Computational identification of potential GLP-1 receptor agonists from marine natural products for nutraceutical applications in diabetes and obesity management
4 affiliations
- 1Department of Medicinal Chemistry, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
- 2Department of Medicinal Chemistry, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran; Drug Design and Development Research Center, The Institute of Pharmaceutical Sciences (TIPS), Tehran University of Medical Sciences, Tehran, Iran
- 3Alfonso X El Sabio University, Faculty of Biomedicine and ATG Medical Genetic Studies Center, Madrid, Spain
- 4Faculty of Medicine, IIS-FundaciónJiménez Díaz, The Autonomous University of Madrid, Madrid, Spain
Abstract
The Glucagon-Like Peptide-1 Receptor (GLP-1R) is a validated diabetes and obesity target, yet challenges with current peptide agonists necessitate orally bioavailable small-molecule alternatives. Marine natural products (MNPs) offer a structurally diverse reservoir for discovering such compounds for nutraceutical use. This study employed a multi-stage computational workflow to identify potential non-peptide GLP-1R agonists from the Comprehensive Marine Natural Products Database (CMNPD). The pipeline integrated virtual screening (Molecular Docking), MM/GBSA binding energy refinement, in silico ADMET profiling, and all-atom molecular dynamics (MD) simulations. An initial screen of 51,199 conformations yielded 50 unique hits across 13 chemical clusters. Docking analyses revealed that top candidates engage key active site residues, including a crucial π-π stacking interaction with Trp33 and a hydrophobic clamp formed by Trp203 and Leu217. Following dual-criterion energetic screening and multiparameter physicochemical and ADMET prioritization, three candidates were advanced to 500 ns MD simulations. The simulations confirmed stable binding for CMNPD17793 and CMNPD26068, whereas a third (CMNPD4578) dissociated, highlighting the criticality of dynamic validation. This work identifies two marine-derived scaffolds that remained dynamically accommodated within the predicted GLP-1R binding pocket. However, their predicted toxicity liabilities preclude any conclusion regarding nutraceutical suitability and indicate the need for rigorous experimental pharmacological and safety evaluation.
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BibTeX
@article{hajipour2026computational,
title = {{Computational identification of potential GLP-1 receptor agonists from marine natural products for nutraceutical applications in diabetes and obesity management}},
author = {Fatemeh Hajipour and Omid Tavakkol Hamedani and Alireza Foroumadi and Nieves Gonzalez Gomez and Oscar Lorenzo Gonzalez and Loghman Firoozpour},
journal = {Results in Chemistry},
year = {2026},
month = nov,
doi = {10.1016/j.rechem.2026.104042},
url = {https://doi.org/10.1016/j.rechem.2026.104042},
note = {CC BY},
}
RIS
TY - JOUR
TI - Computational identification of potential GLP-1 receptor agonists from marine natural products for nutraceutical applications in diabetes and obesity management
AU - Fatemeh Hajipour
AU - Omid Tavakkol Hamedani
AU - Alireza Foroumadi
AU - Nieves Gonzalez Gomez
AU - Oscar Lorenzo Gonzalez
AU - Loghman Firoozpour
PY - 2026
DA - 2026/11/07
JO - Results in Chemistry
DO - 10.1016/j.rechem.2026.104042
UR - https://doi.org/10.1016/j.rechem.2026.104042
AB - The Glucagon-Like Peptide-1 Receptor (GLP-1R) is a validated diabetes and obesity target, yet challenges with current peptide agonists necessitate orally bioavailable small-molecule alternatives. Marine natural products (MNPs) offer a structurally diverse reservoir for discovering such compounds for nutraceutical use. This study employed a multi-stage computational workflow to identify potential non-peptide GLP-1R agonists from the Comprehensive Marine Natural Products Database (CMNPD). The pipeline integrated virtual screening (Molecular Docking), MM/GBSA binding energy refinement, in silico ADMET profiling, and all-atom molecular dynamics (MD) simulations. An initial screen of 51,199 conformations yielded 50 unique hits across 13 chemical clusters. Docking analyses revealed that top candidates engage key active site residues, including a crucial π-π stacking interaction with Trp33 and a hydrophobic clamp formed by Trp203 and Leu217. Following dual-criterion energetic screening and multiparameter physicochemical and ADMET prioritization, three candidates were advanced to 500 ns MD simulations. The simulations confirmed stable binding for CMNPD17793 and CMNPD26068, whereas a third (CMNPD4578) dissociated, highlighting the criticality of dynamic validation. This work identifies two marine-derived scaffolds that remained dynamically accommodated within the predicted GLP-1R binding pocket. However, their predicted toxicity liabilities preclude any conclusion regarding nutraceutical suitability and indicate the need for rigorous experimental pharmacological and safety evaluation.
SN - 2211-7156
ER -