL 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).
Subject(s)
Chelating Agents/chemical synthesis , Contrast Media/chemical synthesis , Coordination Complexes/chemical synthesis , Gadolinium/chemistry , Animals , Artificial Intelligence , Carboxylic Acids/chemistry , Databases, Chemical , Humans , Kinetics , Ligands , Magnetic Resonance Imaging/methods , Polyamines/chemistry , Quantitative Structure-Activity Relationship , ThermodynamicsABSTRACT
Two calixarene-based model systems (a and b) for monocopper enzymes are compared. Both present a tris(pyridine) coordination site for Cu that mimics the imidazole-rich neutral binding site in enzymes. Upon reaction with 1 equiv of copper(I), the tridentate ligands gave rise to ill-defined unsymmetrical complexes. However, in the presence of an organonitrile RCN (R = Me, Et, Ph), tetrahedral species were obtained, with the nitrilo ligand included in the calixarene hydrophobic cone. System b presents a larger cavity than system a, with a wider opening thanks to the removal of three tBu groups from the calixarene structure. As a result, the recognition pattern for MeCN vs PhCN is inverted, and the relative affinity constants differ by 3 orders of magnitude. The mechanism of the acetonitrile exchange at the cuprous centers was studied by (1)H NMR spectroscopy. Thermodynamic and kinetic data show that it follows a dissociative pathway in both cases. The main differences between systems a and b stem from the presence of a door that entraps the guest in case a. In system b indeed, the removal of three calixarene tBu groups led to a 100-fold acceleration of the MeCN exchange rate. Hence, these supramolecular systems provide a rare and interesting model for the hydrophobic substrate channel giving access to a metalloenzyme active site.
Subject(s)
Copper/chemistry , Enzymes/chemistry , Macromolecular Substances , Metalloproteins/chemistry , Calixarenes , Copper/metabolism , Enzymes/metabolism , Kinetics , Ligands , Metalloproteins/metabolism , Molecular Mimicry , Nuclear Magnetic Resonance, Biomolecular , Protein Folding , ThermodynamicsABSTRACT
A cavity that acts as a molecular funnel is formed from calix[6]arene 1 and [CuI (NCCH3 )4 ]PF6 [Eq. (a)]. An exchange of the well-protected acetonitrile ligand for other nitriles RCN is only possible with small R groups. The protection of the copper ions precludes oxidative dimerization; thus, the complexes mimic the mononuclear site of copper enzymes.