Quantitative Structure-Activity Relationship (QSAR) and Molecular Docking Analysis of α-Keto-[1,2,4]-oxadiazoles for Human B-II Tryptase Inhibition

Tan, Jian Wei (2021) Quantitative Structure-Activity Relationship (QSAR) and Molecular Docking Analysis of α-Keto-[1,2,4]-oxadiazoles for Human B-II Tryptase Inhibition. [Project Paper] (Submitted)

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Abstract

Dengue virus (DENV) infection is a threat to one-third of the global human population. Dengue may be asymptomatic or may cause a wide spectrum of diseases, ranging from a mild febrile illness to the most severe form, dengue hemorrhagic fever (DHF). DHF is potentially caused by mast cells (MCs)-derived proteases, particularly tryptase which helps to promote vascular permeability during DENV infection. Currently, the clinical management of DHF is relying on supportive treatments such as cautious fluid management. Although there are some potential anti-DENV drugs being tested in human clinical trials at different stages of development, there is still no specific drug for treating DHF. Hence, a potent inhibitor against β-II tryptase may be a potential treatment for DHF by reducing DENV-induced vascular leakage. Objectives: This study aimed to generate a 2D QSAR model of β-II tryptase to investigate its molecular structure versus biological activity relationship with previously published human β-II tryptase inhibitors, as well as to analyze the interactions between β-II tryptase and its inhibitors through molecular docking. Methodology: Thirty-five α-keto-[1,2,4]-oxadiazoles scaffold-based compounds based on literature search were selected. These compounds were used to generate 2D QSAR model of β-II tryptase by Generic Function Approximation (GFA) method. Molecular docking was performed between β-II tryptase (PDB CODE: 4A6L) and the selected 35 compounds by using CDOCKER tool in Discovery Studio. Results: The best 2D QSAR model was obtained with r2 value of 0.9077, q2 value of 0.733 and r2 (pred) value of 0.8104. For molecular docking, CDOCKER energy of the selected 35 compounds and their protein residues interaction were obtained. Besides, the binding pattern between the most active compound 11e and β-II tryptase was illustrated. Discussion: The contributions of 2D descriptors, ECFP_6, Num_Rings and CHI_V_1 were positive whereas CHI_3_P was negative in enhancing the activity, indicating that structural modifications can be done to improve the activity. The value of statistical parameters proves the robustness and significance of the model. Docking of the most active compound 11e showed lower CDOCKER energy than the co-crystallized β-II tryptase inhibitor, indicating a good binding affinity of 11e to the target protein. Docking of 11e into the binding site of β-II tryptase revealed a similar binding pattern as the cocrystallized β-II tryptase inhibitor by binding to the amide group of essential protein residues. Both 11e and the co-crystallized β-II tryptase inhibitor displayed conventional hydrogen bonding to Gly237 and Ser208. Conclusion: The GFA model study, together with molecular docking analysis, have fundamentally supplied valuable insight and knowledge for the development of novel chemical compounds with improved inhibitory ability against human βII tryptase.

Item Type:	Project Paper
Faculty:	Faculty of Medicine and Health Science
Depositing User:	Ms. Nor Safa'aton Saidin
Date Deposited:	22 Aug 2023 07:53
Last Modified:	22 Aug 2023 07:53
URI:	http://psaspb.upm.edu.my/id/eprint/1126

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