Taner ERDOGAN

DFT, molecular docking and molecular dynamics simulation studies on natural chromone derivatives from Cassia nomame for their possible antiviral activity against Coronavirus, SARS-CoV-2

In this study, two naturally occurred chromone derivatives obtained from Cassia nomame which are recently entered the literature, have been investigated computationally for their potential antiviral activity against SARS-CoV-2. In the first part of the study, DFT calculations were performed on the investigated compounds. In this part, geometry optimizations, frequency analyses, molecular electrostatic potential map calculations, frontier molecular orbital calculations and NMR spectral studies have been performed. In the second part of the study, molecular docking calculations were performed. SARS-CoV-2 main protease (SARS- CoV-2 Mpro) was selected as receptor for molecular docking calculations. In the third part of the study, molecular dynamics simulation studies were performed on the top scoring SARS- CoV-2 M pro – ligand complexes. In this part, binding free energy calculations were also performed on the SARS-CoV-2 Mpro – ligand complexes with the use of molecular mechanics with Poisson-Boltzmann surface area (MM-PBSA) method. Results showed that, two naturally occurred chromone derivatives, 5-(isobutyryl)-2-(2-oxopropyl)-7-methoxy-4H- chromen-4-one and 5-(isobutyryl)-2-(2-oxopropyl)-6-methoxy-4H-chromen-4-one, showed quite high binding affinity to SARS-CoV-2 M pro and remained stable during the molecular dynamics simulations. Additionally, in the last part of the study, drug-likeness analyses were performed on the investigated compounds with the use of Lipinski's rule of five and no violation was observed.

