MARATTO

article · Biological Sciences

α-Amylase Inhibitory Potential of Antidiabetes Ligands in Spondias Mombin Plant Extract: Molecular Docking and ADMET Profiling

Abstract

Diabetes mellitus is majorly characterised by hyperglycemia, resulting from the disturbance of glucose homeostasis in the body due to excess calories of dietary sugar. α-amylase enzyme, involved in the digestion of carbohydrate, when inhibited causes a significant reduction in the post-prandial increase of blood glucose, which makes it an important strategy in the management of type 2 diabetes. Literatures have revealed series of compounds from Spondias mombin that exhibited antidiabetes activity. Therefore, this study sought to evaluate the antidiabetic potential of some Spondias mombin compounds using moleculardocking and ADMET profiling. Molecular docking analysis was carried out to study the binding interaction of some phytocompounds; Chlorogenic acid, Zeinoxanthin, Lutein, Isoquercetin, Quercetin, Rutin, Rhamnetin and Rutinose from Spondias mombin against α-amylase via Maestro 2017. Following the selection of the top five molecules, their bioavailability, drug-likeness, pharmacokinetic properties and toxicity were evaluated using the swissadme and protox iii webserver. Rhamnetin (-8.0 kcal/mol), quercetin (-7.8 kcal/mol), rutin (-7.9 kcal/mol), isoquercetin (-8.4 kcal/mol) and chlorogenic acid (-7.8 kcal/mol) gave higher docking score against α-amylase than the standard drug, acarbose (-7.2 kcal/mol). Quercetin and Rhamnetin also demonstrated high bioavailability, drug-likeness, pharmacokinetic properties and less toxicity. This study therefore uncovers potential α-amylase inhibitors in Spondias mombin with better binding affinities than acarbose and good ADMET properties, which may then serve as potential drug candidates for the management of diabetes. However, pharmacophore modelling is proposed in furtherance of this findings to identify possible variations of binding affinities with modification in their properties.

Research topics

  • Natural Antidiabetic Agents Studies
  • Computational Drug Discovery Methods
  • Pharmacology and Nanomedicine Research

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.55006/biolsciences.2025.5102

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.