In Silico Searching for Alternative Lead Compounds to Treat Type 2 Diabetes through a QSAR and Molecular Dynamics Study. Academic Article uri icon


  • Free fatty acid receptor 1 (FFA1) stimulates insulin secretion in pancreatic -cells. An advantage of therapies that target FFA1 is their reduced risk of hypoglycemia relative to common type 2 diabetes treatments. In this work, quantitative structure-activity relationship (QSAR) approach was used to construct models to identify possible FFA1 agonists by applying four different machine-learning algorithms. The best model (M2) meets the Tropsha's test requirements and has the statistics parameters R2 = 0.843, Q2CV = 0.785, and Q2ext = 0.855. Also, coverage of 100% of the test set based on the applicability domain analysis was obtained. Furthermore, a deep analysis based on the ADME predictions, molecular docking, and molecular dynamics simulations was performed. The lipophilicity and the residue interactions were used as relevant criteria for selecting a candidate from the screening of the DiaNat and DrugBank databases. Finally, the FDA-approved drugs bilastine, bromfenac, and fenofibric acid are suggested as potential and lead FFA1 agonists.

published proceedings

  • Pharmaceutics

altmetric score

  • 1.25

author list (cited authors)

  • Cabrera, N., Cuesta, S. A., Mora, J. R., Calle, L., Mrquez, E. A., Kaunas, R., & Paz, J. L.

citation count

  • 5

complete list of authors

  • Cabrera, Nicolás||Cuesta, Sebastián A||Mora, José R||Calle, Luis||Márquez, Edgar A||Kaunas, Roland||Paz, José Luis

publication date

  • January 2022