Abstract
Benign prostatic hyperplasia (BPH) is caused by augmented levels of androgen dihydrotestosterone (DHT) which is involved in the growth of the prostate in humans. 5α-Reductase type II (5αR2) is an intracellular enzyme that catalyses the formation of DHT from testosterone; hence, the inhibition of 5αR2 has emerged as one of the most promising strategies for the treatment of BPH. In this study, a computational approach that integrates ligand-based pharmacophore modelling, virtual screening, molecular docking and molecular dynamics (MD) simulations was adopted to discover novel 5αR2 inhibitors with less side effects. After validating by Fischer's randomisation and Güner-Henry test, the best quantitative pharmacophore model (Hypo1), consisting of two hydrogen-bond acceptors and three hydrophobic features, was subsequently used as a three-dimensional-query in virtual screening to identify potential hits from Maybridge and National Cancer Institute databases. These hits were further filtered by ADMET (absorption, distribution, metabolism, elimination and toxicology) and molecular docking experiments, and their binding stabilities were validated by 10-ns MD simulations. Finally, only one hit was identified as a potential lead based on higher predicted inhibitory activity to 5αR2 compared with the most active inhibitor (finasteride). Our results further suggest that this potential lead could easily be synthesised and has structural novelty, making it a promising candidate for treating BPH.
Original language | English |
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Pages (from-to) | 287-297 |
Number of pages | 11 |
Journal | Molecular Simulation |
Volume | 41 |
Issue number | 4 |
DOIs | |
Publication status | Published - Mar 4 2015 |
Keywords
- 5a-reductase type II
- benign prostatic hyperplasia
- molecular docking
- molecular dynamics simulations
- pharmacophore
- virtual screening
ASJC Scopus subject areas
- General Chemistry
- Condensed Matter Physics
- General Chemical Engineering
- Information Systems
- General Materials Science
- Modelling and Simulation