Osiris Property Explorer 4.5.1 was used for defining and visualizing multivariate datasets of prospective drug candidates from WS and standard reference drugs through comparison of properties like TPSA, percent absorption, MW, hydrogen bond donor, hydrogen bond acceptor, number of rotatable bonds, Lipinski’s violations, leadlikeness and BAS. PCA helps in reducing the dimensionality of the dataset and increases interpretability. It does so by creating new uncorrelated variables which maximize the variance successively. Another added advantage of PCA is a 3D visualization in chemical space of how ‘drug-like’ are the molecules under study to known standard drugs in terms of their proximity to them in 3D chemical space.