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Abstract

Theoretical Study of Anti-Alzheimer’s Disease Using Molecular Modeling Methods †

1
Group of Computational and Medicinal Chemistry LMCE Laboratory, University of Mohamed Khider Biskra, Biskra 07000, Algeria
2
Laboratory of Natural and Bioactive Substances, LASNABIO, University of Abou-Bakr Belkaid, Tlemcen 13000, Algeria
3
Department of Matter Sciences, University of Mohamed Khider Biskra, BP 145 RP, Biskra 07000, Algeria
4
Laboratory of Molecular Chemistry and Environment (LMCE), Department of Chemistry, University Mohamed Khider, BP 145 RP, Biskra 07000, Algeria
*
Author to whom correspondence should be addressed.
Presented at the 3rd International Electronic Conference on Biomolecules, 23–25 April 2024; Available online: https://sciforum.net/event/IECBM2024.
Proceedings 2024, 103(1), 46; https://doi.org/10.3390/proceedings2024103046
Published: 1 July 2024
(This article belongs to the Proceedings of The 3rd International Electronic Conference on Biomolecules)
Neurodegenerative diseases damage the nervous system and lead to a variety of complex progressive chronic issues. Alzheimer’s disease (AD) is one such case. The most common form of dementia is a degenerative disorder of the brain that leads to memory loss, confusion, and behavioral changes. The main drug classes currently used to treat AD are acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitors. In this study, we investigated the inhibitory effects of a series of newly synthesized compounds of 2-hydroxy-N-phenylbenzamide derivatives on AchE and BchE, using molecular modeling approaches such as molecular dynamics and bioisosteric replacement to treat or reduce Alzheimer’s disease.
The best docking complexes, L18 and L6′, were used as simulation inputs to evaluate the stability of the complex (protein–ligand), using potential energy as a function of time. These results were verified using molecular dynamics simulations, demonstrating the strength of both complexes.
Furthermore, we found that the bioisosteric replacement method successfully proposed two novel analogs of each compound (L18 and L6′) with low energy scores and similar biological activity by replacing molecular substructures with similar chemical groups.
All these methods allow us to identify new inhibitors that have potential against this disease and can be suggested as new drugs against Alzheimer’s disease.

Author Contributions

Data collection, software, formal analysis, and first draft of the manuscript were prepared by F.H. All authors commented on previous versions of the manuscript. I.D. contributed to the conceptualization and supervision of the study. N.M., I.D. and R.K. contributed to the interpretation of docking and ADME-T studies. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All the data in the article are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare that they have no conflict of interest.
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Share and Cite

MDPI and ACS Style

Hasni, F.; Daoud, I.; Melkemi, N.; Kherachi, R. Theoretical Study of Anti-Alzheimer’s Disease Using Molecular Modeling Methods. Proceedings 2024, 103, 46. https://doi.org/10.3390/proceedings2024103046

AMA Style

Hasni F, Daoud I, Melkemi N, Kherachi R. Theoretical Study of Anti-Alzheimer’s Disease Using Molecular Modeling Methods. Proceedings. 2024; 103(1):46. https://doi.org/10.3390/proceedings2024103046

Chicago/Turabian Style

Hasni, Ferdaous, Ismail Daoud, Nadjib Melkemi, and Rania Kherachi. 2024. "Theoretical Study of Anti-Alzheimer’s Disease Using Molecular Modeling Methods" Proceedings 103, no. 1: 46. https://doi.org/10.3390/proceedings2024103046

APA Style

Hasni, F., Daoud, I., Melkemi, N., & Kherachi, R. (2024). Theoretical Study of Anti-Alzheimer’s Disease Using Molecular Modeling Methods. Proceedings, 103(1), 46. https://doi.org/10.3390/proceedings2024103046

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