Inhibitory Activity of Myricetin and Chlorogenic Acid against Dengue Virus NS2b/NS3 Protease through In Silico Approaches

Authors

  • Nirajana Dhoju Central Department of Physics, Institute of Science and Technology, Tribhuvan University, Kirtipur, Kathmandu, Nepal
  • Tika Ram Lamichhane Central Department of Physics, Institute of Science and Technology, Tribhuvan University, Kirtipur, Kathmandu, Nepal https://orcid.org/0000-0002-3422-0808

DOI:

https://doi.org/10.3126/jist.v29i2.67919

Keywords:

Dengue virus, myricetin, chlorogenic acid, molecular docking, molecular dynamics, NS2B/NS3 protease

Abstract

The resurgence of dengue virus (DENV) infection poses a significant global health threat, exacerbated by urbanization and climate change. Flaviviridae family virus, DENV infection can be asymptomatic in some cases while it can be lethal in others. More serious symptoms include dengue hemorrhagic fever, dengue shock syndrome, and liver damage. Despite these worrying features, no specific drug has been approved till now. People have been relying on antipyretic drugs only. This study explores the inhibition potential of natural compounds myricetin and chlorogenic acid against DENV using computational analysis. Molecular docking and molecular dynamics simulations were employed to assess their inhibitory effects on a crucial enzyme NS2B/NS3 protease of DENV. NS2B/NS3 protease, highly conserved in the DENV serotypes, plays a vital role in viral replication and it acts as an excellent drug target. The phytochemicals myricetin (MYR) and chlorogenic acid (CGA) have docking scores of -7.9 kcal/mol and -7.1 kcal/mol targeting NS2B/NS3 protease, respectively. By analyzing RMSD, RMSF, RG, SASA and H-bonding, MYR possesses greater compactness and stability in comparison with quercetin and CGA throughout the MD simulation. The NS2B/NS3 protease in complex with MYR and CGA shows end-state MM/GBSA free energy of -25.053.19 kcal/mol and -20.22±3.02 kcal/mol, respectively. ADMET analysis shows that the proposed compounds offer good bioavailability scores. CGA with a higher LD50 value (5000 mg/kg) appears in predicted toxicity class 5 whereas quercetin and MYR with lower LD50 value (159 mg/kg) appear in the toxicity class 3. The results suggest that CGA and MYR exhibit strong binding affinities and stable interactions, highlighting their potential as DENV inhibitors. Further experimental verifications will be necessary to determine the effectiveness of such drug candidates against DENV.

Downloads

Download data is not yet available.
Abstract
0
PDF
0

References

Acharya, A., Khanal, M., Maharjan, R., Gyawali, K., Luitel, B. R., Adhikari, R., Mulmi, D. D., Lamichhane T.R. & Lamichhane, H. P. (2024). Quantum chemical calculations on calcium oxalate and dolichin A and their binding efficacy to lactoferrin: An in silico study using DFT, molecular docking, and molecular dynamics simulations. AIMS Biophysics, 11(2), 142-165. https://doi.org/10.3934/biophy.2024010

Azeem, M., Hanif, M., Mahmood, K., Ameer, N., Chughtai, F. R. S., & Abid, U. (2023). An insight into anticancer, antioxidant, antimicrobial, antidiabetic and anti-inflammatory effects of quercetin: A review. Polymer Bulletin, 80(1), 241-262. https://doi.org/10.1007/s00289-022-04091-8

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(W1), W257-W263. https://doi.org/10.1093/nar/gky318

Basnet, S., Ghimire, M. P., Lamichhane, T. R., Adhikari, R., & Adhikari, A. (2023). Identification of potential human pancreatic α-amylase inhibitors from natural products by molecular docking, MM/GBSA calculations, MD simulations, and ADMET analysis. Plos one, 18(3), e0275765. https://doi.org/10.1371/journal.pone.0275765

Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., Weissig, H., ... & Bourne, P. E. (2000). The protein data bank. Nucleic Acids Research, 28(1), 235-242. https://doi.org/10.1093/nar/28.1.235

