Luteolin attenuates diabetic nephropathy via inhibition of metalloenzymes in rats

Abstract

Objective: To investigate the renoprotective effects of luteolin on diabetes in rats. Methods: One week after administration of streptozotocin 55 mg/kg intraperitoneally, rats were given 25, 50, and 75 mg/kg/day of luteolin orally for another eight weeks. At the end of the experiment, body weight, blood glucose level, biochemical parameters for renal function (serum creatinine, blood urea nitrogen, uric acid, serum albumin, and total protein), kidney histology, matrix metalloproteinase (MMP)-2, MMP-9, and histone deacetylase 2 (HDAC-2) expression, and malondialdehyde, myeloperoxidase, and hydroxyproline content in renal tissue were evaluated. High glucose-induced damage using NRK-52E cell line was studied to evaluate cell viability and metalloenzyme expression. Additionally, in silico studies including docking and molecular dynamics simulations were conducted. Results: MMP-2, MMP-9, and HDAC-2 expressions were significantly increased in high glucose-induced NRK-52E cells and the renal tissue of diabetic rats. However, these changes were reversed by luteolin at the administered doses. Additionally, luteolin significantly reduced oxidative stress, inflammation, and fibrosis, as well as improved biochemical parameters in diabetic rats. Furthermore, luteolin at the examined doses markedly alleviated diabetes-induced histopathological changes in renal tissues. Conclusions: Luteolin effectively attenuates streptozotocin-induced diabetic nephropathy in rats by inhibiting MMP-2, MMP-9, and HDAC-2 expression, and reducing oxidative stress and inflammation.

Keywords

MMPs / HDAC-2 / Luteolin / NRK-52E / Diabetic nephropathy / Docking / Molecular dynamic simulations

Acknowledgments

The authors concede the support by the G.E. S’s Sir Dr. M. S. Gosavi College of Pharmaceutical Education and Research Nashik; Institute of Pharmacy, Nirma University, Ahmedabad; and Government Polytechnic, Jalgaon. The Sigrid Jusélius Foundation, Biocenter Finland Bioinformatics and Drug Discovery and Chemical Biology networks, CSC IT Center for Science, Joe, Pentti and Tor Borg Memorial Fund, and Prof. Mark Johnson and Dr. Jukka Lehtonen are gratefully acknowledged for the excellent computational infrastructure at the Åbo Akademi University. We would also like to thank Dr. Outi M. H. Salo-Ahen for constructive feedback on the computational part.

Conflict of interest statement

The authors declare that they have no conflicts of interest.

Funding

The study was supported by the Joe, Pentti, and Tor Borg Memorial Fund.

Data availability statement

The data supporting the findings of this study are available from the corresponding authors upon request.

Authors’ contributions

RB performed the modeling, MD simulations, and data analysis, as well as wrote the computational portion of the work. RD carried out experiments, gathered and assessed the literature, and wrote the article. JS was in charge of supervising and revising the text. The final manuscript was reviewed and approved by all authors.

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