Insight parameter drug design for human β-tryptase inhibition integrated molecular docking, QSAR, molecular dynamics simulation, and pharmacophore modelling studies of α-keto-[1,2,4]-oxadiazoles
Dengue hemorrhagic fever (DHF) is life-threatening severe dengue with a hallmark of vascular leakage. A mast cell protease, β-tryptase, has been found to promote vascular leakage in DHF patients, which could be a potential target for the treatment of DHF. This study aims to develop a theoretical bac...
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Taylor and Francis Group
2023
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author | Yu, Chai Xin Tan, Jian Wei Rullah, Kamal Imran, Syahrul Tham, Chau Ling |
author_facet | Yu, Chai Xin Tan, Jian Wei Rullah, Kamal Imran, Syahrul Tham, Chau Ling |
author_sort | Yu, Chai Xin |
collection | UPM |
description | Dengue hemorrhagic fever (DHF) is life-threatening severe dengue with a hallmark of vascular leakage. A mast cell protease, β-tryptase, has been found to promote vascular leakage in DHF patients, which could be a potential target for the treatment of DHF. This study aims to develop a theoretical background for the design and selection of β-tryptase inhibitors through these approaches: two-dimensional quantitative structure-activity relationships (2D-QSAR) study, molecular docking analysis, molecular dynamics (MD) simulation, and structure-based pharmacophore modelling (PM). A total of 34 a-keto-[1,2,3]-oxadiazoles scaffold-based compounds, obtained from a past study, were used to generate 2D-QSAR models by Genetic Function Approximation (GFA). The generated 2D-QSAR models were used to investigate the relationships between the molecular structure and the potency of β-tryptase inhibition. Molecular docking explores the binding affinities and binding interactions of the a-keto-[1,2,3]-oxadiazoles scaffold-based compounds with β-tryptase (PDB Code 4A6L) by the CDOCKER tool in Discovery Studio. In addition, MD simulation was performed using GROMACS on the docked complex of the reported most active compound, compound 11e, to study the binding mechanism of the compound towards β-tryptase. Finally, a structure-based pharmacophore model was generated from the same docked complex to identify the important features that contribute positively to the inhibitory activity of the compound towards β-tryptase. The best 2D-QSAR model has demonstrated statistically significant results through its r2, q2, and r2 (pred) values of 0.9077, 0.733, and 0.8104, respectively. The docking results of compound 11e showed lower CDOCKER energy than the 4A6L co-crystallised ligand, indicating good binding affinity. Furthermore, compound 11e has a similar binding pattern as the 4A6L co-crystallised ligand, which involves the binding of active residues such as Asp207, SER208, and GLY237. The MD simulation shows that the 4A6L-compound 11e complex has RMSD below 2Å throughout the 100ns of simulation, indicating that the docked complex is stable. Besides, MD simulation showed that the inhibitory potency of compound 11e is contributed by hydrogen bonding with 4A6L active site residues, which are ASP207, SER208, and GLY237. The best pharmacophore model identified features that contribute to the inhibitory potency of a compound, which included hydrogen bond acceptor, ionic interaction, hydrophobic interaction, and aromatic ring. This study has fundamentally supplied valuable insight and knowledge for developing novel chemical compounds with improved inhibitory ability against human β-tryptase. |
first_indexed | 2024-09-25T03:42:14Z |
format | Article |
id | upm.eprints-109433 |
institution | Universiti Putra Malaysia |
last_indexed | 2024-09-25T03:42:14Z |
publishDate | 2023 |
publisher | Taylor and Francis Group |
record_format | dspace |
spelling | upm.eprints-1094332024-08-05T02:12:50Z http://psasir.upm.edu.my/id/eprint/109433/ Insight parameter drug design for human β-tryptase inhibition integrated molecular docking, QSAR, molecular dynamics simulation, and pharmacophore modelling studies of α-keto-[1,2,4]-oxadiazoles Yu, Chai Xin Tan, Jian Wei Rullah, Kamal Imran, Syahrul Tham, Chau Ling Dengue hemorrhagic fever (DHF) is life-threatening severe dengue with a hallmark of vascular leakage. A mast cell protease, β-tryptase, has been found to promote vascular leakage in DHF patients, which could be a potential target for the treatment of DHF. This study aims to develop a theoretical background for the design and selection