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

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; common feature pharmacophore modeling; diabetes mellitus; flavonoids; isosilybin; molecular docking; pharmacokinetics.; protein tyrosine phosphatase non-receptor type 1.

Fig. (1)

Ten pharmacophore hypothetical models (lower panel) were generated for eleven compounds using LigandScout 4.1. Six features are the best fit to generate the best pharmacophore model. The proposed pharmacophore model (model 1 shown in upper panel) used in this study contains three HBAs (red spheres), two ARs (purple spheres) and one HR (yellow spheres). (The color version of the figure is available in the electronic copy of the article).

Fig. (2)

Schematic workflow summarizing the screening of Protein tyrosine phosphatase non receptor type 1 inhibitors using computer aided drug design.

Fig. (3)

Hydrophobic surface and the active binding site of the 3EAX protein showing LZP ligands, that is co-crystallized and overlaid at the active site, as generated using chimera.

Fig. (4)

Schematic representation of the binding mode of ligands with Protein tyrosine phosphatase non receptor type 1 protein (PDB ID: 3EAX). The protein site is hydrophobic and the NMR structure of the 3EAX protein complex bonded with LZP is shown in (A). Conserved interacting residues of the binding site of the target protein bonded with the virtual hits (B). ZINC04259056 shows only hydrophobic bonding (C). ZINC30731533 shows large network of hydrophobic and hydrogen bonding (D). ZINC00968072 also shows large network of hydrophobic and hydrogen bonding. Conserved interacting residues are displayed in red circles. (The color version of the figure is available in the electronic copy of the article).