PDF

___

[1] Cheng C.Y., Lee Y.L., Chen C.P., Lin Y.C., Liu C.E., Liao C.H., Cheng S.H., Lopinavir/ritonavir did not shorten the duration of SARS CoV-2 shedding in patients with mild pneumonia in Taiwan, Journal of Microbiology, Immunology and Infection, 53 (2020) 488–492.
[2] Lin M.H., Moses D.C., Hsieh C.H., Cheng S.C., Chen Y.H., Sun C.Y., Chou C.Y., Disulfiram can inhibit MERS and SARS coronavirus papain-like proteases via different modes, Antiviral Research, 150 (2018) 155–163.
[3] Yu R., Chen L., Lan R., Shen R., Li P., Computational screening of antagonists against the SARS-CoV-2 (COVID-19) coronavirus by molecular docking, International Journal of Antimicrobial Agents, 56(2) (2020) 106012.
[4] Elfiky A.A., Ribavirin, Remdesivir, Sofosbuvir, Galidesivir and Tenofovir against SARS-CoV-2 RNA dependent RNA polymerase (RdRp): A molecular docking study, Life Sciences, 253 (2020).
[5] Cai Q., Yang M., Liu D., Chen J., Shu D., Xia J., Liao X., Gu Y., Cai Q., Yang Y., Shen C., Li X., Peng L., Huang D., Zhang J., Zhang S., Wang F., Liu J., Chen L., Chen S., Wang Z., Zhang Z., Cao R., Zhong W., Liu Y., Liu L., Experimental Treatment with Favipiravir for COVID-19: An Open-Label Control Study, Engineering, 6 (2020) 1192–1198.
6] Choy K.T.,. Wong A.Y.L, Kaewpreedee P., Sia S.F., Chen D., Hui K.P.Y., Chu D.K.W., Chan M.C.W., Cheung P.P.H., Huang X., Peiris M., Yen H.L., Remdesivir, lopinavir, emetine, and homoharringtonine inhibit SARS-CoV-2 replication in vitro, Antiviral Research, 178 (2020) 104786.
[7] McKee D.L., Sternberg A., Stange U., Laufer S., Naujokat C., Candidate drugs against SARS- CoV-2 and COVID-19, Pharmacological Research, 157 (2020) 104859.
[8] Erdogan T., DFT, molecular docking and molecular dynamics simulation studies on some newly introduced natural products for their potential use against SARS-CoV-2, Journal of Molecular Structure, 1242 (2021) 130733.
[9] Liu X., Wang X.J., Potential inhibitors against 2019-nCoV coronavirus M protease from clinically approved medicines, Journal of Genetics and Genomics, 47 (2020) 119–121.
[10] Xu Z., Peng C., Shi Y., Zhu Z., Mu K., Wang X., Zhu W., Nelfinavir was predicted to be a potential inhibitor of 2019-nCov main protease by an integrative approach combining homology modelling, molecular docking and binding free energy calculation, BioRxiv, (2020) 2020.01.27.921627.
[11] Liao L.M., Sun Y.Q., Li J., Kong W.S., Liu X., Xu Y., Huang H.T., Zeng W.L., Mi Q.L., Yang G.Y., Hu Q.F., Li Y.K., Two New Chromone Derivatives from Cassia nomame and their Anti- Tobacco Mosaic Virus Activity, Chemistry of Natural Compounds, 56 (2020) 58–61.
[12] Frisch M.J., Trucks G.W., Schlegel H.B., Scuseria G.E., Robb M.A., Cheeseman J.R., Scalmani G., Barone V., Mennucci B., Petersson G.A., Nakatsuji H., Caricato M., Li X., Hratchian H.P., Izmaylov A.F., Bloino J., Zheng G., Sonnenberg J.L., Hada M., Ehara M., Toyota K., Fukuda R., Hasegawa J., Ishida M., Nakajima T., Honda Y., Kitao O., Nakai H., Vreven T., Montgomery J. A., Peralta J.E., Ogliaro F., Bearpark M., Heyd J.J., Brothers E., Kudin K.N., Staroverov V.N., Keith T., Kobayashi R., Normand J., Raghavachari K., Rendell A., Burant J.C., Iyengar S.S., Tomasi J., Cossi M., Rega N., Millam J.M., Klene M., Knox J.E., Cross J.B., Bakken V., Adamo C., Jaramillo J., Gomperts R., Stratmann R.E., Yazyev O., Austin A.J., Cammi R., Pomelli C., Ochterski J.W., Martin R.L., Morokuma K., Zakrzewski V.G., Voth G.A., Salvador P., Dannenberg J.J., Dapprich S., Daniels A.D., Farkas O., Foresman J.B., Ortiz J. V, Cioslowski J., Fox D.J., Gaussian 09, (2013). [13] Dennington, R., T. Keith, J. Millam, GaussView, Version 5, (2009).
[14] Chang C. E. Gilson M.K., Tork: Conformational analysis method for molecules and complexes, Journal of Computational Chemistry, 24 (2003) 1987–1998.
[15] Hanwell M.D., Curtis D.E., Lonie D.C., Vandermeersch T., Zurek E., Hutchison G.R., Avogadro: an advanced semantic chemical editor, visualization, and analysis platform, Journal of Cheminformatics, 4 (2012) 17.
[16] Morris G.M., Huey R., Lindstrom W., Sanner M.F., Belew R.K., Goodsell D.S., Olson A.J., AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility, J Comput. Chem., 30 (2009) 2785–2791.
[17] BIOVIA, D.S., Discovery Studio Visualizer, v20.1.0.19295, (2016). [18] RCSB PDB, Available at: https://www.rcsb.org/, Retrieved May, 2021.
[19] Berman H.M., Westbrook J., Feng Z., Gilliland G., Bhat T.N., Weissig H., Shindyalov I.N., Bourne P.E., The Protein Data Bank, Nucleic Acids Research, 28 (2000) 235–242.
[20] Lindahl, Abraham, Hess, van der Spoel, GROMACS 2020 Source code, (2020).
[21] Ponder J.W., Case D.A., Force fields for protein simulations, Advances in Protein Chemistry, 66 (2003) 27–85.
[22] Sousa Da Silva A.W., Vranken W.F., ACPYPE - AnteChamber PYthon Parser interfacE, BMC Research Notes, 5 (2012) 367.
[23] Kumari R., Kumar R., Lynn A., G -mmpbsa -A GROMACS tool for high-throughput MM-PBSA calculations, Journal of Chemical Information and Modeling, 54 (2014) 1951–1962.
[24] Baker N.A., Sept D., Joseph S., Holst M.J., McCammon J.A., Electrostatics of nanosystems: Application to microtubules and the ribosome, Proceedings of the National Academy of Sciences of the United States of America, 98 (2001) 10037– 10041.
[25] Lipinski C.A., Lombardo F., Dominy B.W., Feeney P.J., Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings, Advanced Drug Delivery Reviews, 46 (2001) 3–
[26] Lipinski C.A., Lombardo F., Dominy B.W., Feeney P.J., Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings, Advanced Drug Delivery Reviews, 23 (1997) 3– 25.
[27] Drug Likeness Tool (DruLiTo), Available at: http://www.niper.gov.in/pi_dev_tools/DruLiTo W eb/DruLiTo_index.html, Retrieved May, 2020.