of β-tryptase inhibitors through these approaches: two-dimensional quantitative structure-activity relationships (2D-QSAR) study, molecular docking analysis, molecular dynamics (MD) simulation, and structure-based pharmacophore modelling (PM). A total of 34 a-keto-[1,2,3]-oxadiazoles scaffold-based compounds, obtained from a past study, were used to generate 2D-QSAR models by Genetic Function Approximation (GFA). The generated 2D-QSAR models were used to investigate the relationships between the molecular structure and the potency of β-tryptase inhibition. Molecular docking explores the binding affinities and binding interactions of the a-keto-[1,2,3]-oxadiazoles scaffold-based compounds with β-tryptase (PDB Code 4A6L) by the CDOCKER tool in Discovery Studio. In addition, MD simulation was performed using GROMACS on the docked complex of the reported most active compound, compound 11e, to study the binding mechanism of the compound towards β-tryptase. Finally, a structure-based pharmacophore model was generated from the same docked complex to identify the important features that contribute positively to the inhibitory activity of the compound towards β-tryptase. The best 2D-QSAR model has demonstrated statistically significant results through its r2, q2, and r2 (pred) values of 0.9077, 0.733, and 0.8104, respectively. The docking results of compound 11e showed lower CDOCKER energy than the 4A6L co-crystallised ligand, indicating good binding affinity. Furthermore, compound 11e has a similar binding pattern as the 4A6L co-crystallised ligand, which involves the binding of active residues such as Asp207, SER208, and GLY237. The MD simulation shows that the 4A6L-compound 11e complex has RMSD below 2Å throughout the 100ns of simulation, indicating that the docked complex is stable. Besides, MD simulation showed that the inhibitory potency of compound 11e is contributed by hydrogen bonding with 4A6L active site residues, which are ASP207, SER208, and GLY237. The best pharmacophore model identified features that contribute to the inhibitory potency of a compound, which included hydrogen bond acceptor, ionic interaction, hydrophobic interaction, and aromatic ring. This study has fundamentally supplied valuable insight and knowledge for developing novel chemical compounds with improved inhibitory ability against human β-tryptase. Taylor and Francis Group 2023-01-29 Article PeerReviewed Yu, Chai Xin and Tan, Jian Wei and Rullah, Kamal and Imran, Syahrul and Tham, Chau Ling (2023) Insight parameter drug design for human β-tryptase inhibition integrated molecular docking, QSAR, molecular dynamics simulation, and pharmacophore modelling studies of α-keto-[1,2,4]-oxadiazoles. Journal of Biomolecular Structure and Dynamics, 41 (22). pp. 12978-12996. ISSN 0739-1102; ESSN: 1538-0254 https://www.tandfonline.com/doi/full/10.1080/07391102.2023.2171131 10.1080/07391102.2023.2171131 |
spellingShingle | Yu, Chai Xin Tan, Jian Wei Rullah, Kamal Imran, Syahrul Tham, Chau Ling Insight parameter drug design for human β-tryptase inhibition integrated molecular docking, QSAR, molecular dynamics simulation, and pharmacophore modelling studies of α-keto-[1,2,4]-oxadiazoles |
title | Insight parameter drug design for human β-tryptase inhibition integrated molecular docking, QSAR, molecular dynamics simulation, and pharmacophore modelling studies of α-keto-[1,2,4]-oxadiazoles |
title_full | Insight parameter drug design for human β-tryptase inhibition integrated molecular docking, QSAR, molecular dynamics simulation, and pharmacophore modelling studies of α-keto-[1,2,4]-oxadiazoles |
title_fullStr | Insight parameter drug design for human β-tryptase inhibition integrated molecular docking, QSAR, molecular dynamics simulation, and pharmacophore modelling studies of α-keto-[1,2,4]-oxadiazoles |
title_full_unstemmed | Insight parameter drug design for human β-tryptase inhibition integrated molecular docking, QSAR, molecular dynamics simulation, and pharmacophore modelling studies of α-keto-[1,2,4]-oxadiazoles |
title_short | Insight parameter drug design for human β-tryptase inhibition integrated molecular docking, QSAR, molecular dynamics simulation, and pharmacophore modelling studies of α-keto-[1,2,4]-oxadiazoles |
title_sort | insight parameter drug design for human β tryptase inhibition integrated molecular docking qsar molecular dynamics simulation and pharmacophore modelling studies of α keto 1 2 4 oxadiazoles |
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