虚拟筛选
药效团
结合亲和力
计算生物学
对接(动物)
小分子
化学
同源建模
药物发现
计算机科学
医学
药理学
生物
生物化学
受体
酶
护理部
作者
Sajjad Haider,Mamona Mushtaq,Mohammad Nur‐e‐Alam,Aftab Ahmed,Zaheer Ul-Haq
标识
DOI:10.1080/07391102.2023.2270708
摘要
Diabetes results in substantial disabilities, diminished quality of life, and mortality that imposes a huge economic burden on societies and governments worldwide. Despite the absence of specific oral therapies at present, there exists an urgent requirement to develop a novel drug for the treatment of diabetes mellitus. The membrane protein sodium glucose co-transporters (SGLT1) present a captivating therapeutic target for diabetes, given its pivotal role in facilitating glucose absorption in the small intestine, offering immense promise for potential therapeutic intervention. In this connection, the present study is aimed at identifying potential inhibitors of SGLT1 from a small molecule database, including compounds from both natural as well as synthetic origins. A comprehensive approach was employed, by integrating homology modeling, ligand-based pharmacophore modeling, virtual screening, and molecular docking simulation. The process resulted in the identification of 16 new compounds, featuring similar attributes as observed for the documented actives. In a systematic screening procedure, five potential virtual hits were selected for simulation studies followed by subsequent binding free energy calculations, providing deeper insight into the time-dependent behavior of protein-ligand complexes in a dynamic state. In conclusion, our findings demonstrated that the identified compounds, particularly compounds 81 and 91, exhibit enhanced stability and favorable binding affinities with the target protein, marking them promising candidates for further investigations.Communicated by Ramaswamy H. Sarma.
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