Discovery of non-peptide GLP-1r natural agonists for enhancing coronary safety in type 2 diabetes patients

Abstract

This study explores the computational discovery of non-peptide agonists targeting the Glucagon-Like Peptide-1 Receptor (GLP-1R) to enhance the safety of major coronary outcomes in individuals affected by Type 2 Diabetes. The objective is to identify novel compounds that can activate the GLP-1R pathway without the limitations associated with peptide agonists. Type 2 diabetes mellitus (T2DM) is associated with an increased risk of cardiovascular disease (CVD) and mortality, which is attributed to the accumulation of fat in organs, including the heart. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are frequently used to manage T2DM and could potentially offer cardiovascular benefits. Therefore, this study examines non-peptide agonists of GLP-1R to improve coronary safety in type 2 diabetes patients. After rigorous assessments, two standout candidates were identified, with natural compound 12 emerging as the most promising. This study represents a notable advancement in enhancing the management of coronary outcomes among individuals with type 2 diabetes. The computational methodology employed successfully pinpointed potential GLP-1R natural agonists, providing optimism for the development of safer and more effective therapeutic interventions. Although computational methodologies have provided crucial insights, realizing the full potential of these compounds requires extensive experimental investigations, crucial in advancing therapeutic strategies for this critical patient population.

Communicated by Ramaswamy H. Sarma

Keywords:

• Glucagon-like peptide-1 receptor (GLP-1R)
• non-peptide agonists
• type 2 diabetes
• coronary outcomes
• computational discovery
• zinc natural database

Disclosure statement

No potential conflict of interest was reported by the authors.

Authors contributions

N.SH. designed the project, wrote the main manuscript text, and prepared figures; S.H. performed molecular docking simulation experiments; F.R. and F.A. performed some of the experiments; H.S. and M. I. reviewed and edited the main manuscript and F.H. managed the project.

Data availability statement

The authors confirmed that the data supporting the study’s conclusions are included in the article and its supplementary materials. Upon a reasonable request, the corresponding author will provide the raw data used to support the findings of this study.

Additional information

Funding

Mashhad University of Medical Sciences provided financial support (grant number: 4020121) for this study.