Volume 6 Supplement 1

9th German Conference on Chemoinformatics

Open Access

Discovery of novel α-amylase inhibitors using structure-based drug design

Journal of Cheminformatics20146(Suppl 1):P50

https://doi.org/10.1186/1758-2946-6-S1-P50

Published: 11 March 2014

α-Amylase is an endoamylase and belongs to glycoside hydrolase family 13 (GH 13) according to the classification of carbohydrate-active enzymes [1]. It initiates starch hydrolysis into smaller oligomers. Inhibitors of this enzyme are of pharmacological importance as α-amylase is considered as attractive target for treating elevated post-prandial blood glucose levels resulting in obesity and type II diabetes. Besides the application as a drug, it is highly interesting to classify nutritional components, such as food additives or secondary plant metabolites with respect to their modulation of α-amylase.

We present a model that predicts the affinity of small organic molecules to α- amylase. On the basis of available crystal structures (Figure 1) [2], we developed a virtual screening workflow for the identification of novel non- peptidic, non-carbohydrate α-amylase inhibitors. In addition to virtual screening using structure-based 3D pharmacophore models [3], molecular docking and clustering for diversity selection have been applied as post-screening filters. Fourteen virtual hits were purchased and tested in vitro using a kinetic assay with p-Nitrophenyl-α-d-maltopentaoside (PNPG5) as a chromogenic substrate. Three of those fourteen compounds showed concentration-dependent inhibition with promising IC50 values (hit rate: 21%).
Figure 1

Subsites of α-amylase with Acarviostatin II03 inhibitor, (ki ~ 14 nM) (PDB entry: 3OLE) and starch. Site of cleavage is between subsites -1 and +1.

Authors’ Affiliations

(1)
Computer-Aided Molecular Design, Pharmaceutical Chemistry Department, Freie Universität Berlin

References

  1. Cantarel BL, Coutinho PM, Rancurel C, Bernard T, Lombard V, Henrissat B: The carbohydrate-active enzymes database (cazy): An expert resource for glycogenomics. Nucleic Acids Res. 2009, 37: D233-D238. 10.1093/nar/gkn663.View ArticleGoogle Scholar
  2. Qin X, Ren L, Yang X, Bai F, Wang L, Geng P, Bai G, Shen Y: Structures of human pancreatic alpha-amylase in complex with acarviostatins: Implications for drug design against type II diabetes. J Struct Biol. 2011, 174 (1): 196-202. 10.1016/j.jsb.2010.11.020.View ArticleGoogle Scholar
  3. Wolber G, Langer T: Ligandscout: 3-d pharmacophores derived from protein-bound ligands and their use as virtual screening filters. J Chem Inf Model. 2005, 45 (1): 160-169. 10.1021/ci049885e.View ArticleGoogle Scholar

Copyright

© Al-Asri and Wolber; licensee Chemistry Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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