Characterization of Multi-targeted Insulin-mimetic Antidiabetic Peptides Using in Silico Approaches
Anas Bilal, Ghulam Mustafa.
Abstract
Diabetes is a metabolic disease that can affect people at any age. Despite being one of the leading causes of death, the treatment of diabetes is extremely difficult. For the treatment of diabetes mellitus various synthetic oral hypoglycemic drugs and insulin is available. However, insulin cannot be taken orally and the synthetic agents used can have harmful side effects. Bioactive peptides are particular protein fragments that have a beneficial impact on human health and physiological processes. These peptides can be applied as antidiabetic agents in the treatment of diabetes.
Introduction
Diabetes mellitus (DM) is recognized as a prevalent multifactorial disease that is approaching epidemic proportions. It has been affecting every age group without any discrimination. Despite being one of the leading causes of death, treatment of diabetes is extremely difficult. Diabetes is characterized by signs including glucose intolerance, prolonged hyperglycemia and disruption in regulatory systems that store and utilize metabolic energy such as carbohydrate, lipid, and protein catabolism and anabolism in a diabetic individual due to impaired insulin receptor functioning or lack of insulin production.
Methods:
Based on the literature information, the protein sequences of plant hypoglycemic proteins including insulin mimetic protein (also known as Cq-IMP) (UniProt accession number: C0HLQ3), AdMc1 protein (UniProt accession number: A0A0M5WZ27), polypeptide-P (UniProt accession number: ADO14327), prolamin binding factor (UniProt accession number: OP763567), MC6 (UniProt accession number: AAX06814), charantin (UniProt accession number: P84072.1), trypsin inhibitor BGIT (UniProt accession number: 1VBW_A), and MC2-1-5 protein were selected and downloaded from the UniProt database.
Discussion
The selected hypoglycemic proteins including Cq-IMP, AdMc1, polypeptide-P, prolamin binding factor, MC6, charantin, trypsin inhibitor BGIT, and MC2-1-5 were digested using Peptide Cutter Server to generate peptides using trypsin and pepsin enzymes.
Citation: Bilal A, Mustafa G (2025) Characterization of multi-targeted insulin-mimetic antidiabetic peptides using in silico approaches. PLoS One 20(8): e0330341. https://doi.org/10.1371/journal.pone.0330341
Editor: Rajesh Kumar Singh, Institute of Medical Sciences, Banaras Hindu University, INDIA
Received: February 21, 2025; Accepted: July 30, 2025; Published: August 19, 2025.
Copyright: © 2025 Bilal, Mustafa. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