Brandão, G. C., Kroon, E. G., Souza, D. E., Filho, J. D. S., & Oliveira, A. B. (2013). Chemistry and antiviral activity of Arrabidaea pulchra (Bignoniaceae). Molecules, 18(8), 9919-9932. https://doi.org/10.3390/molecules18089919

Cheng, F., Li, W., Zhou, Y., Shen, J., Wu, Z., Liu, G., ... & Tang, Y. (2012). admetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties. Journal of Chemical Information and Modeling, 52(11), 3099-3105. https://doi.org/10.1021/ci300367a

Chhetri, S. P., Bhandari, V. S., Maharjan, R., & Lamichhane, T. R. (2024). Identification of lead inhibitors for 3CLpro of SARS-CoV-2 target using machine learning based virtual screening, ADMET analysis, molecular docking and molecular dynamics simulations. RSC advances, 14(40), 29683-29692. https://doi.org/10.1039/D4RA04502E

Daina, A., Michielin, O., & Zoete, V. (2017). SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific reports, 7(1), 42717. https://doi.org/10.1038/srep42717

Du, X., Li, Y., Xia, Y. L., Ai, S. M., Liang, J., Sang, P., ... & Liu, S. Q. (2016). Insights into protein–ligand interactions: mechanisms, models, and methods. International Journal of Molecular Sciences, 17(2), 144.

Erbel, P., Schiering, N., D'Arcy, A., Renatus, M., Kroemer, M., Lim, S. P., ... & Hommel, U. (2006). Structural basis for the activation of flaviviral NS3 proteases from dengue and West Nile virus. Nature Structural & Molecular Biology, 13(4), 372-373. https://doi.org/10.1038/nsmb1073

Faria, W. C. S., da Silva, A. A., Veggi, N., Kawashita, N. H., de França Lemes, S. A., de Barros, W. M., ... & Bragagnolo, N. (2020). Acute and subacute oral toxicity assessment of dry encapsulated and non-encapsulated green coffee fruit extracts. Journal of Food and Drug Analysis, 28(2), 337. https://doi.org/10.38212/2224-6614.1067

Genheden, S., & Ryde, U. (2015). The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opinion on Drug Discovery, 10(5), 449-461. https://doi.org/10.1517/17460441.2015.1032936

Gubler, D. J. (2006, August). Dengue/dengue haemorrhagic fever: history and current status. In New treatment strategies for dengue and other flaviviral diseases: novartis foundation symposium 277 (pp. 3-22). Chichester, UK: John Wiley & Sons, Ltd. https://doi.org/10.1002/0470058005.ch2

Gupta, A., Atanasov, A. G., Li, Y., Kumar, N., & Bishayee, A. (2022). Chlorogenic acid for cancer prevention and therapy: Current status on efficacy and mechanisms of action. Pharmacological Research, 186, 106505.https://doi.org/10.1016/j.phrs.2022.106505

Gyawali, K., Maharjan, R., Acharya, A., Khanal, M., Ghimire, M. P., & Lamichhane, T. R. (2024). Identification of catechin as main protease inhibitor of SARS-CoV-2 Omicron variant using molecular docking, molecular dynamics, PCA, DCCM, MM/GBSA and ADMET profiling. Natural Product Research, 1-8. https://doi.org/10.1080/14786419.2024.2421907

Halstead, S. B. (1989). Antibody, macrophages, dengue virus infection, shock, and hemorrhage: a pathogenetic cascade. Reviews of Infectious Diseases, 11(Supplement_4), S830-S839. https://doi.org/10.1093/clinids/11.Supplement_4.S830

Holmes, E. C., & Burch, S. S. (2000). The causes and consequences of genetic variation in dengue virus. Trends in microbiology, 8(2), 74-77. https://doi.org/10.1016/S0966-842X(99)01669-8

Huang, J., & MacKerell Jr, A. D. (2013). CHARMM36 all‐atom additive protein force field: Validation based on comparison to NMR data. Journal of Computational Chemistry, 34(25), 2135-2145. https://doi.org/10.1002/jcc.23354

Huey, R., Morris, G. M., & Forli, S. (2012). Using AutoDock 4 and AutoDock vina with AutoDockTools: a tutorial. The Scripps Research Institute Molecular Graphics Laboratory, 10550(92037), 1000.

