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ORIGINAL ARTICLE
Year : 2022  |  Volume : 17  |  Issue : 5  |  Page : 540-557

Discovery of novel inhibitors of ghrelin O-acyltransferase enzyme: an in-silico approach


1 Department of Medicinal Chemistry, Faculty of Pharmacy, Tehran University of Medical Sciences; Tehran, I.R. Iran
2 Medicinal Plants and Drugs Research Institute, Shahid Beheshti University, Tehran, I.R. Iran
3 Department of Medicinal Chemistry, Faculty of Pharmacy, Tehran University of Medical Sciences; Experimental Medicine Research Center, Tehran University of Medical Sciences; Tehran, I.R. Iran

Correspondence Address:
Massoud Amanlou
Department of Medicinal Chemistry, Faculty of Pharmacy, Tehran University of Medical Sciences;Tehran, I.R. Iran
I.R. Iran
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/1735-5362.355212

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Background and purpose: Ghrelin is known as a hunger hormone and plays a pivotal role in appetite, food intake, energy balance, glucose metabolism, and insulin secretion, making it a potential target for the treatment of obesity and type 2 diabetes. The essential maturation step of ghrelin to activate the GHS-R1a is the octanoylation of the Ser3, which is catalyzed by the ghrelin O-acyltransferase enzyme (GOAT) enzyme. Therefore, the inhibition of GOAT may be useful for treating ghrelin-related diseases. Experimental approach: To discover the novel inhibitors against GOAT enzyme by a fast and accurate computational method, here, we tried to develop the homology model of GOAT. Subsequently, the generated model was stabilized by molecular dynamics simulation. The consecutive process of docking, pharmacophore mapping, and large-scale virtual screening were performed to find the potential hit compounds. Findings / Results: The homology model of the GOAT enzyme was generated and the quality of 3D structures was increased to the highest level of > 99.8% of residue in allowed regions. The model was inserted into the lipid bilayer and was stabilized by molecular dynamics simulation in 200 ns. The sequential process of pharmacophore-based virtual screening led to the introduction of three compounds including ethaverine, kaempferitrin, and reglitazar as optimal candidates for GOAT inhibition. Conclusion and implications: The results of this study may provide a starting point for further investigation for drug design in the case of GOAT inhibitors and help pave the way for clinical targeting of obesity and type 2 diabetes.


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