Molecular docking study of modified isoniazid compounds on mycolic acid synthase in the cell wall of mycobacterium tuberculosis

Jordi  Buannata; Bambang Wijianto; Ihsanul  Arief

doi:10.29303/aca.v7i2.173

Molecular docking study of modified isoniazid compounds on mycolic acid synthase in the cell wall of mycobacterium tuberculosis

Authors

Jordi Buannata , Bambang Wijianto , Ihsanul Arief

DOI:

10.29303/aca.v7i2.173

Published:

2024-10-31

Issue:

Vol. 7 No. 2 (2024)

Keywords:

molecular docking, Antituberculosis, Modified isoniazid compounds, Autodock VINA, ProTox-II

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Buannata, J. ., Wijianto, B., & Arief, I. . (2024). Molecular docking study of modified isoniazid compounds on mycolic acid synthase in the cell wall of mycobacterium tuberculosis. Acta Chimica Asiana, 7(2), 471–477. https://doi.org/10.29303/aca.v7i2.173

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Abstract

Using the isoniazid in antituberculosis therapy can lead to mutations in the KatG and inhA genes of Mycobacterium tuberculosis, resulting in the development of resistance and necessitating modifications to the isoniazid compound. This study aims to assess the potential and level of toxicity of modified compounds, namely 4-pyridine carboxylic acid, pyridine aldehyde, and methyl pyridine, on the mycolic acid receptor through a molecular docking approach. PyRx was employed for the docking process using a protocol with an exhaustiveness of 106 and a center grid box at X=42.424, Y=22.4321, and Z=46.6391. Additionally, the ProTox-II website was used to determine the toxicity level of the test compounds. The results obtained from this research consist of the respective affinity values of the test compounds: -6, -5.4, and -5.2 kcal/mol. The toxicity levels of the test compounds are as follows: class 5, class 4, and class 4. All test compounds interact with amino acids on the target protein, specifically with residue numbers Histidine (HIS A:8), Phenylalanine (PHE A:142) through hydrogen bonding, Leucine (LEU A:95) through pi-Sigma (π) bonding, and Valine (VAL A:12) through pi-Alkyl (π) bonding. In conclusion, the 4-pyridine carboxylic acid compound exhibits potential as a promising drug candidate but comes with a high level of toxicity

References

Venkatappa, T., Shen, D., Ayala, A., Li, R., Sorri, Y., Punnoose, R., Katz, D. (2023).: Association of Mycobacterium tuberculosis infection test results with risk factors for tuberculosis transmission. Journal of Clinical Tuberculosis and Other Mycobacterial Diseases. 33, 100386. https://doi.org/10.1016/j.jctube.2023.100386.

Sampiron, E.G., Calsavara, L.L., Baldin, V.P., Montaholi, D.C., Leme, A.L.D., Namba, D.Y., Alves Olher, V.G., Caleffi-Ferraciolli, K.R., Cardoso, R.F., Siqueira, V.L.D., Vandresen, F., Scodro, R.B. de L. (2023). Isoniazid-N-acylhydrazones as promising compounds for the anti-tuberculosis treatment. Tuberculosis. 141, 102363. https://doi.org/10.1016/j.tube.2023.102363

Chan, C.-Y., Au-Yeang, C., Yew, W.-W., Hui, M., Cheng, A.F.B. (2001). Postantibiotic Effects of Antituberculosis Agents Alone and in Combination. Antimicrob Agents Chemother. 45, 3631–3634. https://doi.org/10.1128/AAC.45.12.3631-3634.2001

Wang Kun, Deng Yimin, Cui Xujie, Chen Mengli, Ou Yanzhe, Li Danting, Guo Minhao, Li Weihui. (2023). PatA Regulates Isoniazid Resistance by Mediating Mycolic Acid Synthesis and Controls Biofilm Formation by Affecting Lipid Synthesis in Mycobacteria. Microbiology Spectrum. 11, e00928-23. https://doi.org/10.1128/spectrum.00928-23

North, E., Jackson, M., Lee, R. (2013). New Approaches to Target the Mycolic Acid Biosynthesis Pathway for the Development of Tuberculosis Therapeutics. CPD. 20, 4357–4378. https://doi.org/10.2174/1381612819666131118203641

Holzheimer, M., Buter, J., Minnaard, A.J. (2021). Chemical Synthesis of Cell Wall Constituents of Mycobacterium tuberculosis. Chem. Rev. 121, 9554–9643. https://doi.org/10.1021/acs.chemrev.1c00043.

PaweŁczyk Jakub, Kremer Laurent. (2014). The Molecular Genetics of Mycolic Acid Biosynthesis. Microbiology Spectrum. 2, 10.1128/microbiolspec.mgm2-0003–2013. https://doi.org/10.1128/microbiolspec.mgm2-0003-2013

Takayama, K., Wang, C., Besra, G.S. (2005). Pathway to Synthesis and Processing of Mycolic Acids in Mycobacterium tuberculosis. Clin Microbiol Rev. 18, 81–101. https://doi.org/10.1128/CMR.18.1.81-101.2005.

