Journal of Molecular Modeling

, 25:275 | Cite as

In silico evaluation of condensed and hydrolysable tannins as inhibitors of pancreatic α-amylase

  • Paulo Sérgio Alves Bueno
  • Camila Gabriel Kato-Schwartz
  • Diego de Souza Lima
  • Adelar Bracht
  • Rosane Marina Peralta
  • Flavio Augusto Vicente SeixasEmail author
Original Paper


Amylases are interesting targets for antidiabetic drugs because their inhibition is able to lower glycaemia without the need of hormonal control, as promoted by insulin or glibenclamide. In this context, the comparison between the binding features of α-amylases with their substrate and known inhibitors may provide insights aiming at the discovery of new antidiabetic drugs. In this work, the structure of the porcine pancreatic α-amylase was modelled with the acarbose pentasaccharide inhibitor, and used in structure-based virtual screening simulations based on a library containing the structures of amylose (AMY), acarbose (ACA) and the more representative structures of condensed tannin (CTN) and hydrolysable tannin (HTN). After validation of the methodology by redocking (mean rmsd ~ 0.8 Å), the scores provided by programs AutoDock/Molegro were contradictory (− 1.5/− 23.3; − 3.5/− 24.6; − 4.3/− 14.6; −/− 19.5 for AMY, ACA, CTN and HTN respectively), indicating that a more sensitive methodology was necessary. The ΔGbinding was calculated by the molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) method, which indicated that the HTN, ACA and CTN had higher affinities for the enzyme regarding the AMY substrate, with values of − 350.0, − 346.2, − 320.5 and − 209.2 kJ mol−1, respectively. The predicted relative affinities of HTN and CTN are in agreement with those obtained experimentally. The results provided useful information for the characterization of tannin binding to α-amylase, which can be applied in future studies aiming at finding new hypoglycaemic molecules among natural products.


Enzyme Diabetes Natural products MM-PBSA Docking 



The authors would like to acknowledge LNCC for computational facilities.

Funding information

This work was financially supported by Fundação Araucária (grant numbers 147/14 and 40/16), Coordination for the Improvement of Higher Education Personnel–Brazil (CAPES, cód 001) and National Council for Scientific and Technological Development–Brazil (CNPq grant number 305960/2015-6); CENAPAD/SP (Project number 520).

Supplementary material

894_2019_4176_MOESM1_ESM.docx (1.7 mb)
ESM 1 (DOCX 1716 kb)


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Paulo Sérgio Alves Bueno
    • 1
  • Camila Gabriel Kato-Schwartz
    • 1
    • 2
  • Diego de Souza Lima
    • 3
  • Adelar Bracht
    • 1
    • 2
  • Rosane Marina Peralta
    • 1
    • 2
  • Flavio Augusto Vicente Seixas
    • 3
    Email author
  1. 1.Department of BiochemistryUniversidade Estadual de MaringáMaringáBrazil
  2. 2.Post-Graduate Program of Food ScienceUniversidade Estadual de MaringáMaringáBrazil
  3. 3.Department of TechnologyUniversidade Estadual de Maringá, UEMUmuaramaBrazil

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