Aromatase inhibitors identified from Saraca asoca to treat infertility in women with polycystic ovary syndrome via in silico and in vivo studies

Abstract

Polycystic ovary syndrome (PCOS) is a widely occurring metabolic disorder causing infertility in 70%–80% of the affected women. Saraca asoca, an ancient medicinal herb, has been shown to have therapeutic effects against infertility and hormonal imbalance in women. This study was aimed to identify new aromatase inhibitors from S. asoca as an alternative to the commercially available ones via in silico and in vivo approaches. For this, 10 previously reported flavonoids from S. asoca were chosen and the pharmacodynamic and pharmacokinetic properties were predicted using tools like Autodock Vina, GROMACS, Gaussian and ADMETLab. Of the 10, procyanidin B2 and luteolin showed better interaction with higher binding energy when docked against aromatase (3S79) as compared to the commercial inhibitor letrozole. These two compounds showed higher stability in molecular dynamic simulations performed for 100 ns. Molecular mechanics Poisson–Boltzmann surface analysis indicated that these compounds have binding free energy similar to the commercial inhibitor, highlighting their great affinity for aromatase. Density functional theory analysis revealed that both compounds have a good energy gap, and ADMET prediction exhibited the drug-likeness of the two compounds. A dose-dependent administration of these two compounds on zebrafish revealed that both the compounds, at a lower concentration of 50 µg/ml, significantly reduced the aromatase concentration in the ovarian tissues as compared to the untreated control. Collectively, the in silico and in vivo findings recommend that procyanidin B2 and luteolin could be used as potential aromatase inhibitors for overcoming infertility in PCOS patients with estrogen dominance.

Communicated by Ramaswamy H. Sarma

Keywords:

• Aromatase
• polycystic ovary syndrome
• Saraca asoca
• procyanidin B2
• luteolin
• molecular docking
• molecular dynamic simulation
• density functional theory
• ADME/T properties
• zebrafish

Acknowledgements

All the authors thank the High-Performance Computing Centre, SRM Institute of Science and Technology, for providing the computational facility. The authors are grateful to Dr. Thirumurthy Madhavan, Associate Professor, Department of Genetic Engineering, SRMIST, an expert in Bioinformatics, for his valuable suggestions in revising the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Ethics approval

This study was approved by SRM Institute Ethical Committee (Clearance number: SAF/IAEC/280622/027) and has strictly followed the ethical principles of the SRM Institute of Science and Technology.

Additional information

Funding

The authors reported there is no funding associated with the work featured in this article.