Generic placeholder image

Current Topics in Medicinal Chemistry

Editor-in-Chief

ISSN (Print): 1568-0266
ISSN (Online): 1873-4294

Research Article

Ligand and Structure-based Virtual Screening of Lamiaceae Diterpenes with Potential Activity against a Novel Coronavirus (2019-nCoV)

Author(s): Gabriela Cristina Soares Rodrigues, Mayara dos Santos Maia, Renata Priscila Barros de Menezes, Andreza Barbosa Silva Cavalcanti, Natália Ferreira de Sousa, Érika Paiva de Moura, Alex France Messias Monteiro, Luciana Scotti and Marcus Tullius Scotti*

Volume 20, Issue 24, 2020

Page: [2126 - 2145] Pages: 20

DOI: 10.2174/1568026620666200716114546

Price: $65

Abstract

Background: The emergence of a new coronavirus (CoV), named 2019-nCoV, as an outbreak originated in the city of Wuhan, China, has resulted in the death of more than 3,400 people this year alone and has caused worldwide an alarming situation, particularly following previous CoV epidemics, including the Severe Acute Respiratory Syndrome (SARS) in 2003 and the Middle East Respiratory Syndrome (MERS) in 2012. Currently, no exists for infections caused by CoVs; however, some natural products may represent potential treatment resources, such as those that contain diterpenes.

Objective: This study aimed to use computational methods to perform a virtual screening (VS) of candidate diterpenes with the potential to act as CoV inhibitors.

Methods: 1,955 diterpenes, derived from the Nepetoideae subfamily (Lamiaceae), were selected using the SistematX tool (https://sistematx.ufpb.br), which were used to make predictions. From the ChEMBL database, 3 sets of chemical structures were selected for the construction of predictive models.

Results: The chemical structures of molecules with known activity against SARS CoV, two of which were tested for activity against specific viral proteins and one of which was tested for activity against the virus itself, were classified according to their pIC50 values [-log IC50 (mol/l)].

Conclusion: In the consensus analysis approach, combining both ligand- and structure-based VSs, 19 compounds were selected as potential CoV inhibitors, including isotanshinone IIA (01), tanshinlactone (02), isocryptotanshinone (03), and tanshinketolactone (04), which did not present toxicity within the evaluated parameters.

Keywords: Coronavirus, Virtual screening, Natural products database, Diterpenes, Consensus analysis, Ligand.

