Virtual Screening of the Indonesian Medicinal Plant and Zinc Databases for Potential Inhibitors of the RNA-Dependent RNA Polymerase (RdRp) of 2019 Novel Coronavirus

Muhammad Arba(1*), Andry Nur-Hidayat(2), Ida Usman(3), Arry Yanuar(4), Setyanto Tri Wahyudi(5), Gilbert Fleischer(6), Dylan James Brunt(7), Chun Wu(8)

(1) Faculty of Pharmacy, Universitas Halu Oleo, Kendari 93232, Indonesia
(2) Faculty of Pharmacy, Universitas Halu Oleo, Kendari 93232, Indonesia
(3) Department of Physics, Universitas Halu Oleo, Kendari 93232, Indonesia
(4) Faculty of Pharmacy, Universitas Indonesia, Depok 16424, Indonesia
(5) Department of Physics, IPB University, Bogor 16680, Indonesia
(6) Department of Molecular & Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States
(7) Department of Molecular & Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States
(8) Department of Molecular & Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States
(*) Corresponding Author


The novel coronavirus disease 19 (Covid-19) which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a pandemic across the world, which necessitate the need for the antiviral drug discovery. One of the potential protein targets for coronavirus treatment is RNA-dependent RNA polymerase. It is the key enzyme in the viral replication machinery, and it does not exist in human beings, therefore its targeting has been considered as a strategic approach. Here we describe the identification of potential hits from Indonesian Herbal and ZINC databases. The pharmacophore modeling was employed followed by molecular docking and dynamics simulation for 40 ns. 151 and 14480 hit molecules were retrieved from Indonesian herbal and ZINC databases, respectively. Three hits that were selected based on the structural analysis were stable during 40 ns, while binding energy prediction further implied that ZINC1529045114, ZINC169730811, and 9-Ribosyl-trans-zeatin had tighter binding affinities compared to Remdesivir. The ZINC169730811 had the strongest affinity toward RdRp compared to the other two hits including Remdesivir and its binding was corroborated by electrostatic, van der Waals, and nonpolar contribution for solvation energies. The present study offers three hits showing tighter binding to RdRp based on MM-PBSA binding energy prediction for further experimental verification.


[1] World Health Organization, 2020, Coronavirus Disease (COVID-2019): Situation Reports, 94, World Health Organization, Geneva, 12.

[2] Dolan, P.T., Whitfield, Z.J., and Andino, R., 2018, Mechanisms and concepts in RNA virus population dynamics and evolution, Annu. Rev. Virol., 5 (1), 69–92.

[3] Jia, H., and Gong, P., 2019, A structure-function diversity survey of the RNA-dependent RNA polymerases from the positive-strand RNA viruses, Front. Microbiol., 10, 1945.

[4] Agostini, M.L., Andres, E.L., Sims, A.C., Graham, R.L., Sheahan, T.P., Lu, X., Smith, E.C., Case, J.B., Feng, J.Y., Jordan, R., Ray, A.S., Cihlar, T., Siegel, D., Mackman, R.L., Clarke, M.O., Baric, R.S., and Denison, M.R., 2018, Coronavirus susceptibility to the antiviral Remdesivir (GS-5734) is mediated by the viral polymerase and the proofreading exoribonuclease, MBio, 9 (2), e00221-18.

[5] Gordon, C.J., Tchesnokov, E.P., Feng, J.Y., Porter, D.P., and Götte, M., 2020, The antiviral compound Remdesivir potently inhibits RNA-dependent RNA polymerase from Middle East respiratory syndrome coronavirus, J. Biol. Chem., 295 (15), 4773–4779.

[6] Götte, M., and Feld, J.J., 2016, Direct-acting antiviral agents for hepatitis C: Structural and mechanistic insights, Nat. Rev. Gastroenterol. Hepatol., 13 (6), 338–351.

[7] Gane, E.J., Stedman, C.A., Hyland, R.H., Ding, X., Svarovskaia, E., Symonds, W.T., Hindes, R.G., and Berrey, M.M., 2013, Nucleotide polymerase inhibitor sofosbuvir plus ribavirin for Hepatitis C, N. Engl. J. Med., 368 (1), 34–44.

[8] Wolber, G., and Langer, T., 2005, LigandScout:  3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters, J. Chem. Inf. Model., 45 (1), 160–169.

[9] Sunseri, J., and Koes, D.R., 2016, Pharmit: interactive exploration of chemical space, Nucleic Acids Res., 44 (W1), W442–W448.

[10] Yanuar, A., Mun’im, A., Lagho, A.B.A., Syahdi, R.R., Rahmat, M., and Suhartanto, H., 2011, Medicinal plants database and three dimensional structure of the chemical compounds from medicinal plants in Indonesia, Int. J. Comput. Sci. Issues, 8 (5), 180–183.

