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In recent years, evidence has mounted that a particular form of vitamin E (its δ-tocotrienol variant) mayhave cellular functions beyond that of an antioxidant, a role commonly ascribed to the tocotrienol class ofcompounds. In particular, numerous studies of δ-tocotrienol’s effect on cancer cells have identified it as apotent anticancer and antitumor agent. However, this important revelation of potential therapeutic use posesa series of new challenges, with arguably the most important being the elucidation of the precise mechanismof 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 identifiespotential 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, weutilized PharmMapper and PASS (a ligand-based chemoinformatic approach), and ProBiS (a tool thatanalyses binding site similarities across known proteins). The results of our multipronged computationalconsensus-seeking approach showed that such a strategy can identify potential cellular targets of smallmolecules. This is evidenced by our identification of estrogen receptor-beta, a protein that has beenpreviously shown to bind δ-tocotrienol, which elicited a cellular response. This study supports the use ofsuch a computational approach as an initial step in target identification to avoid time-consuming, costlylarge-scale experimental screening, greatly reducing the experimental work to just one or a few candidateproteins.

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