Identification of novel inhibitors of Neisseria gonorrhoeae MurI using homology modeling, structure-based pharmacophore, molecular docking, and molecular dynamics simulation-based approach
Identification of novel inhibitors of Neisseria gonorrhoeae MurI using homology modeling, structure-based pharmacophore, molecular docking, and molecular dynamics simulation-based approach
MurI is one of the most significant role players in the biosynthesis of the peptidoglycan layer in Neisseria gonorrhoeae (Ng). We attempted to highlight the structural and functional relationship between Ng-MurI and D-glutamate to design novel molecules targeting this interaction. The three-dimensional (3D) model of the protein was constructed by homology modeling and the quality and consistency of generated model were assessed. The binding site of the protein was identified by molecular docking studies and a pharmacophore was identified using the interactions of the control ligand. The structure-based pharmacophore model was validated and employed for high-throughput virtual screening and molecular docking to identify novel Ng-MurI inhibitors. Finally, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with the substrate glutamate and novel molecules facilitated us to confirm the stability of the protein-ligand docked complexes. The 100 ns MD simulations of the potential lead compounds with protein confirmed that the modeled complexes were stable. This study identifies novel potential compounds with good fitness and docking scores, which made the interactions of biological significance within the protein active site. Hence, the identified compounds may act as new leads to design and develop Ng-MurI inhibitors. Communicated by Ramaswamy H. Sarma.
7433-7446
Kant, Ravi
7701bda0-8d8b-4c7b-b988-75f6da612e2a
Jha, Prakash
4358528c-39ba-491e-8f9c-7b312c55cd74
Saluja, Daman
c632b624-e87e-4d82-a045-5e3af0dd8439
Chopra, Madhu
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Kant, Ravi
7701bda0-8d8b-4c7b-b988-75f6da612e2a
Jha, Prakash
4358528c-39ba-491e-8f9c-7b312c55cd74
Saluja, Daman
c632b624-e87e-4d82-a045-5e3af0dd8439
Chopra, Madhu
a7faf3c3-200c-42fd-991c-77a03de223fd
Kant, Ravi, Jha, Prakash, Saluja, Daman and Chopra, Madhu
(2022)
Identification of novel inhibitors of Neisseria gonorrhoeae MurI using homology modeling, structure-based pharmacophore, molecular docking, and molecular dynamics simulation-based approach.
Journal of Biomolecular Structure and Dynamics, 41 (15), .
(doi:10.1080/07391102.2022.2121943).
Abstract
MurI is one of the most significant role players in the biosynthesis of the peptidoglycan layer in Neisseria gonorrhoeae (Ng). We attempted to highlight the structural and functional relationship between Ng-MurI and D-glutamate to design novel molecules targeting this interaction. The three-dimensional (3D) model of the protein was constructed by homology modeling and the quality and consistency of generated model were assessed. The binding site of the protein was identified by molecular docking studies and a pharmacophore was identified using the interactions of the control ligand. The structure-based pharmacophore model was validated and employed for high-throughput virtual screening and molecular docking to identify novel Ng-MurI inhibitors. Finally, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with the substrate glutamate and novel molecules facilitated us to confirm the stability of the protein-ligand docked complexes. The 100 ns MD simulations of the potential lead compounds with protein confirmed that the modeled complexes were stable. This study identifies novel potential compounds with good fitness and docking scores, which made the interactions of biological significance within the protein active site. Hence, the identified compounds may act as new leads to design and develop Ng-MurI inhibitors. Communicated by Ramaswamy H. Sarma.
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Accepted/In Press date: 1 September 2022
e-pub ahead of print date: 15 September 2022
Identifiers
Local EPrints ID: 501481
URI: http://eprints.soton.ac.uk/id/eprint/501481
ISSN: 0739-1102
PURE UUID: 8a9079d1-ce5f-4e64-b600-d3f6fcf1f33c
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Date deposited: 02 Jun 2025 16:54
Last modified: 03 Jun 2025 02:16
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Author:
Ravi Kant
Author:
Prakash Jha
Author:
Daman Saluja
Author:
Madhu Chopra
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