Abstract

BackgroundMelanoma cancer causes serious health problem worldwide because of its rapid invasion to other organs and lack of satisfactory chemotherapy. The pGI50 anticancer activity values of 70 compounds from the NCI (National Cancer Institute) on MALME-3M cell line was modeled to describe the quantitative structure-activity relationships (QSARs) of the compounds, and some selected compounds were docked.ResultsThe generated QSAR model was found to be statistically significant based on the obtained values of the validation keys such as R2 (0.885), {R}_{mathrm{adjusted}}^2 (0.868), Q2cv (0.842), and {R}_{pred}^2 (0.738) required to evaluate the strength and robustness of QSAR model. Compound 39 was selected as a template due to its good pGI50 (9.205) and was modified to design new potent compounds. The predicted pGI50 activity of the designed compounds by the built model was N1 (9.836), N2 (12.876), N3 (10.901), and N4 (11.263) respectively. These proposed compounds were docked with V600E-BRAF receptor and the result shows that, N1, N2, N3, and N4 with free binding energy (FBE) of − 11.7 kcal mol−1, − 12.8 kcal mol−1, − 12.7 kcal mol−1, and − 12.9 kcal mol−1 respectively were better than the parent structure of the template (compound 39, FBE = − 7.0 kcal mol−1) and the standard V600E-BRAF inhibitor (Vemurafenib, FBE = − 11.3 kcal mol−1). Additionally, these compounds passed the drug-likeness criteria successfully to be orally bioavailable.ConclusionThe proposed compounds were considered optimal as their performances are comparable to vemurafenib and possessed enhanced physicochemical properties. Thus recommends further research such as synthesis, in vivo, and ex-vivo evaluation.

Highlights

  • Melanoma cancer causes serious health problem worldwide because of its rapid invasion to other organs and lack of satisfactory chemotherapy

  • In this research, the genetic function algorithm (GFA)-Multiple linear regression (MLR) modeling tool was used in the construction of a Quantitative evaluation of the structure-activity relationship (QSAR) model and the in-silico screening method was applied to the developed QSAR model which enable the design and prediction of activity of new potentially active compounds on MALME-3M cell line

  • Compound 39 was selected as a template among the data set due to its good pGI50 (9.205) and was utilized to design new potent compounds, thereby enhancing the activity of the parent structure

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Summary

Introduction

Melanoma cancer causes serious health problem worldwide because of its rapid invasion to other organs and lack of satisfactory chemotherapy. Melanoma is one of the most aggressive forms of skin tumor and a serious health issue worldwide because of its increasing incidence and the lack of satisfactory chemotherapy for the advanced stages of the disease [1, 2]. It has a high ability of metastasis and rapid invasion of other organs, e.g., lymph node, lung, liver, brain, etc. QSAR is an important factor in the drug design; it is quite evident why many users of QSAR are found mostly in the research units of industries [15,16,17]

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