Lipoxygenase directed anti-inflammatory and anti-cancerous secondary metabolites: ADMET-based screening, molecular docking and dynamics simulation

Abstract

Lipoxygenases (LOXs), key enzymes involved in the biosynthesis of leukotrienes, are well known to participate in the inflammatory and immune responses. With the recent reports of involvement of 5-LOX (one of the isozymes of LOX in human) in cancer, there is a need to find out selective inhibitors of 5-LOX for their therapeutic application. In the present study, plant-derived 300 anti-inflammatory and anti-cancerous secondary metabolites (100 each of alkaloids, flavonoids and terpenoids) have been screened for their pharmacokinetic properties and subsequently docked for identification of potent inhibitors of 5-LOX. Pharmacokinetic analyses revealed that only 18 alkaloids, 26 flavonoids, and 9 terpenoids were found to fulfill all the absorption, distribution, metabolism, excretion, and toxicity descriptors as well as those of Lipinski’s Rule of Five. Docking analyses of pharmacokinetically screened metabolites and their comparison with a known inhibitor (drug), namely zileuton revealed that only three alkaloids, six flavonoids and three terpenoids were found to dock successfully with 5-LOX with the flavonoid, velutin being the most potent inhibitor among all. The results of the docking analyses were further validated by performing molecular dynamics simulation and binding energy calculations for the complexes of 5-LOX with velutin, galangin, chrysin (in order of LibDock scores), and zileuton. The data revealed stabilization of all the complexes within 15 ns of simulation with velutin complex exhibiting least root-mean-square deviation value (.285 ± .007 nm) as well as least binding energy (ΔG_bind = −203.169 kJ/mol) as compared to others during the stabilization phase of simulation.

Keywords:

• ADMET
• binding free energy
• cancer
• lipoxygenase
• molecular docking and dynamics simulation

Acknowledgments

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