Literature DB >> 31129879

Receptor-based pharmacophore modeling, virtual screening, and molecular docking studies for the discovery of novel GSK-3β inhibitors.

Ahmed M El Kerdawy1,2,3, Alaa A Osman4, Marwa A Zaater5.   

Abstract

Considering the emerging importance of glycogen synthase kinase 3 beta (GSK-3β) inhibitors in treatment of Alzheimer's disease, multi-protein structure receptor-based pharmacophore modeling was adopted to generate a 3D pharmacophore model for (GSK-3β) inhibitors. The generated 3D pharmacophore was then validated using a test set of 1235 compounds. The ZINCPharmer web tool was used to virtually screen the public ZINC database using the generated 3D pharmacophore. A set of 12,251 hits was produced and then filtered according to their lead-like properties, predicted central nervous system (CNS) activity, and Pan-assay interference compounds (PAINS) fragments to 630 compounds. Scaffold Hunter was then used to cluster the filtered compounds according to their chemical structure framework. From the different clusters, 123 compounds were selected to cover the whole chemical space of the obtained hits. The SwissADME online tool was then used to filter out the compounds with undesirable pharmacokinetic properties giving a set of 91 compounds with promising predicted pharmacodynamic and pharmacokinetic properties. To confirm their binding capability to the GSK-3β binding site, molecular docking simulations were performed for the final 91 compounds in the GSK-3β binding site. Twenty-five compounds showed acceptable binding poses that bind to the key amino acids in the binding site Asp133 and Val135 with good binding scores. The quinolin-2-one derivative ZINC67773573 was found to be a promising lead for designing new GSK-3β inhibitors for Alzheimer's disease treatment. Graphical abstract A 3D pharmacophore model for the discovery of novel (GSK-3β) inhibitors.

Entities:  

Keywords:  Alzheimer’s disease; GSK-3β; Molecular docking; Pharmacophore modeling; Tau protein aggregation; Virtual screening

Mesh:

Substances:

Year:  2019        PMID: 31129879     DOI: 10.1007/s00894-019-4032-5

Source DB:  PubMed          Journal:  J Mol Model        ISSN: 0948-5023            Impact factor:   1.810


  4 in total

1.  Novel Small-Molecule Scaffolds as Candidates against the SARS Coronavirus 2 Main Protease: A Fragment-Guided in Silico Approach.

Authors:  Teresa L Augustin; Roxanna Hajbabaie; Matthew T Harper; Taufiq Rahman
Journal:  Molecules       Date:  2020-11-24       Impact factor: 4.411

2.  Novel oxindole/benzofuran hybrids as potential dual CDK2/GSK-3β inhibitors targeting breast cancer: design, synthesis, biological evaluation, and in silico studies.

Authors:  Wagdy M Eldehna; Sara T Al-Rashood; Tarfah Al-Warhi; Razan O Eskandrani; Amal Alharbi; Ahmed M El Kerdawy
Journal:  J Enzyme Inhib Med Chem       Date:  2021-12       Impact factor: 5.051

3.  Establishing an Analogue Based In Silico Pipeline in the Pursuit of Novel Inhibitory Scaffolds against the SARS Coronavirus 2 Papain-Like Protease.

Authors:  Roxanna Hajbabaie; Matthew T Harper; Taufiq Rahman
Journal:  Molecules       Date:  2021-02-20       Impact factor: 4.927

Review 4.  Recent Developments in New Therapeutic Agents against Alzheimer and Parkinson Diseases: In-Silico Approaches.

Authors:  Pedro Cruz-Vicente; Luís A Passarinha; Samuel Silvestre; Eugenia Gallardo
Journal:  Molecules       Date:  2021-04-11       Impact factor: 4.411

  4 in total

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