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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:

Keywords

  • Molecular Docking
  • Virtual Screening
  • Pharmacophore Model
  • Secondary Plant Metabolite
  • Glycoside Hydrolase Family

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
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, Berlin, 14195, Germany

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

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