Quantitative Structure Activity Relationship Study of MF-63 (Phenanthrene Imidazole Series) Derivatives for mPGES-1 Inhibitory Activity

Inhibition of COX-2 signaling has been one of the strategies to reduce occurrence and aggressiveness of many cancer types. Due to several side effects associated with the direct targeting of COX-2, inhibition of various other key players in COX-2 signaling like mPGES-1 is suggested. MF-63 is known to inhibit mPGES-1; a crucial component of COX-2 signaling. In this study, a quantitative structure activity relationship (QSAR) was performed on eighteen bioactive MF-63 (phenanthrene imidazole) derivatives. Initially 3224 molecular descriptors were obtained using DRAGON software and finally a model was developed using five of them. For variable selection, Genetic Algorithm (GA) method was used. The model was build using Partial Least Square Regression (PLSR). The most significant model generated was having correlation coefficient (r2) of 0. 9421 cross validated correlation coefficient (q2) of 0. 7888, F-test value of 81.33, r2 for external test set (pred_ r2) 0.6011, coefficient of correlation of predicted data set and (pred_r2se) 0.9706. Descriptors found suitable to construct the model included radial distribution function (RDF110u), GETAWAY descriptor (R3u), Moran Autocorrelation descriptor (MATS5v) and MoRSE descriptors (Mor28v and Mor31p). As these descriptors majorly belong to electronic and structural properties, our proposed model indicated that these properties significantly contribute towards the potency of MF-63 derivatives. The current study will aid in the future designing and development of more potent mPGES-1 inhibitors as anti-cancer agents.