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An Integrated Computational Approach for Plant-Based Protein Tyrosine Phosphatase Non-Receptor Type 1 Inhibitors

[ Vol. 13 , Issue. 4 ]

Author(s):

Shabana Bibi and Katsumi Sakata*   Pages 319 - 335 ( 17 )

Abstract:


Background: Protein tyrosine phosphatase non-receptor type 1 is a therapeutic target for the type 2 diabetes mellitus. According to the International Diabetes Federation 2015 report, one out of 11 adults suffers from diabetes mellitus globally.

Objective: Current anti-diabetic drugs can cause life-threatening side-effects. The present study proposes a pipeline for the development of effective and plant-derived anti-diabetic drugs that may be safer and better tolerated.

Methods: Plant-derived protein tyrosine phosphatase non-receptor type 1 inhibitors possessing antidiabetic activity less than 10µM were used as a training set. A common feature pharmacophore model was generated. Pharmacophore-based screening of plant-derived compounds of the ZINC database was conducted using ZINCpharmer. Screened hits were assessed to evaluate their drug-likeness, pharmacokinetics, detailed binding behavior, and aggregator possibility based on their physiochemical properties and chemical similarity with reported aggregators.

Results: Through virtual screening and in silico pharmacology protocol isosilybin (ZINC30731533) was identified as a lead compound with optimal properties. This compound can be recommended for laboratory tests and further analyses to confirm its activity as protein tyrosine phosphatase nonreceptor type 1 inhibitor.

Conclusion: The present study has identified plant-derived anti-diabetic virtual lead compound with the potential to inhibit protein tyrosine phosphatase non-receptor type 1, which may be helpful to enhance insulin production. This computer-aided study could facilitate the development of novel pharmacological inhibitors for diabetes treatment.

Keywords:

Computer-aided drug design, diabetes mellitus, flavonoids, isosilybin, protein tyrosine phosphatase non-receptor type 1, common feature pharmacophore modeling, molecular docking, pharmacokinetics.

Affiliation:

Department of Environment and Life Engineering, Graduate School of Engineering, Maebashi Institute of Technology, Maebashi, Department of Environment and Life Engineering, Graduate School of Engineering, Maebashi Institute of Technology, Maebashi, Gunma 371-0816

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