Exploration of alpha-glucosidase inhibitors: A comprehensive in silico approach targeting a large set of triazole derivatives

TL;DR

This study uses computer modeling to find new alpha-glucosidase inhibitors that could help treat diabetes more effectively.

Contribution

A large-scale in silico screening of triazole derivatives to identify novel alpha-glucosidase inhibitors with favorable pharmacokinetic properties.

Findings

Nine compounds were identified as potential alpha-glucosidase inhibitors with stable ligand-target interactions.

Three compounds showed stability in 100 ns molecular dynamics simulations and favorable ADMET profiles.

The findings suggest these compounds are promising candidates for further experimental validation.

Abstract

The increasing prevalence of diabetes and the side effects associated with current medications necessitate the development of novel candidate drugs targeting alpha-glucosidase as a potential treatment option.

This study employed computer-aided drug design techniques to identify potential alpha-glucosidase inhibitors from the PubChem database. Molecular docking was used to evaluate 81,197 compounds, narrowing the set for further analysis and providing insights into ligand-target interactions. An ADMET study assessed the pharmacokinetic properties of these compounds, including absorption, distribution, metabolism, excretion, and toxicity. Molecular dynamics simulations validated the docking results.

9 compounds were identified as potential candidate drugs based on their ability to form stable complexes with alpha-glucosidase and their favorable pharmacokinetic profiles, three of these compounds were subjected to the molecular dynamics, which showed stability throughout the entire 100 ns simulation.

These findings suggest promising new alpha-glucosidase inhibitors for diabetes treatment. Further validation through in vitro and in vivo studies is recommended to confirm their efficacy and safety.

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