Khanal, M., Acharya, A., Maharjan, R., Gyawali, K., Adhikari, R., Mulmi, D. D., Lamichhane T.R. & Lamichhane, H. P. (2024). Identification of potent inhibitors of HDAC2 from herbal products for the treatment of colon cancer: Molecular docking, molecular dynamics simulation, MM/GBSA calculations, DFT studies, and pharmacokinetic analysis. PloS one, 19(7), e0307501. https://doi.org/10.1371/journal.pone.0307501

Kuhn, R. J., Zhang, W., Rossmann, M. G., Pletnev, S. V., Corver, J., Lenches, E., ... & Strauss, J. H. (2002). Structure of dengue virus: implications for flavivirus organization, maturation, and fusion. Cell, 108(5), 717-725. https://doi.org/10.1016/S0092-8674(02)00660-8

Lamichhane, T.R., & Ghimire, M.P. (2021). Evaluation of SARS-CoV-2 main protease and inhibitor interactions using dihedral angle distributions and radial distribution function, Heliyon 7, e08220. https://doi.org/10.1016/j.heliyon.2021.e08220

Lee, B., & Richards, F. M. (1971). The interpretation of protein structures: estimation of static accessibility. Journal of molecular biology, 55(3), 379-IN4.

Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (2012). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 64, 4-17. https://doi.org/10.1016/j.addr.2012.09.019

Maharjan, R., Gyawali, K., Acharya, A., Khanal, M., Ghimire, M. P., & Lamichhane, T. R. (2024). Artemisinin derivatives as potential drug candidates against Mycobacterium tuberculosis: insights from molecular docking, MD simulations, PCA, MM/GBSA and ADMET analysis. Molecular Simulation, 50(11)1-12. https://doi.org/10.1080/08927022.2024.2346525

Morris, G. M., Huey, R., Lindstrom, W., Sanner, M. F., Belew, R. K., Goodsell, D. S., & Olson, A. J. (2009). AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. Journal of Computational Chemistry, 30(16), 2785-2791. https://doi.org/10.1002/jcc.21256

Mukhtar, M., & Khan, H. A. (2023). Exploring the inhibitory potential of Nigella sativa against dengue virus NS2B/NS3 protease and NS5 polymerase using computational approaches. RSC advances, 13(27), 18306-18322. https://doi.org/10.1039/D3RA02613B

Nguyen, V., Taine, E. G., Meng, D., Cui, T., & Tan, W. (2024). Chlorogenic Acid: A Systematic Review on the Biological Functions, Mechanistic Actions, and Therapeutic Potentials. Nutrients, 16(7), 924.https://doi.org/10.3390/nu16070924

Norahmad, N. A., Mohd Abd Razak, M. R., Mohmad Misnan, N., Md Jelas, N. H., Sastu, U. R., Muhammad, A., ... & Syed Mohamed, A. F. (2019). Effect of freeze-dried Carica papaya leaf juice on inflammatory cytokines production during dengue virus infection in AG129 mice. BMC Complementary and Alternative Medicine, 19, 1-10. https://doi.org/10.1186/s12906-019-2438-3

Obi, J. O., Gutiérrez-Barbosa, H., Chua, J. V., & Deredge, D. J. (2021). Current trends and limitations in dengue antiviral research. Tropical Medicine and Infectious Disease, 6(4), 180. https://doi.org/10.3390/tropicalmed6040180

Padilla-s, L., Rodríguez, A., Gonzales, M. M., Gallego-g, J. C., & Castaño-o, J. C. (2014). Inhibitory effects of curcumin on dengue virus type 2-infected cells in vitro. Archives of Virology, 159, 573-579. https://doi.org/10.1007/s00705-013-1849-6

Panya, A., Yongpitakwattana, P., Budchart, P., Sawasdee, N., Krobthong, S., Paemanee, A., ... & Yenchitsomanus, P. T. (2019). Novel bioactive peptides demonstrating anti‐dengue virus activity isolated from the Asian medicinal plant Acacia catechu. Chemical Biology &Drug Design, 93(2), 100-109. https://doi.org/10.1111/cbdd.13400

Perera, R., & Kuhn, R. J. (2008). Structural proteomics of dengue virus. Current opinion in microbiology, 11(4), 369-377. https://doi.org/10.1016/j.mib.2008.06.004

