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Discovery of New α-Glucosidase Inhibitors: Structure-Based Virtual Screening and Biological Evaluation.

ABSTRACT: α-Glycosidase inhibitors could inhibit the digestion of carbohydrates into glucose and promote glucose conversion, which have been used for the treatment of type 2 diabetes. In the present study, 52 candidates of α-glycosidase inhibitors were selected from commercial Specs compound library based on molecular docking-based virtual screening. Four different scaffold compounds (7, 22, 37, and 44) were identified as α-glycosidase inhibitors with IC₅₀ values ranging from 9.99 to 35.19 μM. All these four compounds exerted better inhibitory activities than the positive control (1-deoxynojirimycin, IC₅₀ = 52.02 μM). The fluorescence quenching study and kinetic analysis revealed that all these compounds directly bind to α-glycosidase and belonged to the noncompetitive α-glycosidase inhibitors. Then, the binding modes of these four compounds were carefully investigated. Significantly, these four compounds showed nontoxicity (IC₅₀ > 100 μM) toward the human normal hepatocyte cell line (LO2), which indicated the potential of developing into novel candidates for type 2 diabetes treatment.

SUBMITTER: Liu SK

PROVIDER: S-EPMC7982526 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Discovery of New α-Glucosidase Inhibitors: Structure-Based Virtual Screening and Biological Evaluation.

Liu Shan-Kui SK Hao Haifang H Bian Yuan Y Ge Yong-Xi YX Lu Shengyuan S Xie Hong-Xu HX Wang Kai-Ming KM Tao Hongrui H Yuan Chao C Zhang Juan J Zhang Jie J Jiang Cheng-Shi CS Zhu Kongkai K

Frontiers in chemistry 20210308

α-Glycosidase inhibitors could inhibit the digestion of carbohydrates into glucose and promote glucose conversion, which have been used for the treatment of type 2 diabetes. In the present study, 52 candidates of α-glycosidase inhibitors were selected from commercial Specs compound library based on molecular docking-based virtual screening. Four different scaffold compounds (7, 22, 37, and 44) were identified as α-glycosidase inhibitors with IC<sub>50</sub> values ranging from 9.99 to 35.19 μM. ...[more]

PMID: 33763406

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Project description:BackgroundSchistosomiasis is a neglected tropical disease caused by trematodes of the genus Schistosoma, with a limited treatment, mainly based on the use of praziquantel (PZQ). Currently, several aspartic proteases genes have already been identified within the genome of Schistosoma species. At least one enzyme encoded from this gene family (SmAP), named SmCD1, has been validated for the development of schistosomicidal drugs, since it has a key role in haemoglobin digestion by worms.ObjectiveIn this work, we integrated a structure-based virtual screening campaign, enzymatic assays and adult worms ex vivo experiments aiming to discover the first classes of SmCD1 inhibitors.MethodsInitially, the 3D-structures of SmCD1, SmCD2 and SmCD3 were generated using homology modelling approach. Using these models, we prioritised 50 compounds from 20,000 compounds from ChemBridge database for further testing in adult worm aqueous extract (AWAE) and recombinant SmCD1 using enzymatic assays.FindingsSeven compounds were confirmed as hits and among them, two compounds representing new chemical scaffolds, named 5 and 19, had IC50 values against SmCD1 close to 100 μM while presenting binding efficiency indexes comparable to or even higher than pepstatin, a classical tight-binding peptide inhibitor of aspartyl proteases. Upon activity comparison against mammalian enzymes, compound 50 was selective and the most potent against the AWAE aspartic protease activity (IC50 = 77.7 μM). Combination of computational and experimental results indicate that compound 50 is a selective inhibitor of SmCD2. Compounds 5, 19 and 50 tested at low concentrations (10 uM) were neither cytotoxic against WSS-1 cells (48 h) nor could kill adult worms ex-vivo, although compounds 5 and 50 presented a slight decrease on female worms motility on late incubations times (48 or 72 h).Main conclusionOverall, the inhibitors identified in this work represent promising hits for further hit-to-lead optimisation.

Dataset Information

Discovery of New α-Glucosidase Inhibitors: Structure-Based Virtual Screening and Biological Evaluation.

Publications

Discovery of New α-Glucosidase Inhibitors: Structure-Based Virtual Screening and Biological Evaluation.

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