[11] Arba, M., Pangan, A., and Yanuar, A., 2020, The search for peptide deformylase inhibitor from Indonesian medicinal plant database: An in-silico investigation, Biointerface Res. Appl. Chem., 10 (2), 5117–5121.

[12] Irwin, J.J., Sterling, T., Mysinger, M.M., Bolstad, E.S., and Coleman, R.G., 2012, ZINC: A free tool to discover chemistry for biology, J. Chem. Inf. Model., 52 (7), 1757–1768.

[13] Li, H., Leung, K.S., and Wong, M.H., 2012, idock: A multithreaded virtual screening tool for flexible ligand docking, IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), San Diego, United States, 9-12 May 2012, 77–84.

[14] Gao, Y., Yan, L., Huang, Y., Liu, F., Zhao, Y., Cao, L., Wang, T., Sun, Q., Ming, Z., Zhang, L., Ge, J., Zheng, L., Zhang, Y., Wang, H., Zhu, Y., Zhu, C., Hu, T., Hua, T., Zhang, B., Yang, X., Li, J., Yang, H., Liu, Z., Xu, W., Guddat, L.W., Wang, Q., Lou, Z., and Rao, Z., 2020, Structure of the RNA-dependent RNA polymerase from COVID-19 virus, Science, 368 (6492), 779–782.

[15] Daina, A., Michielin, O., and Zoete, V., 2017, SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules, Sci. Rep., 7, 42717.

[16] Arba, M., and Nurmawati, O., 2020, Identification of potential inhibitors for Bruton’s Tyrosine Kinase (BTK) based on pharmacophore-based virtual screening, Biointerface Res. Appl. Chem., 10 (3), 5472–5477.

[17] Maier, J.A., Martinez, C., Kasavajhala, K., Wickstrom, L., Hauser, K.E., and Simmerling, C., 2015, ff14SB: Improving the accuracy of protein side chain and backbone parameters from ff99SB, J. Chem. Theory Comput., 11 (8), 3696–3713.

[18] Wang, J., Wolf, R.M., Caldwell, J.W., Kollman, P.A., and Case, D.A., 2004, Development and testing of a general amber force field, J. Comput. Chem., 25 (9), 1157–1174.

[19] Roe, D.R., and Cheatham III, T.E., 2013, PTRAJ and CPPTRAJ: Software for processing and analysis of molecular dynamics trajectory data, J. Chem. Theory Comput., 9 (7), 3084–3095.

[20] Appleby, T.C., Perry, J.K., Murakami, E., Barauskas, O., Feng, J., Cho, A., Fox, D., Wetmore, D.R., McGrath, M.E., Ray, A.S., Sofia, M.J., Swaminathan, S., and Edwards, T.E., 2015, Structural basis for RNA replication by the hepatitis C virus polymerase, Science, 347 (6223), 771–775.

[21] Deval, J., Symons, J.A., and Beigelman, L., 2014, Inhibition of viral RNA polymerases by nucleoside and nucleotide analogs: Therapeutic applications against positive-strand RNA viruses beyond hepatitis C virus, Curr. Opin. Virol., 9, 1–7.

[22] Rifai, E.A., Ferrario, V., Pleiss, J., and Geerke, D.P., 2020, Combined linear interaction energy and alchemical solvation free-energy approach for protein-binding affinity computation, J. Chem. Theory. Comput., 16 (2), 1300–1310.

[23] Kollman, P.A., Massova, I., Reyes, C., Kuhn, B., Huo, S., Chong, L., Lee, M., Lee, T., Duan, Y., Wang, W., Donini, O., Cieplak, P., Srinivasan, J., Case, D.A., and Cheatham, T.E., 2000, Calculating structures and free energies of complex molecules: Combining molecular mechanics and continuum models, Acc. Chem. Res., 33 (12), 889–897.

[24] Srinivasan, J., Cheatham, T.E., Cieplak, P., Kollman, P.A., and Case, D.A., 1998, Continuum solvent studies of the stability of DNA, RNA, and phosphoramidate−DNA helices, J. Am. Chem. Soc., 120 (37), 9401–9409.

[25] Arba, M., Ruslin, Ihsan, S., Tri Wahyudi, S., and Tjahjono, D.H., 2017, Molecular modeling of cationic porphyrin-anthraquinone hybrids as DNA topoisomerase IIβ inhibitors, Comput. Biol. Chem., 71, 129–135.


Article Metrics

Abstract views : 495 | views : 212 | views : 65

Copyright (c) 2020 Indonesian Journal of Chemistry

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


Indonesian Journal of Chemistry (ISSN 1411-9420 / 2460-1578) - Chemistry Department, Universitas Gadjah Mada, Indonesia.

Analytics View The Statistics of Indones. J. Chem.