Molecular docking and dynamics simulation of farnesol as a potential anticancer agent targeting mTOR pathway.

Abstract

Farnesol is a natural acyclic sesquiterpene alcohol, found in various essential oils such as, lemon grass, citronella, tuberose, neroli, and musk. It has a molecular mass of 222.372 g/mol and chemical formula of C₁₅H₂₆O. The main objective of this study was to assess the effect of farnesol on mTOR and its two downstream effectors, p70S6K and eIF4E, which are implicated in the development of cancer, via molecular dynamic simulation, and docking analysis in an in silico study. A multilayer, primarily computer-based analysis was conducted to assess farnesol's anticancer potential, with a focus on primary cancer targets. From the calculations performed, farnesol showed a binding affinity of - 9.66 kcal/mol, followed by binding affinity of - 7.4 kcal/mol and - 7.8 kcal/mol for mTOR, p70S6K and eIF4E respectively. Rapamycin showed the binding affinity of - 10.45 kcal/mol for mTOR, for p70S6K and eIF4E the calculated binding affinity was - 10.65 kcal/mol and 8.16 kcal/mol respectively. The binding affinity of farnesol was comparable to the standard drug rapamycin indicating its potential as an mTOR inhibitor. Molecular dynamics simulations suggest that the ligands (farnesol and rapamycin) were well trapped within the active site of the protein over a time gap of 50 ns. It is clear that farnesol showed relatively stable MD simulation results, with minor fluctuations and maintains a consistent binding orientation, suggesting a strong and stable interaction with the target proteins when compared to simulation data of standard drug. This study explores the potential of farnesol as an anticancer agent through an in-silico approach, focusing on its interaction with mTOR and its downstream effectors. Inhibition of mTOR signaling pathway may be responsible for the anticancer effect of farnesol. As this pathway plays a crucial role in cell proliferation and survival, making it a significant target in cancer research.