Pintado Silva, J., & Fernandez-Sesma, A. (2023). Challenges on the development of a dengue vaccine: a comprehensive review of the state of the art. Journal of General Virology, 104(3), 001831. https://doi.org/10.1099/jgv.0.001831

Shabir, I., Kumar Pandey, V., Shams, R., Dar, A. H., Dash, K. K., Khan, S. A., ... & Pandiselvam, R. (2022). Promising bioactive properties of quercetin for potential food applications and health benefits: A review. Frontiers in Nutrition, 9, 999752. https://doi.org/10.3389/fnut.2022.999752

Tian, W., Chen, C., Lei, X., Zhao, J., & Liang, J. (2018). CASTp 3.0: computed atlas of surface topography of proteins. Nucleic Acids Research, 46(W1), W363-W367. https://doi.org/10.1093/nar/gky473

Valdés-Tresanco, M. S., Valdés-Tresanco, M. E., Valiente, P. A., & Moreno, E. (2021). gmx_MMPBSA: a new tool to perform end-state free energy calculations with GROMACS. Journal of Chemical Theory and Computation, 17(10), 6281-6291. https://doi.org/10.1021/acs.jctc.1c00645

Van Der Spoel, D., Lindahl, E., Hess, B., Groenhof, G., Mark, A. E., & Berendsen, H. J. (2005). GROMACS: fast, flexible, and free. Journal of Computational Chemistry, 26(16), 1701-1718. https://doi.org/10.1002/jcc.20291

Wahaab, A., Mustafa, B. E., Hameed, M., Stevenson, N. J., Anwar, M. N., Liu, K., ... & Ma, Z. (2021). Potential role of flavivirus NS2B-NS3 proteases in viral pathogenesis and anti-flavivirus drug discovery employing animal cells and models: a review. Viruses, 14(1), 44. https://doi.org/10.3390/v14010044

Watanabe, T., Arai, Y., Mitsui, Y., Kusaura, T., Okawa, W., Kajihara, Y., & Saito, I. (2006). The blood pressure-lowering effect and safety of chlorogenic acid from green coffee bean extract in essential hypertension. Clinical and Experimental Hypertension, 28(5), 439-449. https://doi.org/10.1080/10641960600798655

Yusof, R., Clum, S., Wetzel, M., Murthy, H. K., & Padmanabhan, R. (2000). Purified NS2B/NS3 serine protease of dengue virus type 2 exhibits cofactor NS2B dependence for cleavage of substrates with dibasic amino acids in vitro. Journal of Biological Chemistry, 275(14), 9963-9969. https://doi.org/10.1074/jbc.275.14.996

Zheng, W., Wu, H., Wang, T., Zhan, S., & Liu, X. (2021). Quercetin for COVID-19 and DENGUE co-infection: a potential therapeutic strategy of targeting critical host signal pathways triggered by SARS-CoV-2 and DENV. Briefings in Bioinformatics, 22(6), bbab199. https://doi.org/10.1093/bib/bbab199

Zoete, V., Cuendet, M. A., Grosdidier, A., & Michielin, O. (2011). SwissParam: a fast force field generation tool for small organic molecules. Journal of Computational Chemistry, 32(11), 2359-2368. https://doi.org/10.1002/jcc.21816

Downloads

Published

2024-12-22

How to Cite

Dhoju, N., & Lamichhane, T. R. (2024). Inhibitory Activity of Myricetin and Chlorogenic Acid against Dengue Virus NS2b/NS3 Protease through In Silico Approaches. Journal of Institute of Science and Technology, 29(2), 95–108. https://doi.org/10.3126/jist.v29i2.67919

Issue

Vol. 29 No. 2 (2024)

Section

Research Articles

License

Copyright (c) 2024 Institute of Science and Technology, T.U.

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

The views and interpretations in this journal are those of the author(s). They are not attributable to the Institute of Science and Technology, T.U. and do not imply the expression of any opinion concerning the legal status of any country, territory, city, area of its authorities, or concerning the delimitation of its frontiers of boundaries.

The copyright of the articles is held by the Institute of Science and Technology, T.U.