Binding of anticancer compound glycopentalone with cell cycle macromolecules

Journal Article
Kim, A.B. Gurung, M.A. Ali, A. Bhattacharjee, K.M. Al-Anazi, M.A.Farah, F.M. Al-Hemaid, F.M. Abou-Tarboush, J. Lee and S.Y. . 2016
Publication Work Type: 
KSU Research Work
Glycosmis pentaphylla, Glycopentalone; Molecular docking; Reverse pharmacophore mapping, Anticancer;
Magazine \ Newspaper: 
Genetics and Molecular Research
Volume Number: 
In Press
Accepted Manuscript
Publication Abstract: 

The bioactive compound, Glycopentalone isolated from Glycosmis pentaphylla (Retz) (family Rutaceae) have recently reported to have cytotoxic and apoptosis inducing effects in various human cancer cell lines. However, their mode of action have not clearly been defined; therefore, target fishing of glycopentalone using combined inverse docking and reverse pharmacophore mapping approach was attempted to identify potential targets of glycopentalone, and gain insights of its binding modes against the selected molecular targets viz; CDK-2, CDK-6, Topoisomerase I, Bcl-2, VEGFR-2, Telomere:G-Quadruplex and Topoisomerase II. These targets were chosen based on their key role in progression of cancer via regulation of cell cycle and DNA replication. Molecular docking analysis revealed that glycopentalone displayed binding energies ranging from -6.38 kcal/mol to -8.35 kcal/mol to -6.38 kcal/mol and inhibition constants ranging from 20.90µM to 0.758µM. Further, the binding affinities of glycopentalone with the targets were in order Telomere:G-quadruplex> VEGFR-2> CDK-6> CDK-2> Topoisomerase II> Topoisomerase I> Bcl-2 and its binding mode analysis revealed critical hydrogen bonds as well as hydrophobic interactions with the targets. The targets were validated by reverse pharmacophore mapping of glycopentalone against a set of 2241 known human target proteins which revealed CDK-2 and VEGFR-2 as its most favorable targets. The glycopentalone was well mapped to CDK-2 and VEGFR-2 which involve a total of six pharmacophore features (two hydrophobic centres and four hydrogen bond acceptors) and nine pharmacophore features (five hydrophobic, two hydrogen bond acceptors and two hydrogen bond donors) respectively. The present computational approaches may aid in rational identification of targets for small molecules against a large set of candidate macromolecules before experimental validation by bioassays, which will save both time and economy.