QSAR modelling and molecular docking studies for anti-cancer compounds against melanoma cell line SK-MEL-2

A dataset of seventy-two (72) cytotoxic compounds of the National Cancer Institute (NCI) was studied by QSAR and docking approaches to gain deeper insights into ligands selectivity on SK-MEL-2 cell line. The QSAR model was built using fifty (50) molecules and the best-generated model based on multiple linear regression showed, respectively good quality of fits ( $$ (0.864), $$ (0.845), Q² _cv (0.799) and $$ (0.706)). The model's predictive ability was determined by a test set of twenty-two (22) compounds. Compounds 30 and 41 were selected as templates for in silico design because they had high pGI₅₀ activity and are in the model's applicability domain. The obtained information from the model was explored to design novel molecules by introducing various modifications. Moreover, the designed compounds with better-predicted activity (pGI₅₀) values were selected and docked on the active site of the protein (PDB-CODE: 3OG7) which is responsible for melanoma cancer to elucidate their binding mode. AN2 (-12.1kcalmol^-1) and AC4 (-12.4kcalmol^-1) showed a better binding score for the target when compared with (vemurafenib, -11.3kcalmol^-1) the known inhibitor of the target (V600E-BRAF). These findings may be very helpful in early anti-cancer drug development.