Dyas, R.A.A., Wijianto, B., Ih, H. (2023). Docking studies for screening antibacterial compounds of Red Jeringau (Acorus calamus L.) using Shigella flexneri protein as a model system. Acta.Chim.Asiana. 6, 343–350. https://doi.org/10.29303/aca.v6i2.161

Budiarto, D., Wijianto, B., Ih, H. (2023). Study of Anthocyanin Molecule Blocking as Anti-Hypertensive through the Pathway of the Renin-Angiotensin-Aldosterone System (RAAS). Indo. J. Chem. Res. 11, 49–58. https://doi.org/10.30598//ijcr.2023.11-bud

Wijianto, B., Ritmaleni, R., Hari, P., Arief, N. (2020). In silico and in vitro anti-inflammatory evaluation of 2,6-bis-(3’-ethoxy, 4’-hydroxybenzylidene)-cyclohexanone, 2,6-bis-(3’-Bromo,4’-methoxybenzylidene)-cyclohexanone, and 2,6-bis- (3’,4’-dimethoxybenzylidene)-cyclohexanone. J app pharm sci. 10, 99–106. https://doi.org/10.7324/JAPS.2020.10613.

Wijianto, B., . R., Purnomo, H., Nurrochmad, A. (2019). In silico and in vitro assay of HGV analogue as antibacterial. Int J Pharm Pharm Sci. 78–85. https://doi.org/10.22159/ijpps.2019v11i3.30581.

C Malau, N. D., & Azzahra, S. F. (2020). Analysis docking of plasmodium falciparum enoyl acyl carrier protein reductase (pfenr) with organic compunds from virtual screening of herbal database. Acta Chimica Asiana, 3(1), 127-134. Dyas, R. A. A., Wijianto, B., & Hariyanto, I. H. (2023). Docking studies for screening antibacterial compounds of Red Jeringau (Acorus calamus L.) using Shigella flexneri protein as a model system. Acta Chimica Asiana, 6(2), 343-350. https://doi.org/10.4081/jphia.2023.2532

Banerjee, P., Eckert, A.O., Schrey, A.K., Preissner, R. (2018). ProTox-II: a webserver for the prediction of toxicity of chemicals. Nucleic Acids Research. 46, W257–W263. https://doi.org/10.1093/nar/gky318

Cavasotto, C.N., Scardino, V. (2022). Machine Learning Toxicity Prediction: Latest Advances by Toxicity End Point. ACS Omega. 7, 47536–47546. https://doi.org/10.1021/acsomega.2c05693

Yang, S., Kar, S. (2023). Application of artificial intelligence and machine learning in early detection of adverse drug reactions (ADRs) and drug-induced toxicity. Artificial Intelligence Chemistry. 1, 100011. https://doi.org/10.1016/j.aichem.2023.100011

Pires, D.E.V., Blundell, T.L., Ascher, D.B. (2015). pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures. J. Med. Chem. 58, 4066–4072. https://doi.org/10.1021/acs.jmedchem.5b00104

Wade, A.D., Huggins, D.J. (2020). Identification of Optimal Ligand Growth Vectors Using an Alchemical Free-Energy Method. J. Chem. Inf. Model. 60, 5580–5594. https://doi.org/10.1021/acs.jcim.0c00610

Du, X., Li, Y., Xia, Y.-L., Ai, S.-M., Liang, J., Sang, P., Ji, X.-L., Liu, S.-Q. (2016). Insights into Protein–Ligand Interactions: Mechanisms, Models, and Methods. IJMS. 17, 144. https://doi.org/10.3390/ijms17020144

Decherchi, S., Cavalli, A. (2020). Thermodynamics and Kinetics of Drug-Target Binding by Molecular Simulation. Chem. Rev. 120, 12788–12833. https://doi.org/10.1021/acs.chemrev.0c00534

Kim, S., Thiessen, P.A., Bolton, E.E., Chen, J., Fu, G., Gindulyte, A., Han, L., He, J., He, S., Shoemaker, B.A., Wang, J., Yu, B., Zhang, J., Bryant, S.H. (2016). PubChem Substance and Compound databases. Nucleic Acids Res. 44, D1202–D1213. https://doi.org/10.1093/nar/gkv951

Kim, S., Chen, J., Cheng, T., Gindulyte, A., He, J., He, S., Li, Q., Shoemaker, B.A., Thiessen, P.A., Yu, B., Zaslavsky, L., Zhang, J., Bolton, E.E. (2023). PubChem 2023 update. Nucleic Acids Research. 51, D1373–D1380. https://doi.org/10.1093/nar/gkac956

Tanbin, S., Ahmad Fuad, F.A., Abdul Hamid, A.A. (2020). Virtual Screening for Potential Inhibitors of Human Hexokinase II for the Development of Anti-Dengue Therapeutics. BioTech. 10, 1. https://doi.org/10.3390/biotech10010001

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Molecular docking study of modified isoniazid compounds on mycolic acid synthase in the cell wall of mycobacterium tuberculosis

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