Development of quantitative structure-property relationships using calculated descriptors for the prediction of the physicochemical properties (n(D),p, bp, epsilon, eta) of a series of organic solvents

Quantitative structure-property relationship (QSPR) models were derived for predicting boiling point (at 760 mmHg), density (at 25 degrees C), viscosi ty (at 25 degrees C), static dielectric constant (at 25 degrees C), and ref ractive index (at 20 degrees C) of a series of pure organic solvents of str uctural formula X-CH2CH2-Y. A very large number of calculated molecular des criptors were derived by quantum chemical methods, molecular topology, and molecular geometry by using the CODESSA software package. A comparative ana lysis of the multiple linear regression techniques (heuristic and best mult ilinear regression) implemented in CODESSA, with the multivariate PLS/GOLPE method, has been carried out. The performance of the different regression models has been evaluated by the standard deviation of prediction errors, c alculated for the compounds of both the training set (internal validation) and the test set (external validation). Satisfactory QSPR models, from both predictive and interpretative point of views, have been obtained for all t he studied properties.