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Identifying promising GSK3β inhibitors for cancer management: a computational pipeline combining virtual screening and molecular dynamics simulations

Glycogen synthase kinase-3 (GSK3β), a serine/threonine protein kinase, has been discovered as a novel target for anticancer drugs. Although GSK3β is involved in multiple pathways linked to the etiology of various cancers, no specific GSK3β inhibitor has been authorized for cancer therapy. Most of it...

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Autores principales: Hua, Libo, Anjum, Farah, Shafie, Alaa, Ashour, Amal Adnan, Almalki, Abdulraheem Ali, Alqarni, Ali Abdullah, Banjer, Hamsa Jameel, Almaghrabi, Sarah Abdullah, He, Shan, Xu, Nenggui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10239944/
https://www.ncbi.nlm.nih.gov/pubmed/37284581
http://dx.doi.org/10.3389/fchem.2023.1200490
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author Hua, Libo
Anjum, Farah
Shafie, Alaa
Ashour, Amal Adnan
Almalki, Abdulraheem Ali
Alqarni, Ali Abdullah
Banjer, Hamsa Jameel
Almaghrabi, Sarah Abdullah
He, Shan
Xu, Nenggui
author_facet Hua, Libo
Anjum, Farah
Shafie, Alaa
Ashour, Amal Adnan
Almalki, Abdulraheem Ali
Alqarni, Ali Abdullah
Banjer, Hamsa Jameel
Almaghrabi, Sarah Abdullah
He, Shan
Xu, Nenggui
author_sort Hua, Libo
collection PubMed
description Glycogen synthase kinase-3 (GSK3β), a serine/threonine protein kinase, has been discovered as a novel target for anticancer drugs. Although GSK3β is involved in multiple pathways linked to the etiology of various cancers, no specific GSK3β inhibitor has been authorized for cancer therapy. Most of its inhibitors have toxicity effects therefore, there is a need to develop safe and more potent inhibitors. In this study, a library of 4,222 anti-cancer compounds underwent rigorous computational screening to identify potential candidates for targeting the binding pocket of GSK3β. The screening process involved various stages, including docking-based virtual screening, physicochemical and ADMET analysis, and molecular dynamics simulations. Ultimately, two hit compounds, BMS-754807 and GSK429286A, were identified as having high binding affinities to GSK3β. BMS-754807 and GSK429286A exhibited binding affinities of −11.9, and −9.8 kcal/mol, respectively, which were greater than that of the positive control (−7.6 kcal/mol). Further, molecular dynamics simulations for 100 ns were employed to optimize the interaction between the compounds and GSK3β, and the simulations demonstrated that the interaction was stable and consistent throughout the study. These hits were also anticipated to have good drug-like properties. Finally, this study suggests that BMS-754807 and GSK429286A may undergo experimental validation to evaluate their potential as cancer treatments in clinical settings.
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spelling pubmed-102399442023-06-06 Identifying promising GSK3β inhibitors for cancer management: a computational pipeline combining virtual screening and molecular dynamics simulations Hua, Libo Anjum, Farah Shafie, Alaa Ashour, Amal Adnan Almalki, Abdulraheem Ali Alqarni, Ali Abdullah Banjer, Hamsa Jameel Almaghrabi, Sarah Abdullah He, Shan Xu, Nenggui Front Chem Chemistry Glycogen synthase kinase-3 (GSK3β), a serine/threonine protein kinase, has been discovered as a novel target for anticancer drugs. Although GSK3β is involved in multiple pathways linked to the etiology of various cancers, no specific GSK3β inhibitor has been authorized for cancer therapy. Most of its inhibitors have toxicity effects therefore, there is a need to develop safe and more potent inhibitors. In this study, a library of 4,222 anti-cancer compounds underwent rigorous computational screening to identify potential candidates for targeting the binding pocket of GSK3β. The screening process involved various stages, including docking-based virtual screening, physicochemical and ADMET analysis, and molecular dynamics simulations. Ultimately, two hit compounds, BMS-754807 and GSK429286A, were identified as having high binding affinities to GSK3β. BMS-754807 and GSK429286A exhibited binding affinities of −11.9, and −9.8 kcal/mol, respectively, which were greater than that of the positive control (−7.6 kcal/mol). Further, molecular dynamics simulations for 100 ns were employed to optimize the interaction between the compounds and GSK3β, and the simulations demonstrated that the interaction was stable and consistent throughout the study. These hits were also anticipated to have good drug-like properties. Finally, this study suggests that BMS-754807 and GSK429286A may undergo experimental validation to evaluate their potential as cancer treatments in clinical settings. Frontiers Media S.A. 2023-05-22 /pmc/articles/PMC10239944/ /pubmed/37284581 http://dx.doi.org/10.3389/fchem.2023.1200490 Text en Copyright © 2023 Hua, Anjum, Shafie, Ashour, Almalki, Alqarni, Banjer, Almaghrabi, He and Xu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Chemistry
Hua, Libo
Anjum, Farah
Shafie, Alaa
Ashour, Amal Adnan
Almalki, Abdulraheem Ali
Alqarni, Ali Abdullah
Banjer, Hamsa Jameel
Almaghrabi, Sarah Abdullah
He, Shan
Xu, Nenggui
Identifying promising GSK3β inhibitors for cancer management: a computational pipeline combining virtual screening and molecular dynamics simulations
title Identifying promising GSK3β inhibitors for cancer management: a computational pipeline combining virtual screening and molecular dynamics simulations
title_full Identifying promising GSK3β inhibitors for cancer management: a computational pipeline combining virtual screening and molecular dynamics simulations
title_fullStr Identifying promising GSK3β inhibitors for cancer management: a computational pipeline combining virtual screening and molecular dynamics simulations
title_full_unstemmed Identifying promising GSK3β inhibitors for cancer management: a computational pipeline combining virtual screening and molecular dynamics simulations
title_short Identifying promising GSK3β inhibitors for cancer management: a computational pipeline combining virtual screening and molecular dynamics simulations
title_sort identifying promising gsk3β inhibitors for cancer management: a computational pipeline combining virtual screening and molecular dynamics simulations
topic Chemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10239944/
https://www.ncbi.nlm.nih.gov/pubmed/37284581
http://dx.doi.org/10.3389/fchem.2023.1200490
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