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In silico characterisation of olive phenolic compounds as potential cyclooxygenase modulators.

journal contribution
posted on 2024-11-02, 14:30 authored by Julia Liang, Natalie Bonvino, Andrew HungAndrew Hung, Tom Karagiannis
Non-steroidal anti-inflammatory drugs (NSAIDs) are widely used to reduce pain. These target cyclooxygenase (COX) enzymes which produce inflammatory mediators. Adverse effects associated with the use of traditional NSAIDs have led to a rise in the development of alternative therapies. Derived from Olea Europaea, olive oil is a main component of the Mediterranean diet, containing phenolic compounds that contribute to its antioxidant and anti-inflammatory properties. It has previously been found that oleocanthal, a phenolic compound derived from the olive, had similar effects to ibuprofen, a commonly used NSAID. There is an abundance of olive phenolic compounds that have yet to be investigated for their anti-inflammatory properties. In this study, it was sought to identify potential olive-derived compounds with the ability to inhibit COX enzymes, and study the mechanisms using in silico approaches. Molecular docking was employed to determine the COX inhibitory potential of an olive phenolic compound library. From docking, it was determined that 1-oleyltyrosol (1OL) and ligstroside derivative 2 (LG2) demonstrated the greatest binding affinity to both COX-1 and COX-2. Interactions with these compounds were further examined using molecular dynamics simulations. The residue contributions to binding free energy were computed using Molecular Mechanics-Poisson Boltzmann Surface Area (MM-PBSA) methods, revealing that residues Leu93, Val116, Leu352, and Ala527 in COX-1 and COX-2 were key determinants of potential inhibition. Along with part 2 of this study, this work aims to identify and characterise novel phenolic compounds which may possess COX inhibitory properties.

History

Related Materials

  1. 1.
    DOI - Is published in 10.1016/j.jmgm.2020.107719
  2. 2.
    ISSN - Is published in 10933263

Journal

Journal of Molecular Graphics and Modelling

Volume

101

Number

107719

Start page

1

End page

13

Total pages

13

Publisher

Elsevier

Place published

United States

Language

English

Copyright

© 2020 Elsevier Inc. All rights reserved.

Former Identifier

2006103332

Esploro creation date

2022-11-23