Literature DB >> 33103275

Screening and identifying of α-amylase inhibitors from medicine food homology plants: Insights from computational analysis and experimental studies.

Chao Jiang1, Li Wang1, Jiajia Shao1, Huijuan Jing1, Xin Ye1, Chengyu Jiang1, Hongxin Wang1,2, Chaoyang Ma1,2.   

Abstract

There is a growing interest in screening α-amylase inhibitors from natural products for application in the development of new antidiabetic drugs or functional foods. In this study, a structure-based virtual screening was applied to rapidly identify the α-amylase inhibitors from medicine food homology (MFH) plants. Similarity search, docking & scoring were used for further filter small molecules. As a result, 21 corresponding potential α-amylase inhibitors from MFH plants were obtained. And, six polyphenol compounds (curcumin, procyanidins, epicatechin gallate (ECG), epigallocatechin gallate (EGCG), hesperidin, and puerarin) were highlighted for further verification after a thorough assessment of the classification of hit molecules as well as docking scores. The results of the enzyme inhibition test showed that ECG, EGCG, and procyanidins had the better binding ability of α-amylase among these six polyphenols. The Ki values of ECG, EGCG, and procyanidins on α-amylase were 0.70, 1.68, and 0.24, respectively. The CD spectra results indicated that the three polyphenols can cause conformational changes in α-amylase. PRACTICAL APPLICATIONS: A structure-based virtual screening method for rapid identifying α-amylase inhibitors from MFH plants was developed successfully in this study. These findings suggested that natural polyphenols such as ECG, EGCG, and procyanidins may be a potential inhibitor of α-amylase which could be used as a nutrient supplement for the prevention of diabetes mellitus or can be further used in the development of hypoglycemic drugs. At the same time, it can provide theoretical guidance for the better utilization and development of medicine food homology plants containing these potential α-amylase inhibitors. Moreover, this work may provide ideas and references for the screening of other target protein inhibitors.
© 2020 Wiley Periodicals LLC.

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Keywords:  inhibition kinetic analysis; polyphenols; virtual screening; α-amylase inhibitor

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Year:  2020        PMID: 33103275     DOI: 10.1111/jfbc.13536

Source DB:  PubMed          Journal:  J Food Biochem        ISSN: 0145-8884            Impact factor:   2.720


  1 in total

1.  Discovery of TCMs and derivatives against the main protease of SARS-CoV-2 via high throughput screening, ADMET analysis, and inhibition assay in vitro.

Authors:  Xinyu Qi; Binglin Li; Alejandra B Omarini; Martin Gand; Xiaoli Zhang; Jiao Wang
Journal:  J Mol Struct       Date:  2022-07-12       Impact factor: 3.841

  1 in total

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