TY - JOUR
AR - COR-2020-8-112
TI - Identifying Biomolecular Targets of the Anticancer Vitamin-E-δ-Tocotrienol Using a Computational Approach: Virtual Target Screening
AU - Yuri , Pevzner
AU - Elza , Pevzner
AU -  Kenyon , G. Daniel
AU - Wayne , C. Guida
AU - Wesley H., Brooks
AU - Mokenge , P. Malafa
JO - Clinical Oncology and Research
PY - 2020
DA - Wed 30, Dec 2020
SN - 2613-4942
DO - http://dx.doi.org/10.31487/j.COR.2020.08.12
UR - https://www.sciencerepository.org/identifying-biomolecular-targets-of-the-anticancer-vitamin-e-tocotrienol_COR-2020-8-112 
KW -  Natural products, docking, virtual target screening, structure-activity relation, vitamin E
AB - 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.