ABSTRACT
Matrix metalloproteinase-2 (MMP-2) is a lucrative therapeutic target as far as anticancer drug discovery is concerned. Overexpression of MMP-2 is found to facilitate tumour propagation through the involvement of vascular endothelial growth factor (VEGF). However, even after different techniques, finding a target-specific MMP-2 inhibitor with respectable pharmacodynamic properties is still a challenging task. Regression-dependent quantitative structure–activity relationship (QSAR) strategies might be among the possible drug design methods to explore the essential structural features that would be valuable to find a suitable MMP-2 inhibitor. In this paper, 72 molecules were explored using the PaDEL descriptors and stepwise multiple linear regression (S-MLR). The partial least squares (PLS) method was also used to create a viable statistical model with an acceptable metric related to these models. The final statistical models were formed with statistical parameters within acceptable range (r2 = 0.797, Q2 = 0.725 and r2pred = 0.643 for the MLR model, and r2 = 0.780, Q2 = 0.685 and r2pred = 0.666 for the PLS model). The models were analysed and compared with those already published on the same endpoint.
Acknowledgments
SAA sincerely acknowledges Jadavpur University, Kolkata for awarding Junior Research Fellowship under State Government Fellowship Scheme of Jadavpur University, Kolkata, India. TJ is grateful for the financial support from University with Potential for Excellence (UPE), Phase II Program of UGC, New Delhi to Jadavpur University, Kolkata, India. We heartily thank Sandip Kr Baidya, Suvankar Banerjee, Rajat Sarkar and Subha Mondal for their multi-modal inputs in creation of this manuscript. We thank the support from Jadavpur University, Kolkata, India for providing research facilities.
Disclosure statement
No potential conflict of interest was reported by the authors.