Structure‐Based Approaches for the Prediction of Alzheimer's Disease Inhibitors: Comparative Interactions Analysis, Pharmacophore Modeling and Molecular Dynamics Simulations

Author:

Zerroug Enfale1ORCID,Belaidi Salah1ORCID,Chtita Samir2ORCID,Tuffaha Ghada3,AbulQais Faizan4ORCID,Kciuk Mateusz56ORCID,Dubey Amit7ORCID,Taha Mutasem O.8ORCID

Affiliation:

1. Group of Computational and Pharmaceutical Chemistry LMCE Laboratory University of Biskra, BP 145 Biskra 07000 Algeria

2. Faculty of Sciences Ben M'Sik Hassan II University of Casablanca Sidi Othman, Casablanca Morocco

3. Hikma Pharmaceuticals 11942 Amman Jordan

4. Department of Agricultural Microbiology Aligarh Muslim University Aligarh UP 202002 India

5. Doctoral School of Exact and Natural Sciences University of Lodz Banacha Street 12/16 90-237 Lodz Poland

6. Department of Molecular Biotechnology and Genetics University of Lodz Banacha 12/16 90-237 Lodz Poland

7. Department of Pharmacology Saveetha Dental College and Hospital Saveetha Institute of Medical and Technical Sciences Chennai Tamil Nadu India

8. Drug Discovery Unit Department of Pharmaceutical Sciences Faculty of Pharmacy University of Jordan 11942 Amman Jordan

Abstract

AbstractDue to its significant role in neurodegeneration, Cyclin‐dependent kinase 5 (CDK5) has emerged as a potential target for addressing neuropathological disorders, including Alzheimer's disease (AD). The application of CDK5 inhibitors has demonstrated promise in the treatment of AD. This prompted us to model this interesting target using a computational workflow named Docking‐based Comparative Intermolecular Contacts Analysis (dbCICA). Approaches including 3D‐QSAR, genetic algorithm, and pharmacophore modeling were employed to discover new CDK inhibitors.

Publisher

Wiley

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