Molecular Modeling Studies of RNA Polymerase II Inhibitors as Potential Anticancer Agents
Ankita Agarwal, Sarvesh Paliwal, Ruchi Mishra · 2013
Global physicochemical descriptor based QSAR models were developed using multiple linear regression (MLR) and partial least squares (PLS) for a set of 44 molecules as Derivatives of Oncrasin-1synthesized against cancer. Leave out one row method is used to validate the developed model. The MLR and PLS generated excellent models with good predictive ability and all the statistical values, such as r, r 2 , r 2 cv, r 2 ( test set), F and S values were 0.88, 0.78, 0.77, 0.77, 30.75 and 0.40 for MLR and r 2 cv, r 2 (test set) and statistical significance value were 0.77, 0.77 and 0.92 for PLS respectively, were satisfactory. The results obtained from this study provides insights regarding role of Bond dipole moment (subst. 2), Balaban topological index (whole molecule), First Atom E- state index (subst. 1) and VAMP heat of formation (Whole molecule) in determining the RNA polymerase II inhibitory activity. The results clearly reveal that the anti-cancer activity.