In silico evaluation of selected triterpenes as potential inhibitors of BRAF and BRAFV600E kinases for cancer treatment.

contextBRAF kinases are involved in cancer cell survival and metastasis. Mutations in BRAF are frequent in several types of cancer, occurring in more than 50% of melanomas, 50-70% of thyroid cancers, 15% of colorectal cancers, and 5-8% of non-small-cell lung cancers. The most prevalent mutation is V600E. Vemurafenib and dabrafenib are two selective BRAF inhibitors approved by the FDA for clinical use. However, due to the increasing resistance to current kinase inhibitors, there is an urgent need to identify new molecular scaffolds with potential BRAF inhibitory activity. In this work, molecular docking, molecular dynamics, and metadynamics simulations were performed on twelve triterpenes to identify the best ligands with potential binding to BRAFWT and BRAFV600E. The interaction profiles of the selected triterpenes revealed key contacts with residues ILE463, THR529, GLN530, TRP531, CYS532, and PHE583, which contribute to stabilizing the conformation of both inhibitors and triterpenes within the catalytic binding site of the proteins. The ΔG of betulinic acid (-57.46 kcal/mol) in complex with BRAFWT is comparable to the BRAF inhibitors vemurafenib-OMe and dabrafenib reported in previous work, the ΔG of β-amyrin (-51.83 kcal/mol) showed a ΔG comparable to the inhibitors with BRAFV600E; moreover, the ΔG of lupeol (-62.43 kcal/mol) and moronic acid (-61.05 kcal/mol) are more favorable with BRAFV600E than vemurafenib-OMe and dabrafenib. These computational calculations allow us to consider these triterpenes as potential candidates for drug design cycles and to optimize the binding profile for the development of new selective inhibitors for BRAFV600E to cancer treatments.

methodsMolecular docking calculations using AutoGrid 4.2.6, AutoDockGPU 1.5.3, and AutoDockTools 1.5.6 were performed. Molecular dynamics and metadynamics simulations were performed in the Desmond module of the academic version of the Schrödinger-Maestro 2021-4 program, utilizing the OPLS-2005 force field. Finally, all the protein figures presented in this article were made in the PyMOL program and the RMSD graphics were made in the statistical package R and RStudio 2025.05.1.