Cargando…

Identification of Potential Inhibitors for the Treatment of Alkaptonuria Using an Integrated In Silico Computational Strategy

Alkaptonuria (AKU) is a rare genetic autosomal recessive disorder characterized by elevated serum levels of homogentisic acid (HGA). In this disease, tyrosine metabolism is interrupted because of the alterations in homogentisate dioxygenase (HGD) gene. The patient suffers from ochronosis, fractures,...

Descripción completa

Detalles Bibliográficos
Autores principales: Zaib, Sumera, Rana, Nehal, Hussain, Nadia, Ogaly, Hanan A., Dera, Ayed A., Khan, Imtiaz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10058836/
https://www.ncbi.nlm.nih.gov/pubmed/36985595
http://dx.doi.org/10.3390/molecules28062623
_version_ 1785016730503872512
author Zaib, Sumera
Rana, Nehal
Hussain, Nadia
Ogaly, Hanan A.
Dera, Ayed A.
Khan, Imtiaz
author_facet Zaib, Sumera
Rana, Nehal
Hussain, Nadia
Ogaly, Hanan A.
Dera, Ayed A.
Khan, Imtiaz
author_sort Zaib, Sumera
collection PubMed
description Alkaptonuria (AKU) is a rare genetic autosomal recessive disorder characterized by elevated serum levels of homogentisic acid (HGA). In this disease, tyrosine metabolism is interrupted because of the alterations in homogentisate dioxygenase (HGD) gene. The patient suffers from ochronosis, fractures, and tendon ruptures. To date, no medicine has been approved for the treatment of AKU. However, physiotherapy and strong painkillers are administered to help mitigate the condition. Recently, nitisinone, an FDA-approved drug for type 1 tyrosinemia, has been given to AKU patients in some countries and has shown encouraging results in reducing the disease progression. However, this drug is not the targeted treatment for AKU, and causes keratopathy. Therefore, the foremost aim of this study is the identification of potent and druggable inhibitors of AKU with no or minimal side effects by targeting 4-hydroxyphenylpyruvate dioxygenase. To achieve our goal, we have performed computational modelling using BioSolveIT suit. The library of ligands for molecular docking was acquired by fragment replacement of reference molecules by ReCore. Subsequently, the hits were screened on the basis of estimated affinities, and their pharmacokinetic properties were evaluated using SwissADME. Afterward, the interactions between target and ligands were investigated using Discovery Studio. Ultimately, compounds c and f were identified as potent inhibitors of 4-hydroxyphenylpyruvate dioxygenase.
format Online
Article
Text
id pubmed-10058836
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-100588362023-03-30 Identification of Potential Inhibitors for the Treatment of Alkaptonuria Using an Integrated In Silico Computational Strategy Zaib, Sumera Rana, Nehal Hussain, Nadia Ogaly, Hanan A. Dera, Ayed A. Khan, Imtiaz Molecules Article Alkaptonuria (AKU) is a rare genetic autosomal recessive disorder characterized by elevated serum levels of homogentisic acid (HGA). In this disease, tyrosine metabolism is interrupted because of the alterations in homogentisate dioxygenase (HGD) gene. The patient suffers from ochronosis, fractures, and tendon ruptures. To date, no medicine has been approved for the treatment of AKU. However, physiotherapy and strong painkillers are administered to help mitigate the condition. Recently, nitisinone, an FDA-approved drug for type 1 tyrosinemia, has been given to AKU patients in some countries and has shown encouraging results in reducing the disease progression. However, this drug is not the targeted treatment for AKU, and causes keratopathy. Therefore, the foremost aim of this study is the identification of potent and druggable inhibitors of AKU with no or minimal side effects by targeting 4-hydroxyphenylpyruvate dioxygenase. To achieve our goal, we have performed computational modelling using BioSolveIT suit. The library of ligands for molecular docking was acquired by fragment replacement of reference molecules by ReCore. Subsequently, the hits were screened on the basis of estimated affinities, and their pharmacokinetic properties were evaluated using SwissADME. Afterward, the interactions between target and ligands were investigated using Discovery Studio. Ultimately, compounds c and f were identified as potent inhibitors of 4-hydroxyphenylpyruvate dioxygenase. MDPI 2023-03-14 /pmc/articles/PMC10058836/ /pubmed/36985595 http://dx.doi.org/10.3390/molecules28062623 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zaib, Sumera
Rana, Nehal
Hussain, Nadia
Ogaly, Hanan A.
Dera, Ayed A.
Khan, Imtiaz
Identification of Potential Inhibitors for the Treatment of Alkaptonuria Using an Integrated In Silico Computational Strategy
title Identification of Potential Inhibitors for the Treatment of Alkaptonuria Using an Integrated In Silico Computational Strategy
title_full Identification of Potential Inhibitors for the Treatment of Alkaptonuria Using an Integrated In Silico Computational Strategy
title_fullStr Identification of Potential Inhibitors for the Treatment of Alkaptonuria Using an Integrated In Silico Computational Strategy
title_full_unstemmed Identification of Potential Inhibitors for the Treatment of Alkaptonuria Using an Integrated In Silico Computational Strategy
title_short Identification of Potential Inhibitors for the Treatment of Alkaptonuria Using an Integrated In Silico Computational Strategy
title_sort identification of potential inhibitors for the treatment of alkaptonuria using an integrated in silico computational strategy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10058836/
https://www.ncbi.nlm.nih.gov/pubmed/36985595
http://dx.doi.org/10.3390/molecules28062623
work_keys_str_mv AT zaibsumera identificationofpotentialinhibitorsforthetreatmentofalkaptonuriausinganintegratedinsilicocomputationalstrategy
AT rananehal identificationofpotentialinhibitorsforthetreatmentofalkaptonuriausinganintegratedinsilicocomputationalstrategy
AT hussainnadia identificationofpotentialinhibitorsforthetreatmentofalkaptonuriausinganintegratedinsilicocomputationalstrategy
AT ogalyhanana identificationofpotentialinhibitorsforthetreatmentofalkaptonuriausinganintegratedinsilicocomputationalstrategy
AT deraayeda identificationofpotentialinhibitorsforthetreatmentofalkaptonuriausinganintegratedinsilicocomputationalstrategy
AT khanimtiaz identificationofpotentialinhibitorsforthetreatmentofalkaptonuriausinganintegratedinsilicocomputationalstrategy