2D QSAR approach to develop newer generation molecules active aganist ERBB2 receptor kinase as potential Anticancer Agent

Abstract

Quantative Structure Activity Relationship analysis was performed using 159 molecules active against ERBB2 kinase inhibitory activity, where IC50 was converted into pIC50. The statistically suitable QSAR model was PIC50 = -0.27351(+/-1.85955) -0.02792(+/-0.08389) ALogP -2.14626(+/-1.14052) SpMin3_Bhv -1.32984(+/-0.13918) ntN +0.21209(+/-0.02129) ETA_Beta_ns (SEE :0.63346, r^2 :0.56219, r^2 adjusted :0.54627, F :35.31334 (DF :4, 110) which suggest that electron-richness of the molecule (ETA_Beta_ns) will create positive response and Ghose-Crippen LogKow value (ALogP), Smallest absolute eigenvalue of Burden modified matrix - n 3 / weighted by relative van der Waals volumes (SpMin3_Bhv) and number of atom type E state (ntN) cause negative response in biological activity. Then the model was validated by Golbraikh and Tropsha acceptable criteria as Q^2: 0.51805 Passed (Threshold value Q^2>0.5),r^2 :0.60327 Passed(Threshold value r^2>0.6), |r0^2-r'0^2|:0.18983 Passed (Threshold value |r0^2-r'0^2| 0.3. The External Validation Parameters(Without Scaling): r^2 :0.60327 and external Validation parameters (After Scaling): rm^2 :0.5955. The model was cross validated using Leave-One-Out (LOO) process with Q2:0.51805, PRESS: 48.59098, SDEP :0.65002.So the QSAR model was suitable for future development.