Abstract

QSAR RATIONALES FOR THE MMP-13 INHIBITION ACTIVITY OF NON-ZINC BINDING QUINAZOLINE-2-CARBOXAMIDE DERIVATIVES

Jahan Afsar, Sharma Brij Kishore,* and Yadav Rama Nand

Abstract

The MMP-13 inhibition activity of non-zinc binding quinazoline-2- carboxamide derivatives has been quantitatively analyzed in terms of chemometric descriptors. The statistically validated quantitative structure-activity relationship (QSAR) models provided rationales to explain the inhibition activity of these congeners. The descriptors identified through combinatorial protocol in multiple linear regression (CP-MLR) analysis have highlighted the role of positive and negative maximal electrotopological variations (MAXDP and MAXDN, respectively), path/walk 2- and 4-Randic shape index (PW2 and PW4, respectively), bond information content of neighborhood symmetry of 4-order (BIC4), Moran autocorrelations of lag-1 and -2/weighted by atomic van der Waals volumes (MATS1v and MATS2v, respectively) and of lag-8/ weighted by atomic Sanderson electronegativities (MATS8e). In addition to these 4th order Galvez topological charge index (GGI4), number of nitrogen atoms (nN), aromatic ethers functionality (nRORPh) and RC(= X)-X/ R-C#X/X=C=X type structural fragments (C-040) have also shown prevalence to model the inhibition actions. From statistically validated models, it appeared that the descriptors MAXDP, BIC4, PW4, GGI4, nRORPh, MATS8e, MATS1v and C-040 make positive contribution to activity and their higher values are conducive in improving the MMP-13 inhibition activity of a compound. On the other hand, the descriptors nN, MAXDN, PW2 and MATS2v render detrimental effect to activity. Therefore, lower values of descriptors nN, MAXDN, PW2 and MATS2v would be advantageous. Such guidelines may be helpful in exploring more potential analogues of the series. The statistics emerged from the test sets have validated the identified significant models. PLS analysis has further confirmed the dominance of the CP‐MLR identified descriptors. Applicability domain analysis revealed that the suggested models have acceptable predictability. All the compounds are within the applicability domain of the proposed models and were evaluated correctly.

Keywords: QSAR, MMP-13 inhibitors, Combinatorial protocol in multiple linear regression (CP-MLR) analysis, Chemometric descriptors, Quinazoline-2-carboxamide derivatives.