Molecular modeling strategy to design novel anticancer agents against UACC-62 and UACC-257 melanoma cell lines

Abstract

ABSTRACT The resistance of melanoma cancer cells to the known treatments becomes a barrier to the progress of chemotherapy which obliges the discovery of novel and potent drugs. In this work, Quantitative Structure-Activity Relationships (QSAR), Molecular docking, and pharmacokinetics evaluation were applied to design novel molecules from a series of 69 anticancer molecules retrieved from the National cancer institute (NCI) database with activity against UACC-62 and UACC-257 melanoma cell lines. The best QSAR model for UACC-62 cell line showed good statistical parameters [(R^2 (0.819), R_adj^2 (0.794), Q2cv (0.772) and R_pred^2 (0.771)], while for UACC-257 cell line [(R^2 (0.844), R_adj^2 (0.821), Q2cv (0.789) and R_pred^2 (0.712)]. The Y-randomization test further strengthens the statistical prominence of the developed models. Docking investigation was further applied to predict the inhibition of V600E-BRAF by some potent molecules among the dataset using Molegro Virtual Docker (MVD). The docking result demonstrates that Dermocybin (DMB) and Bisantrene (BSN) HCl best inhibit V600E-BRAF when compared with other molecules within the dataset. These molecules were used in designing novel molecules by attaching some favorable substituents, out of which DMB1 and BSN2 were considered optimal among other molecules that outperformed Vemurafenib (approved V600E-BRAF-inhibitor) with an acceptable drug-likeness parameter and enhanced pharmacological properties.