Prediction of aqueous solubility of organic salts of diclofenac using PLS and molecular modeling

Abstract

Organic salts of diclofenac were predicted by using computed molecular descriptors and multivariate partial least squares (PLS). The molecular descriptors including binding energy and surface area of salts were calculated by the use of Hyperchem and ChemPlus QSAR programs for Windows. Other physicochemical properties such as hydrogen acceptor for oxygen atoms, hydrogen acceptor for nitrogen atoms, hydrogen bond donors, hydrogen bond-forming ability, molecular weight, and log partition coefficient (log P) of bases were also used as descriptors. Good statistical models were derived that permit simple computational prediction of salt solubility of a same parent structure. The final models derived had R 2 value=0.96 and root mean square error for prediction (RMSEP) values ranging from 0.021 to 0.054 (log scale). Preferably all utilized descriptors in the final models can readily obtain from the chemical structure of salt and base. Molecular weight of base is one of the important factors associated with salt solubility. While increased molecular weight of base, surface area of salt and hydrogen bonding ability of base increase solubility, and increased binding energy and log P of base have negative effect on salt solubility.