Development and evaluation of a QSPR model for the prediction of diamagnetic susceptibility

Abstract

A novel QSPR model is developed and evaluated for the prediction of diamagnetic susceptibility. The model was produced using the Multiple Linear Regression (MLR) technique on a database that consists of 406 organic compounds involving a diverse set of chemical structures. The accuracy of the QSPR model (R2=0.88) is illustrated using various evaluation techniques, such as leave-one-out procedure (Q2=0.87) and validation through an external test set (R2pred=0.89). The study leads to the conclusion that three physical - topological descriptors affect significantly the diamagnetic susceptibility: Polar Surface Area (PSAr), Principal Moment of Inertia X (PMIX), and Diameter (Diam). © 2008 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.