Abstract
Ebola virus (EBOV) prevails as a serious public health issue which infected at least 27,000 people and claimed the lives of about 11,000 people in the latest Ebola outbreak in 2014. Although the virus has been known for almost 40 years, currently there is no approved drug for this virus. Hence, the development of a new drug candidate for Ebola is required to anticipate the future outbreak that may happen. In this research, about 229,538 natural product (NP) compounds were retrieved and screened using a computational approach against EBOV nucleoprotein (NP). In the beginning, all NP compounds were screened throughout computational toxicity and druglikeness prediction tests, followed by pharmacophore-based virtual screening and molecular docking simulation to identify their binding affinity and molecular interaction in the RNA-binding groove of EBOV NP. All of the results were compared to 18β-glycyrrhetinic acid, the standard molecule of EBOV NP. In the end, about five NP compounds (UNPD213871, UNPD199951, UNPD124962, UNPD139843, and UNPD147202) were identified to have exciting activities against EBOV NP. Therefore, based on the results of this study, these compounds appeared to have potential inhibition activities against EBOV NP and can be proposed for further in silico and in vitro studies.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Dowall, S.D., et al.: Antiviral screening of multiple compounds against Ebola virus. Viruses 8, 1–17 (2016)
Sanchez, A., Kiley, M.P., Holloway, B.P., McCormick, J.B., Auperin, D.D.: The nucleoprotein gene of Ebola virus: Cloning, sequencing, and in vitro expression. Virology 170, 81–91 (1989)
Dong, S., et al.: Insight into the Ebola virus nucleocapsid assembly mechanism: crystal structure of Ebola virus nucleoprotein core domain at 1.8 Å resolution. Protein Cell 6, 351–362 (2015)
Lin, L.T., Hsu, W.C., Lin, C.C.: Antiviral natural products and herbal medicines. J. Tradit. Complement. Med. 4, 24–35 (2014)
Von Rintelen, K., Arida, E., Häuser, C.: A review of biodiversity-related issues and challenges in megadiverse Indonesia and other Southeast Asian countries. Res. Ideas Outcomes 3, 1–16 (2017)
Orbell, J., Coulepis, T.: Medicinal plants of Indonesia. Asia Pac. Biotech News 11, 726–743 (2007)
Harvey, A.L.: Natural products in drug discovery. Drug Discov. Today 13, 894–901 (2008)
Yang, S.-Y.: Pharmacophore modeling and applications in drug discovery: challenges and recent advances. Drug Discov. Today 15, 444–450 (2010)
Young, D.C.: Computational Drug Design: A Guide for Computational and Medicinal Chemists (2009)
Rizki, I.F., Nasution, M.A.F., Siregar, S., Ekawati, M.M., Tambunan, U.S.F.: Screening of Sonic Hedgehog (Shh) inhibitors in the Hedgehog signaling pathway from Traditional Chinese Medicine (TCM) database through structure-based pharmacophore design. In: Zhang, F., Cai, Z., Skums, P., Zhang, S. (eds.) ISBRA 2018. LNCS, vol. 10847, pp. 179–184. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-94968-0_16
Nasution, M.A.F., Toepak, E.P., Tambunan, U.S.F.: Flexible docking-based molecular dynamics simulation of natural product compounds and Ebola virus Nucleocapsid (EBOV NP): a computational approach to discover new drug for combating Ebola 19, 2011 (2018)
Sander, T., Freyss, J., Von Korff, M., Rufener, C.: DataWarrior: an open-source program for chemistry aware data visualization and analysis. J. Chem. Inf. Model. 55, 460–473 (2015)
Vilar, S., Cozza, G., Moro, S.: Medicinal chemistry and the molecular operating environment (MOE): application of QSAR and molecular docking to drug discovery. Curr. Top. Med. Chem. 8, 1555–1572 (2008)
Rose, P.W., et al.: The RCSB protein data bank: integrative view of protein, gene and 3D structural information. Nucl. Acids Res. gkw1000 (2016)
Gu, J., Gui, Y., Chen, L., Yuan, G., Lu, H.Z., Xu, X.: Use of natural products as chemical library for drug discovery and network pharmacology. PLoS ONE 8, 1–10 (2013)
Fu, X., et al.: Novel chemical ligands to Ebola virus and Marburg virus nucleoproteins identified by combining affinity mass spectrometry and metabolomics approaches. Sci. Rep. 6, 29680 (2016)
Acknowledgements
The research and the publication costs are entirely funded by Kementerian Riset, Teknologi, and Pendidikan Tinggi (Kemenristekdikti), Republic of Indonesia, through Hibah Penelitian Kerjasama Luar Negeri Tahun 2018 No: 538/UN2.R3.1/HKP.05.00/2018. All authors were responsible equally for writing the manuscript, conducting the experiments, as well as approving the final version of the manuscript. Finally, none conflict of interest is declared.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Nasution, M.A.F., Alkaff, A.H., Rizki, I.F., Bakri, R., Tambunan, U.S.F. (2020). Pharmacophore Modelling, Virtual Screening, and Molecular Docking Simulations of Natural Product Compounds as Potential Inhibitors of Ebola Virus Nucleoprotein. In: Raposo, M., Ribeiro, P., Sério, S., Staiano, A., Ciaramella, A. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2018. Lecture Notes in Computer Science(), vol 11925. Springer, Cham. https://doi.org/10.1007/978-3-030-34585-3_15
Download citation
DOI: https://doi.org/10.1007/978-3-030-34585-3_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-34584-6
Online ISBN: 978-3-030-34585-3
eBook Packages: Computer ScienceComputer Science (R0)