Identifying Biomolecular Targets of the Anticancer Vitamin-E-δ-Tocotrienol Using a Computational Approach: Virtual Target Screening

In recent years, evidence has mounted that a particular form of vitamin E (its δ-tocotrienol variant) may have cellular functions beyond that of an antioxidant, a role commonly ascribed to the tocotrienol class of compounds. In particular, numerous studies of δ-tocotrienol’s effect on cancer cells have identified it as a potent anticancer and antitumor agent. However, this important revelation of potential therapeutic use poses a series of new challenges, with arguably the most important being the elucidation of the precise mechanism of action responsible for the anticancer activity of δ-tocotrienol. As an initial step to address this question, we have used a computational tool, Virtual Target Screening (a molecular docking-based tool that identifies potential binding partners for small molecules), to identify potential biomolecular targets of δ-tocotrienol. Then, to gain a consensus as to the type of biomolecular entity that could be a target for δ-tocotrienol, we utilized PharmMapper and PASS (a ligand-based chemoinformatic approach), and ProBiS (a tool that analyses binding site similarities across known proteins). The results of our multipronged computational consensus-seeking approach showed that such a strategy can identify potential cellular targets of small molecules. This is evidenced by our identification of estrogen receptor-beta, a protein that has been previously shown to bind δ-tocotrienol, which elicited a cellular response. This study supports the use of such a computational approach as an initial step in target identification to avoid time-consuming, costly large-scale experimental screening, greatly reducing the experimental work to just one or a few candidate proteins.