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Medicinal Chemistry Research

, Volume 25, Issue 6, pp 1049–1056 | Cite as

In silico structural prediction of human steroid 5α-reductase type II

  • Wiranpat Karnsomwan
  • Thanyada Rungrotmongkol
  • Wanchai De-Eknamkul
  • Supakarn Chamni
Original Research

Abstract

Steroid 5α-reductase type II is a membrane-associated enzyme in an oxidoreductase family. This enzyme, which is found in male sexual organs, plays the important biological actions toward steroid metabolism. Overexpression of 5α-reductase type II has affected the balance between testosterone and dihydrotestosterone, which implicates the androgenic disorders, including prostate cancer, hirsutism, and androgenic alopecia. Lack of single-crystal X-ray structures of 5α-reductase has hindered mechanistic understanding and delayed the discovery and development of an effective inhibitor. Herein, we illustrated a comparative structure of 5α-reductase type II that derived from the homology modeling, employing a membrane-bound protein, isoprenylcysteine carboxyl methyltransferase as a homologous template. A catalytic pocket and the transmembrane site were identified. The resulting in silico structure was validated via Ramachandran plot and confirmed by docking studies of 30 known 5α-reductase type I and type II inhibitors, including finasteride and dutasteride. The comparative docking study of the derived in silico 5α-reductase type II and 5β-reductase, a reported surrogate enzyme, was conducted. Our homology model approximately fitted to the membrane-associated character and showed the reasonable docking results, which depicted the well-defined comparative three-dimensional structure applicable for steroid reductase drug design.

Keywords

5α-Reductase 5β-Reductase Homology modeling Androgenic disorders 

Notes

Acknowledgments

Graduate student working in this project was funded by Chulalongkorn University and ICS-UNIDO collaborative research project. This research was supported by the New Researcher Grants of National Science and Technology Development Agency sponsored by Ministry of Science & Technology for Dr. Supakarn Chamni (SCH-NR2014-098), the Thailand Research Fund (IRG5780008), and the PERDO’s Center of Excellence on Medical Biotechnology (CEMB) program. Our gratitude goes to the Structural and Computational Biology Research Group and the Ph.D. Program in Bioinformatics and Computational Biology, Department of Biochemistry, Faculty of Science, Chulalongkorn University, for computational facilities and resources.

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Pharmacognosy and Pharmaceutical Botany, Faculty of Pharmaceutical SciencesChulalongkorn UniversityBangkokThailand
  2. 2.Structural and Computational Biology Research Group, Department of Biochemistry, Faculty of ScienceChulalongkorn UniversityBangkokThailand

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