Literature DB >> 33882412

Hydroxytyrosol as anti-parkinsonian molecule: Assessment using in-silico and MPTP-induced Parkinson's disease model.

Anjana Pathania1, Rajnish Kumar2, Rajat Sandhir3.   

Abstract

3-Hydroxytyrosol (HXT) is a natural polyphenol present in extra virgin olive oil. It is a key component of Mediterranean diet and is known for its strong antioxidant activity. The present study evaluated the potential of HXT as an anti-parkinsonian molecule in terms of its ability to inhibit MAO-B and thereby maintaining dopamine (DA) levels in Parkinson's disease (PD). In-silico molecular docking study followed by MMGBSA binding free energy calculation revealed that HXT has a strong binding affinity for MAO-B in comparison to MAO-A. Moreover, rasagiline and HXT interacted with the similar binding sites and modes of interactions. Additionally, molecular dynamics simulation studies revealed stable nature of HXT-MAO-B interaction and also provided information about the amino acid residues involved in binding. Moreover, in vitro studies revealed that HXT inhibited MAO-B in human platelets with IC50 value of 7.78 μM. In vivo studies using MPTP-induced mouse model of PD revealed increase in DA levels with concomitant decrease in DA metabolites (DOPAC and HVA) on HXT treatment. Furthermore, MAO-B activity was also inhibited on HXT administration to PD mice. In addition, HXT treatment prevented MPTP-induced loss of DA neurons in substantia nigra and their nerve terminals in the striatum. HXT also attenuated motor impairments in PD mice assessed by catalepsy bar, narrow beam walk and open field tests. Thus, the present findings reveal HXT as a potential inhibitor of MAO-B, which may be used as a lead molecule for the development of therapeutics for PD.
Copyright © 2021 The Authors. Published by Elsevier Masson SAS.. All rights reserved.

Entities:  

Keywords:  Dopamine; Hydroxytyrosol; In silico; Monoamine oxidase; Olive oil; Parkinson’s disease

Year:  2021        PMID: 33882412     DOI: 10.1016/j.biopha.2021.111525

Source DB:  PubMed          Journal:  Biomed Pharmacother        ISSN: 0753-3322            Impact factor:   6.529


  2 in total

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Journal:  Drug Des Devel Ther       Date:  2022-05-18       Impact factor: 4.319

Review 2.  Deep learning tools for advancing drug discovery and development.

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Journal:  3 Biotech       Date:  2022-04-09       Impact factor: 2.893

  2 in total

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