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  5. In silico approaches to predict the potential of milk protein-derived peptides as dipeptidyl peptidase IV (DPP-IV) inhibitors
 
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In silico approaches to predict the potential of milk protein-derived peptides as dipeptidyl peptidase IV (DPP-IV) inhibitors

Author(s)
Nongonierma, Alice B.  
Mooney, Catherine  
Shields, Denis C.  
FitzGerald, Richard J.  
Uri
http://hdl.handle.net/10197/13040
Date Issued
2014-07
Date Available
2022-08-05T08:57:56Z
Abstract
Molecular docking of a library of all 8000 possible tripeptides to the active site of DPP-IV was used to determine their binding potential. A number of tripeptides were selected for experimental testing, however, there was no direct correlation between the Vina score and their in vitro DPP-IV inhibitory properties. While Trp-Trp-Trp, the peptide with the best docking score, was a moderate DPP-IV inhibitor (IC50 216 μM), Lineweaver and Burk analysis revealed its action to be non-competitive. This suggested that it may not bind to the active site of DPP-IV as assumed in the docking prediction. Furthermore, there was no significant link between DPP-IV inhibition and the physicochemical properties of the peptides (molecular mass, hydrophobicity, hydrophobic moment (μH), isoelectric point (pI) and charge). LIGPLOTs indicated that competitive inhibitory peptides were predicted to have both hydrophobic and hydrogen bond interactions with the active site of DPP-IV. DPP-IV inhibitory peptides generally had a hydrophobic or aromatic amino acid at the N-terminus, preferentially a Trp for non-competitive inhibitors and a broader range of residues for competitive inhibitors (Ile, Leu, Val, Phe, Trp or Tyr). Two of the potent DPP-IV inhibitors, Ile-Pro-Ile and Trp-Pro (IC 50 values of 3.5 and 44.2 μM, respectively), were predicted to be gastrointestinally/intestinally stable. This work highlights the needs to test the assumptions (i.e. competitive binding) of any integrated strategy of computational and experimental screening, in optimizing screening. Future strategies targeting allosteric mechanisms may need to rely more on structure-activity relationship modeling, rather than on docking, in computationally selecting peptides for screening.
Sponsorship
Enterprise Ireland
Science Foundation Ireland
Type of Material
Journal Article
Publisher
Elsevier
Journal
Peptides
Volume
57
Start Page
43
End Page
51
Copyright (Published Version)
2014 Elsevier
Subjects

Bioactive peptides

Dipeptidyl peptidase ...

Hydrophobicity

Milk

Molecular docking

Predictive modeling

DOI
10.1016/j.peptides.2014.04.018
Language
English
Status of Item
Peer reviewed
ISSN
0196-9781
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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RMS_Nongonierma_2014.pdf

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752.48 KB

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Checksum (MD5)

30992402c63ed641aa97dd1f81796aec

Owning collection
Computer Science Research Collection
Mapped collections
CASL Research Collection•
Conway Institute Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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