Melanoma is an aggressive and currently incurable skin cancer, primarily affecting individuals with light skin pigmentation. Key oncogenic drivers include mutations in BRAF, NRAS, CDK4 and MITF, with signaling mediated mainly through the MAPK and PI3K–Akt pathways. MEK inhibitors have shown limited clinical success, emphasizing the need for novel therapeutic agents. In this study, structure-based virtual screening and molecular docking were employed to identify natural products that inhibit mutant NRAS. The crystal structure of wild-type NRAS was obtained from the Protein Data Bank and clinically relevant mutations (Gly12, Gly13, Gln61) were introduced computationally. A library of natural compounds from the ZINC database was screened, identifying candidates based on binding free energy. Eleven top-ranking compounds were further analyzed for binding interactions, revealing stabilizing hydrogen bonds and hydrophobic contacts, particularly involving residues Phe28 and Asp119. These compounds exhibited strong predicted affinity for the NRAS mutant binding site, representing promising scaffolds for further development. The results demonstrate the utility of computational approaches to accelerate early-stage drug discovery targeting oncogenic NRAS in melanoma.
Baladhye et al. (Sun,) studied this question.