Correlation-based feature selection was employed to initially select important descriptors from a large set of descriptors obtained from the calculation. The pair-correlation of each descriptor value and bioactivity (pIC50) was calculated using a Pearson's correlation coefficient (r) of 0.6 as a cut-off value. Descriptors with |r| < 0.6 were considered weakly correlated descriptors and were excluded from the study, whereas those with |r| ≥ 0.6 were selected for further selection process using stepwise multiple linear regression (MLR) as implemented in SPSS statistics 18.0 (SPSS Inc., USA). Finally, a set of important descriptors was obtained for multivariate analysis.