Predictive modelling of angiotensin converting enzyme inhibitory dipeptides
|Title:||Predictive modelling of angiotensin converting enzyme inhibitory dipeptides||Authors:||Norris, Roseanne
FitzGerald, Richard J.
Shields, Denis C.
|Permanent link:||http://hdl.handle.net/10197/3748||Date:||14-Aug-2012||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 IC50 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 IC50 results did not correlate since, for example, Trp-pThr and Pro-pTyr, having Vina scores of −8.5 and −8.1, respectively, displayed IC50 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.||Funding Details:||Science Foundation Ireland
Irish Research Council for Science, Engineering and Technology
|Type of material:||Journal Article||Publisher:||Elsevier||Journal:||Food Chemistry||Volume:||133||Issue:||4||Start page:||1349||End page:||1354||Copyright (published version):||2012 Elsevier Ltd.||Keywords:||Predictive modelling; Predictive modelling; ACE inhibition; Dipeptides; AutoDock Vina; Intestinal stability||Subject LCSH:||Angiotensin converting enzyme--Inhibitors
|DOI:||10.1016/j.foodchem.2012.02.023||Language:||en||Status of Item:||Peer reviewed|
|Appears in Collections:||Conway Institute Research Collection|
CASL Research Collection
Medicine Research Collection
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