In silico Studies of some potential anti-cancer agents on M19-MEL cell line

The resistance of melanoma cancer cells to the known treatments has become a barrier to the success of chemotherapy.  In this research, a quantitative evaluation of the structure-activity relationship (QSAR) was carried out on 57 anti-cancer compounds and some selected potent compounds were screened through Lipinski’s rule and docked. Genetic function algorithm (GFA) was adopted in variables selection and Multiple linear regression (MLR) was used to generate the model. The built QSAR model showed good statistical parameters (( (0.904), (0.885), Q 2 cv (0.873) and (0.779)). The cR⁠ 2 ⁠ P for Y-randomization is 0.749 and the applicability domain was also determined. The predictive ability of the model was found to be satisfactory and could be used to predict the anti-cancer activity of compounds on M19 MEL cell line. 4 most potent compounds were selected among the data set and screened through Lipinski's rule of five filters for oral bioavailability, ADMET risk filter for a drug like features. Later, V600E-BRAF, a known melanoma cancer target was used for docking. Based on the interaction energy and types of interactions involved, the selected compounds were identified as the best hits against V600E-BRAF. This research would help in the lead identification and design of novel drugs.