Virtual screening of acetylcholinesterase inhibitors through pharmacophore-based 3D-QSAR modeling, ADMET, molecular docking, and MD simulation studies

© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law..

Alzheimer's disease (AD) is a leading cause of dementia in elderly patients. The pathophysiology of AD includes various pathways, such as the degradation of acetylcholine, amyloid-beta deposition, neurofibrillary tangle formation, and neuroinflammation. Many studies showed that targeting acetylcholinesterase enzyme (AChE) to improve acetylcholine can be an effective option to treat AD. In the current work, we employed a 3D QSAR-based approach to generate a pharmacophore to screen a chemical library of compounds that may inhibit AChE. Data from experimental studies were collected and used for the generation of pharmacophores. More than 1 million compounds were screened, and further drug-like properties were determined via in-silico ADMET studies. Techniques like molecular docking and molecular dynamics simulation were performed to analyze the binding of novel AChE inhibitors. A novel AChE inhibitor ligand-1 was identified as best with a docking score of -13.560 kcal/mol with RMSD of 1.71 Å during a 100 ns MD run. Further biological studies can give an insight into the potential of ligand-1 as a therapeutic agent for AD.

Graphical Abstract:.

Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-024-00189-1.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:12

Enthalten in:

In silico pharmacology - 12(2024), 1 vom: 07., Seite 13

Sprache:

Englisch

Beteiligte Personen:

Kumar, Hitesh [VerfasserIn]
Datusalia, Ashok Kumar [VerfasserIn]
Khatik, Gopal L [VerfasserIn]

Links:

Volltext

Themen:

3D pharmacophore
Acetylcholinesterase
Alzheimer’s disease
Journal Article
Molecular docking
Molecular dynamic
Virtual screening

Anmerkungen:

Date Revised 20.02.2024

published: Electronic-eCollection

Citation Status PubMed-not-MEDLINE

doi:

10.1007/s40203-024-00189-1

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM368609197