Quantitative structure-property relationships for predicting metal binding by organic ligands.
Quantitative structure-property relationships (QSPRs) are developed to predict the complexation of Al(III), Ca(II), Cd(II), Cu(II), Ni(II), Pb(II), and Zn(II) by organic ligands containing carboxylate, phenol, amine, ether, and alcoholfunctional groups. These QSPRs predict conditional stability constants (K(M') at pH 7.0 and I = 0.1) over a range of ligand types with consistent uncertainties of approximately 1 log unit without requiring any steric or connectivity information. Calibration and validation data sets were constructed using 1:1 complex formation constants from the NIST Critical Stability Constants database (version 8.0). The descriptor variables are intuitive quantities conceptually related to metal binding, such as the numbers of various ligand groups, charge density, etc. The resulting calibrations have r2 = 0.87 to 0.93 and Spred = 0.67 to 1.05 log units, with positive values for all ligand count descriptor variables. The QSPRs account for 75-95% of the variability in the validation data set with RMSE of 0.74 to 1.30 log units. These QSPRs improve upon previous work by providing a tested and mechanistically reasonable method for log K(M') prediction with uncertainties comparable to or betterthan other QSPRs calibrated with groups of diverse ligands.
Cabaniss
Stephen E
SE
Department of Chemistry, University of New Mexico, Albuquerque, New Mexico 87131, USA. cabaniss@unm.edu