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A Quantitative Structure-Activity Relationship Study on a Series of Selective Non-zinc Binding Inhibitors of MMP13

[ Vol. 10 , Issue. 2 ]


Prithvi Singh   Pages 174 - 188 ( 15 )


Two novel series of potent and selective matrix metalloproteinase (MMP) inhibitors, involving unique binding mode at the active site and not interacting with the catalytic zinc, were collectively investigated to quantify their inhibition actions in relation with chemometric descriptors. Significant correlations, between their MMP13 inhibition activity and 2D-descriptors, were obtained through the combinatorial protocol in multiple linear regression (CP-MLR) computational procedure. The derived bi-variant models, validated internally and externally, were able to account for 86.5% of variance in the observed MMP13 inhibition activities. The filtered descriptors, from CP-MLR, satisfactorily explained the biological phenomenon under investigation. However the descriptors, MPC10, N-075 and C-030 accounting, respectively, for molecular path (bond) count of order 10, the structural fragments CH--N--CH and N--CH--N of aromatic ring remained prime to address the MMP13 inhibition actions of the compounds. From the highest significant correlations, it appeared that the higher value of MPC10 and absence of these aromatic ring fragments, are conducive in further improvement of MMP13 inhibition activity of a compound. The partial least squares (PLS) analysis has further confirmed the dominance of the identified descriptors. In the analysis, two-components remained optimum for these descriptors which are able to explain 89.3% of variances. Applicability domain (AD) analysis revealed that the suggested models have acceptable predictability. All the compounds remained within the AD of the proposed models and were evaluated correctly. Based on the inferences drawn from the study, some new analogues were suggested for further exploration. Their predicted MMP13 inhibition activities were much higher than the highest active congener of the original series.


Non-zinc binding inhibitors of MMP13, Combinatorial protocol in multiple linear regression (CP-MLR) analysis, Chemometric 2D-descriptors, QSAR study.


Department of Chemistry, S.K. Government College, Sikar 332 001, India.

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