In silico modeling of α-glucosidase, aldose reductase, and PPAR-γ with benzoyl/sulfonyl hydrazone derivatives using molecular docking, ADMET, and molecular dynamics simulations
Yıl: 2023 Cilt: 27 Sayı: 4 Sayfa Aralığı: 1567 - 1576 Metin Dili: İngilizce DOI: 10.29228/jrp.442 İndeks Tarihi: 28-07-2023
In silico modeling of α-glucosidase, aldose reductase, and PPAR-γ with benzoyl/sulfonyl hydrazone derivatives using molecular docking, ADMET, and molecular dynamics simulations
Öz: Type 2 diabetes mellitus (T2DM) is the most common type of diabetes and has become a serious public health problem in over the world. There are various antidiabetic drugs on the market, but most of these drugs cause many side effects such as diarrhea, kidney failure, musculoskeletal pain, and enlarged urinary system infections in the clinical treatment of T2DM. Therefore, there is a need for new antidiabetic drugs that can be used orally, are safe with improved efficacy, and reduced side effects. Today, drugs targeting alpha-glucosidase (α-glucosidase), peroxisome proliferator activating receptor gamma (PPAR-γ), and aldose reductase have an important role in the treatment of T2DM. This study is aimed to develop new antidiabetic agents with molecular modeling methods that are more effective, and specific and have fewer side effects than existing drug molecules for α-glucosidase, PPAR-γ, and aldose reductase. Herein, enzyme-ligand interaction mechanisms between target enzymes and 45 hydrazone compounds were examined by using molecular docking and molecular dynamics simulation methods. In addition, the ADME properties of these compounds and their pharmacokinetic suitability according to Lipinski and Veber’s rules were evaluated. Compound 2 has shown the best binding affinity against α-glucosidase, compound 27 for aldose reductase, and compound 4 for PPAR-γ and these compounds exhibited good ADME properties. Also, the best active hydrazone compounds have been observed to interact with key amino acid residues on target enzymes via hydrogen bonds. This information can guide the development of new antidiabetic agents by making important contributions to experimental studies.
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| APA | YILMAZ G, AKTAR B, ORUÇ EMRE E (2023). In silico modeling of α-glucosidase, aldose reductase, and PPAR-γ with benzoyl/sulfonyl hydrazone derivatives using molecular docking, ADMET, and molecular dynamics simulations. , 1567 - 1576. 10.29228/jrp.442 |
| Chicago | YILMAZ Gizem TATAR,AKTAR Bedriye Seda KURŞUN,ORUÇ EMRE Emine Elçin In silico modeling of α-glucosidase, aldose reductase, and PPAR-γ with benzoyl/sulfonyl hydrazone derivatives using molecular docking, ADMET, and molecular dynamics simulations. (2023): 1567 - 1576. 10.29228/jrp.442 |
| MLA | YILMAZ Gizem TATAR,AKTAR Bedriye Seda KURŞUN,ORUÇ EMRE Emine Elçin In silico modeling of α-glucosidase, aldose reductase, and PPAR-γ with benzoyl/sulfonyl hydrazone derivatives using molecular docking, ADMET, and molecular dynamics simulations. , 2023, ss.1567 - 1576. 10.29228/jrp.442 |
| AMA | YILMAZ G,AKTAR B,ORUÇ EMRE E In silico modeling of α-glucosidase, aldose reductase, and PPAR-γ with benzoyl/sulfonyl hydrazone derivatives using molecular docking, ADMET, and molecular dynamics simulations. . 2023; 1567 - 1576. 10.29228/jrp.442 |
| Vancouver | YILMAZ G,AKTAR B,ORUÇ EMRE E In silico modeling of α-glucosidase, aldose reductase, and PPAR-γ with benzoyl/sulfonyl hydrazone derivatives using molecular docking, ADMET, and molecular dynamics simulations. . 2023; 1567 - 1576. 10.29228/jrp.442 |
| IEEE | YILMAZ G,AKTAR B,ORUÇ EMRE E "In silico modeling of α-glucosidase, aldose reductase, and PPAR-γ with benzoyl/sulfonyl hydrazone derivatives using molecular docking, ADMET, and molecular dynamics simulations." , ss.1567 - 1576, 2023. 10.29228/jrp.442 |
| ISNAD | YILMAZ, Gizem TATAR vd. "In silico modeling of α-glucosidase, aldose reductase, and PPAR-γ with benzoyl/sulfonyl hydrazone derivatives using molecular docking, ADMET, and molecular dynamics simulations". (2023), 1567-1576. https://doi.org/10.29228/jrp.442 |
| APA | YILMAZ G, AKTAR B, ORUÇ EMRE E (2023). In silico modeling of α-glucosidase, aldose reductase, and PPAR-γ with benzoyl/sulfonyl hydrazone derivatives using molecular docking, ADMET, and molecular dynamics simulations. Journal of research in pharmacy (online), 27(4), 1567 - 1576. 10.29228/jrp.442 |
| Chicago | YILMAZ Gizem TATAR,AKTAR Bedriye Seda KURŞUN,ORUÇ EMRE Emine Elçin In silico modeling of α-glucosidase, aldose reductase, and PPAR-γ with benzoyl/sulfonyl hydrazone derivatives using molecular docking, ADMET, and molecular dynamics simulations. Journal of research in pharmacy (online) 27, no.4 (2023): 1567 - 1576. 10.29228/jrp.442 |
| MLA | YILMAZ Gizem TATAR,AKTAR Bedriye Seda KURŞUN,ORUÇ EMRE Emine Elçin In silico modeling of α-glucosidase, aldose reductase, and PPAR-γ with benzoyl/sulfonyl hydrazone derivatives using molecular docking, ADMET, and molecular dynamics simulations. Journal of research in pharmacy (online), vol.27, no.4, 2023, ss.1567 - 1576. 10.29228/jrp.442 |
| AMA | YILMAZ G,AKTAR B,ORUÇ EMRE E In silico modeling of α-glucosidase, aldose reductase, and PPAR-γ with benzoyl/sulfonyl hydrazone derivatives using molecular docking, ADMET, and molecular dynamics simulations. Journal of research in pharmacy (online). 2023; 27(4): 1567 - 1576. 10.29228/jrp.442 |
| Vancouver | YILMAZ G,AKTAR B,ORUÇ EMRE E In silico modeling of α-glucosidase, aldose reductase, and PPAR-γ with benzoyl/sulfonyl hydrazone derivatives using molecular docking, ADMET, and molecular dynamics simulations. Journal of research in pharmacy (online). 2023; 27(4): 1567 - 1576. 10.29228/jrp.442 |
| IEEE | YILMAZ G,AKTAR B,ORUÇ EMRE E "In silico modeling of α-glucosidase, aldose reductase, and PPAR-γ with benzoyl/sulfonyl hydrazone derivatives using molecular docking, ADMET, and molecular dynamics simulations." Journal of research in pharmacy (online), 27, ss.1567 - 1576, 2023. 10.29228/jrp.442 |
| ISNAD | YILMAZ, Gizem TATAR vd. "In silico modeling of α-glucosidase, aldose reductase, and PPAR-γ with benzoyl/sulfonyl hydrazone derivatives using molecular docking, ADMET, and molecular dynamics simulations". Journal of research in pharmacy (online) 27/4 (2023), 1567-1576. https://doi.org/10.29228/jrp.442 |
