LEAD IDENTIFICATION AND OPTIMIZATION OF PLANT INSULIN-BASED ANTIDIABETES DRUGS THROUGH MOLECULAR DOCKING ANALYSES
Keywords:
Diabetes mellitus, Plant insulin, Lead identification and optimization, Computer-aided drug designAbstract
Objective: Diabetes mellitus (DM) is a multifactorial disorder of the pancreas and the third leading cause of deaths in humans. Presence of plant proteins whose genomic sequences are similar to those of animal insulin has been demonstrated. We wished to discover anti-DM drugs having high inhibitory activity based on plant proteins.
Methods: Â Computer-aided molecular docking methods were applied using Auto Dock Vina software.
Results: Â We selected a plant protein with Uni Prot identification Q7M217 insulin in Canavalia ensiformis as the target protein for DM. We identified an active lead compound among eight candidate compounds on the basis of significant binding interactions with the target protein and half-maximal inhibitory concentration (IC50) values. We designed four analogs of the lead compound. Molecular docking analyses showed that the four analogs could be used as anti-DM agents with suitable drug-like properties as compared with a standard compound for the treatment of DM (aleglitazar). These analogs can also be used for future studies.
Conclusion: We identified an anti-DM compound, a biphenyl derivative, based on plant insulin. We designed its analogs using a functional-group inter-conversion approach. Our computer-aided study provided information on binding energies and binding interactions of the analogs to predict their anti-DM activity.
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