1
|
Firouzi R, Sowlati-Hashjin S, Chávez-García C, Ashouri M, Karimi-Jafari MH, Karttunen M. Identification of Catechins' Binding Sites in Monomeric A β42 through Ensemble Docking and MD Simulations. Int J Mol Sci 2023; 24:ijms24098161. [PMID: 37175868 PMCID: PMC10179585 DOI: 10.3390/ijms24098161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 04/09/2023] [Accepted: 04/17/2023] [Indexed: 05/15/2023] Open
Abstract
The assembly of the amyloid-β peptide (Aβ) into toxic oligomers and fibrils is associated with Alzheimer's disease and dementia. Therefore, disrupting amyloid assembly by direct targeting of the Aβ monomeric form with small molecules or antibodies is a promising therapeutic strategy. However, given the dynamic nature of Aβ, standard computational tools cannot be easily applied for high-throughput structure-based virtual screening in drug discovery projects. In the current study, we propose a computational pipeline-in the framework of the ensemble docking strategy-to identify catechins' binding sites in monomeric Aβ42. It is shown that both hydrophobic aromatic interactions and hydrogen bonding are crucial for the binding of catechins to Aβ42. Additionally, it has been found that all the studied ligands, especially EGCG, can act as potent inhibitors against amyloid aggregation by blocking the central hydrophobic region of Aβ. Our findings are evaluated and confirmed with multi-microsecond MD simulations. Finally, it is suggested that our proposed pipeline, with low computational cost in comparison with MD simulations, is a suitable approach for the virtual screening of ligand libraries against Aβ.
Collapse
Affiliation(s)
- Rohoullah Firouzi
- Department of Physical Chemistry, Chemistry and Chemical Engineering Research Center of Iran, Tehran 1496813151, Iran
| | | | - Cecilia Chávez-García
- Department of Chemistry, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada
- The Centre of Advanced Materials and Biomaterials Research, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada
| | - Mitra Ashouri
- Department of Physical Chemistry, School of Chemistry, College of Science, University of Tehran, Tehran P.O. Box 14155-6619, Iran
| | - Mohammad Hossein Karimi-Jafari
- Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran P.O. Box 14155-6619, Iran
| | - Mikko Karttunen
- Department of Chemistry, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada
- The Centre of Advanced Materials and Biomaterials Research, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada
- Department of Physics and Astronomy, The University of Western Ontario, 1151 Richmond Street, London, ON N6A 3K7, Canada
| |
Collapse
|
2
|
Integrating structure-based and ligand-based approaches for computational drug design. Future Med Chem 2011; 3:735-50. [PMID: 21554079 DOI: 10.4155/fmc.11.18] [Citation(s) in RCA: 103] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Methods utilized in computer-aided drug design can be classified into two major categories: structure based and ligand based, using information on the structure of the protein or on the biological and physicochemical properties of bound ligands, respectively. In recent years there has been a trend towards integrating these two methods in order to enhance the reliability and efficiency of computer-aided drug-design approaches by combining information from both the ligand and the protein. This trend resulted in a variety of methods that include: pseudoreceptor methods, pharmacophore methods, fingerprint methods and approaches integrating docking with similarity-based methods. In this article, we will describe the concepts behind each method and selected applications.
Collapse
|
3
|
Tan L, Batista J, Bajorath J. Computational methodologies for compound database searching that utilize experimental protein-ligand interaction information. Chem Biol Drug Des 2010; 76:191-200. [PMID: 20636330 DOI: 10.1111/j.1747-0285.2010.01007.x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Ligand- and target structure-based methods are widely used in virtual screening, but there is currently no methodology available that fully integrates these different approaches. Herein, we provide an overview of various attempts that have been made to combine ligand- and structure-based computational screening methods. We then review different types of approaches that utilize protein-ligand interaction information for database screening and filtering. Interaction-based approaches make use of a variety of methodological concepts including pharmacophore modeling and direct or indirect encoding of protein-ligand interactions in fingerprint formats. These interaction-based methods have been successfully applied to tackle different tasks related to virtual screening including postprocessing of docking poses, prioritization of binding modes, selectivity analysis, or similarity searching. Furthermore, we discuss the recently developed interacting fragment approach that indirectly incorporates 3D interaction information into 2D similarity searching and bridges between ligand- and structure-based methods.
Collapse
Affiliation(s)
- Lu Tan
- Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstr. 2, D-53113 Bonn, Germany
| | | | | |
Collapse
|