Plant derived anti-cancerous secondary metabolites as multipronged inhibitor of COX, Topo, and aromatase: molecular modeling and dynamics simulation analyses

Abstract

In the present study, 300 plant derived secondary metabolites (100 each of alkaloid, flavonoid, and terpenoid), have been screened for their anti-cancerous activity through inhibition of selected key enzymatic targets, namely cyclooxygenases (COXs), topoisomerases (Topos), and aromatase by molecular docking approach. Furthermore, the stability of the complexes of top hits, from each class of secondary metabolites, with their respective enzymatic targets was analyzed using molecular dynamics (MD) simulation analyses and binding free energy calculations. Analysis of the results of the docking in light of the pharmacokinetically screened 18 alkaloids, 26 flavonoids, and 9 terpenoids, revealed that the flavonoid, curcumin, was the most potent inhibitor for all the selected enzymatic targets. The stability of the complexes of COX-1, COX-2, Topo I, Topo IIβ and aromatase with the most potent inhibitor curcumin and those of the respective drugs, namely ibuprofen, aspirin, topotecan, etoposide, and exemestane were also analyzed through MD simulation analyses which revealed better stability of curcumin complexes than those of respective drugs. Binding energy calculations of the complexes of the curcumin with all the targets, except those of Topos, exhibited lower binding energies for the curcumin complexes than those of respective drugs which corroborated with the results of molecular docking analyses. Thus, the present study affirms the versatile and multipronged nature of curcumin, the traditionally used herbal medicine, as anti-cancer molecule directed against these enzymatic targets.

Keywords:

• aromatase
• cancer
• curcumin
• cyclooxygenase
• molecular docking and dynamics simulation
• secondary metabolites
• topoisomerase

Acknowledgment

Financial support from the Department of Science and Technology (DST), Government of India, New Delhi, in the form of DST-INSPIRE-SRF to S.S. is gratefully acknowledged. Financial support from the Department of Biotechnology, Government of India, New Delhi, under BIF; the Department of Science and Technology, Government of India, New Delhi, under DST PURSE; and the Department of Higher Education, Government of U.P. under Center of Excellence in Bioinformatics programs are also gratefully acknowledged.