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

Author(s): Shabana Bibi, Katsumi Sakata*.

Journal Name: Current Computer-Aided Drug Design

Volume 13 , Issue 4 , 2017

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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.

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Article Details

VOLUME: 13
ISSUE: 4
Year: 2017
Page: [319 - 335]
Pages: 17
DOI: 10.2174/1573409913666170406145607

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