Computational Identification of GPR119-Targeted Small Molecules as Potential Therapies for Diabetes Mellitus
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Alison Wang
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Type 2 diabetes mellitus (T2DM) is a global epidemic, accounting for over 90% of diabetes mellitus cases worldwide, in part due to inadequate treatment options. GPR119 is a protein receptor that stimulates insulin excretion and has the potential to revolutionise current T2DM care. In this study, we used computational methods to search for promising GPR119 agonists. Firstly, a test for binding sites in GPR119 was done using geometric, energetic-based, and machine-learning methods. Secondly, a pharmacophore map was generated and used to scan for potential small molecule agonists. Next, a molecular docking method was used to test the energetic favourability of selected molecules. The top compounds of this test then underwent virtual screening to determine their ADME profiles, and were then tested for toxicity. This study identified Z1275113833 to be the most promising candidate based on the above tests, warranting further exploration into its capabilities as a new GPR119-based treatment for T2DM. In addition, more computational tests to search for more potential agonists could be done.
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Alison Wang
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