In Silico Searching for Alternative Lead Compounds to Treat Type 2 Diabetes through a QSAR and Molecular Dynamics Study
Free fatty acid receptor 1 (FFA1) stimulates insulin secretion in pancreatic β-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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Pharmaceutics |
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| Online Access: | https://www.mdpi.com/1999-4923/14/2/232 |
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| author | Nicolás Cabrera Sebastián A. Cuesta José R. Mora Luis Calle Edgar A. Márquez Roland Kaunas José Luis Paz |
| author_facet | Nicolás Cabrera Sebastián A. Cuesta José R. Mora Luis Calle Edgar A. Márquez Roland Kaunas José Luis Paz |
| author_sort | Nicolás Cabrera |
| collection | DOAJ |
| description | Free fatty acid receptor 1 (FFA1) stimulates insulin secretion in pancreatic β-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 R<sup>2</sup> = 0.843, Q<sup>2</sup><sub>CV</sub> = 0.785, and Q<sup>2</sup><sub>ext</sub> = 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. |
| first_indexed | 2024-03-09T21:14:54Z |
| format | Article |
| id | doaj.art-53c3eceb901944b794139ee8b25851df |
| institution | Directory Open Access Journal |
| issn | 1999-4923 |
| language | English |
| last_indexed | 2024-03-09T21:14:54Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Pharmaceutics |
| spelling | doaj.art-53c3eceb901944b794139ee8b25851df2023-11-23T21:35:51ZengMDPI AGPharmaceutics1999-49232022-01-0114223210.3390/pharmaceutics14020232In Silico Searching for Alternative Lead Compounds to Treat Type 2 Diabetes through a QSAR and Molecular Dynamics StudyNicolás Cabrera0Sebastián A. Cuesta1José R. Mora2Luis Calle3Edgar A. Márquez4Roland Kaunas5José Luis Paz6Department of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USADepartment of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester M1 7DN, UKGrupo de Química Computacional y Teórica (QCT-USFQ), Departamento de Ingeniería Química, Universidad San Francisco de Quito, Diego de Robles y vía Interoceánica, Quito 170901, EcuadorFaculty of Pharmacy, University of Granada, 18011 Granada, SpainGrupo de Investigaciones en Química y Biología, Departamento de Química y Biología, Facultad de Ciencias Exactas, Universidad del Norte, Carrera 51B, Km 5, vía Puerto Colombia, Barranquilla 081007, ColombiaDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USADepartamento Académico de Química Inorgánica, Facultad de Química e Ingeniería Química, Universidad Nacional Mayor de San Marcos, Cercado de Lima 15081, PeruFree fatty acid receptor 1 (FFA1) stimulates insulin secretion in pancreatic β-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 R<sup>2</sup> = 0.843, Q<sup>2</sup><sub>CV</sub> = 0.785, and Q<sup>2</sup><sub>ext</sub> = 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.https://www.mdpi.com/1999-4923/14/2/232free fatty acid receptor 1type 2 diabetesmolecular dynamicsmolecular dockingagonits of FFA1 |
| spellingShingle | Nicolás Cabrera Sebastián A. Cuesta José R. Mora Luis Calle Edgar A. Márquez Roland Kaunas José Luis Paz In Silico Searching for Alternative Lead Compounds to Treat Type 2 Diabetes through a QSAR and Molecular Dynamics Study Pharmaceutics free fatty acid receptor 1 type 2 diabetes molecular dynamics molecular docking agonits of FFA1 |
| title | In Silico Searching for Alternative Lead Compounds to Treat Type 2 Diabetes through a QSAR and Molecular Dynamics Study |
| title_full | In Silico Searching for Alternative Lead Compounds to Treat Type 2 Diabetes through a QSAR and Molecular Dynamics Study |
| title_fullStr | In Silico Searching for Alternative Lead Compounds to Treat Type 2 Diabetes through a QSAR and Molecular Dynamics Study |
| title_full_unstemmed | In Silico Searching for Alternative Lead Compounds to Treat Type 2 Diabetes through a QSAR and Molecular Dynamics Study |
| title_short | In Silico Searching for Alternative Lead Compounds to Treat Type 2 Diabetes through a QSAR and Molecular Dynamics Study |
| title_sort | in silico searching for alternative lead compounds to treat type 2 diabetes through a qsar and molecular dynamics study |
| topic | free fatty acid receptor 1 type 2 diabetes molecular dynamics molecular docking agonits of FFA1 |
| url | https://www.mdpi.com/1999-4923/14/2/232 |
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