Predictive modelling of angiotensin converting enzyme inhibitory dipeptides

Roseanne Norris, Fergal Casey, Richard J. FitzGerald, Denis Shields, Catherine Mooney

Research output: Contribution to journalArticlepeer-review

Abstract

The ability of docking to predict angiotensin converting enzyme (ACE) inhibitory dipeptide sequences was assessed using AutoDock Vina. All potential dipeptides and phospho-dipeptides were docked and scored. Peptide intestinal stability was assessed using a prediction amino acid clustering model. Selected dipeptides, having AutoDock Vina scores ≤ -8.1 and predicted to be 'stable' intestinally, were characterised, using LIGPLOT and for ACE-inhibitory potency. Two newly identified ACE-inhibitory dipeptides, Asp-Trp and Trp-Pro, having Vina scores of -8.3 and -8.6 gave IC 50 values of 258 ± 4.23 and 217 ± 15.7 μM, respectively. LIGPLOT analysis indicated no zinc interaction for these dipeptides. Phospho-dipeptides were predicted to have a good affinity for ACE. However, the experimentally determined IC 50 results did not correlate since, for example, Trp-pThr and Pro-pTyr, having Vina scores of -8.5 and -8.1, respectively, displayed IC 50 values of >500 μM. While docking allowed identification of new ACE inhibitory dipeptides, it may not be a fully reliable predictive tool in all cases.

Original languageEnglish
Pages (from-to)1349-1354
Number of pages6
JournalFood Chemistry
Volume133
Issue number4
DOIs
Publication statusPublished - 15 Aug 2012

Keywords

  • ACE inhibition
  • AutoDock Vina
  • Dipeptides
  • Intestinal stability
  • Predictive modelling

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