Graphical Abstract
[1]
Friedman, N.; Alter, H.; Hindiyeh, M.; Mendelson, E.; Shemer Avni, Y.; Mandelboim, M. Human coronavirus infections in Israel: epidemiology, clinical symptoms and summer seasonality of HCoV-HKU1. Viruses, 2018, 10(10), 1-9.
[http://dx.doi.org/10.3390/v10100515 ] [PMID: 30241410]
[2]
Zhang, L.; Lin, D.; Kusov, Y.; Nian, Y.; Ma, Q.; Wang, J.; von Brunn, A.; Leyssen, P.; Lanko, K.; Neyts, J.; de Wilde, A.; Snijder, E.J.; Liu, H.; Hilgenfeld, R. Alpha-ketoamides as broad-spectrum inhibitors of coronavirus and enterovirus replication. J. Med. Chem., 2020, 63(9), 4562-4578.
[http://dx.doi.org/10.1021/acs.jmedchem.9b01828 ] [PMID: 32045235]
[3]
Li, G.; Fan, Y.; Lai, Y.; Han, T.; Li, Z.; Zhou, P.; Pan, P.; Wang, W.; Hu, D.; Liu, X.; Zhang, Q.; Wu, J. Coronavirus infections and immune responses. J. Med. Virol., 2020, 92(4), 424-432.
[http://dx.doi.org/10.1002/jmv.25685 ] [PMID: 31981224]
[4]
Liu, X.; Wang, X-J. Potential inhibitors against 2019-nCoV coronavirus M protease from clinically approved medicines. J. Genet. Genomics, 2020, 47(2), 119-121.
[http://dx.doi.org/10.1016/j.jgg.2020.02.001 ] [PMID: 32173287]
[5]
Lee, T-W.; Cherney, M.M.; Huitema, C.; Liu, J.; James, K.E.; Powers, J.C.; Eltis, L.D.; James, M.N.G. Crystal structures of the main peptidase from the SARS coronavirus inhibited by a substrate-like aza-peptide epoxide. J. Mol. Biol., 2005, 353(5), 1137-1151.
[http://dx.doi.org/10.1016/j.jmb.2005.09.004 ] [PMID: 16219322]
[6]
Zhao, Q.; Li, S.; Xue, F.; Zou, Y.; Chen, C.; Bartlam, M.; Rao, Z. Structure of the main protease from a global infectious human coronavirus, HCoV-HKU1. J. Virol., 2008, 82(17), 8647-8655.
[http://dx.doi.org/10.1128/JVI.00298-08 ] [PMID: 18562531]
[7]
Casanova, L.M.; Costa, S.S. Synergistic interactions in natural products: therapeutic potential and challenges. Rev. VIRTUAL Quim., 2017, 9, 575-595.
[http://dx.doi.org/10.21577/1984-6835.20170034]
[8]
Koparde, A.A.; Doijad, R.C.; Magdum, C.S. Natural Products in Drug Discovery. In: Pharmacognosy-Medicinal Plants; IntechOpen: London, 2019.
[http://dx.doi.org/10.5772/intechopen.82860]
[9]
Calixto, J.B. The role of natural products in modern drug discovery. An. Acad. Bras. Cienc., 2019, 91(Suppl. 3), e20190105.
[http://dx.doi.org/10.1590/0001-3765201920190105 ] [PMID: 31166478]
[10]
Alves, V.; Braga, R.; Muratov, E.; Andrade, C. Chemoinformatics: an introduction. Quim. Nova, 2017, 41, 202-212.
[11]
Rocha Martins, L.R.; Brenzan, M.A.; Nakamura, C.V.; Dias Filho, B.P.; Nakamura, T.U.; Ranieri Cortez, L.E.; Garcia Cortez, D.A. In vitro antiviral activity from Acanthospermum australe on herpesvirus and poliovirus. Pharm. Biol., 2011, 49(1), 26-31.
[http://dx.doi.org/10.3109/13880209.2010.493177 ] [PMID: 20819023]
[12]
Nothias-Scaglia, L-F.; Pannecouque, C.; Renucci, F.; Delang, L.; Neyts, J.; Roussi, F.; Costa, J.; Leyssen, P.; Litaudon, M.; Paolini, J. Antiviral activity of diterpene esters on chikungunya virus and HIV replication. J. Nat. Prod., 2015, 78(6), 1277-1283.
[http://dx.doi.org/10.1021/acs.jnatprod.5b00073 ] [PMID: 25970561]
[13]
Nothias, L-F.; Boutet-Mercey, S.; Cachet, X.; De La Torre, E.; Laboureur, L.; Gallard, J-F.; Retailleau, P.; Brunelle, A.; Dorrestein, P.C.; Costa, J.; Bedoya, L.M.; Roussi, F.; Leyssen, P.; Alcami, J.; Paolini, J.; Litaudon, M.; Touboul, D. Environmentally friendly procedure based on supercritical fluid chromatography and tandem mass spectrometry molecular networking for the discovery of potent antiviral compounds from Euphorbia semiperfoliata. J. Nat. Prod., 2017, 80(10), 2620-2629.
[http://dx.doi.org/10.1021/acs.jnatprod.7b00113 ] [PMID: 28925702]
[14]
Hassan, S.T.S.; Masarčíková, R.; Berchová, K. Bioactive natural products with anti-herpes simplex virus properties. J. Pharm. Pharmacol., 2015, 67(10), 1325-1336.
[http://dx.doi.org/10.1111/jphp.12436 ] [PMID: 26060043]
[15]
Kohmoto, S.; Mcconnell, O.J.; Wright, A.; Cross, S. Isospongiadiol, a cytotoxic and antiviral diterpene from a Caribbean deep water marine sponge, Spongia sp. Chem. Lett., 1987, 16, 1687-1690.
[http://dx.doi.org/10.1246/cl.1987.1687]
[16]
Ogawa, K.; Nakamura, S.; Hosokawa, K.; Ishimaru, H.; Saito, N.; Ryu, K.; Fujimuro, M.; Nakashima, S.; Matsuda, H. New diterpenes from Nigella damascena seeds and their antiviral activities against herpes simplex virus type-1. J. Nat. Med., 2018, 72(2), 439-447.
[http://dx.doi.org/10.1007/s11418-017-1166-6 ] [PMID: 29288328]
[17]
Tan, Y.P.; Houston, S.D.; Modhiran, N.; Savchenko, A.I.; Boyle, G.M.; Young, P.R.; Watterson, D.; Williams, C.M. Stachyonic acid: A dengue virus inhibitor from Basilicum polystachyon. Chemistry, 2019, 25(22), 5664-5667.
[http://dx.doi.org/10.1002/chem.201900591 ] [PMID: 30924209]
[18]
Islam, M.T.; Mubarak, M.S. Diterpenes and their derivatives as promising agents against dengue virus and dengue vectors: A literature‐based review. Phytother. Res., 2019, 1, 1-11.
[http://dx.doi.org/10.1002/ptr.6562 ] [PMID: 31802573]
[19]
Lee, C-L.; Chiang, L-C.; Cheng, L-H.; Liaw, C-C.; Abd El-Razek, M.H.; Chang, F-R.; Wu, Y-C.; Influenza, A. H1N1) antiviral and cytotoxic agents from Ferula assa-foetida. J. Nat. Prod., 2009, 72(9), 1568-1572.
[http://dx.doi.org/10.1021/np900158f ] [PMID: 19691312]
[20]
Chien, D.T.; Bahri, S.; Szardenings, A.K.; Walsh, J.C.; Mu, F.; Su, M-Y.; Shankle, W.R.; Elizarov, A.; Kolb, H.C. Early clinical PET imaging results with the novel PHF-tau radioligand [F-18]-T807. J. Alzheimers Dis., 2013, 34(2), 457-468.
[http://dx.doi.org/10.3233/JAD-122059 ] [PMID: 23234879]
[21]
Cirne-Santos, C.C.; Barros, C. de S.; Gomes, M.W.L.; Gomes, R.; Cavalcanti, D.N.; Obando, J.M.C.; Ramos, C.J.B.; Villaça, R.C.; Teixeira, V.L.; Paixão, I.C.N. de P. In vitro antiviral activity against zika virus from a natural product of the Brazilian brown seaweed dictyota menstrualis. Nat. Prod. Commun., 2019, 14, 1-7.
[http://dx.doi.org/10.1177/1934578X19859128]
[22]
Abreu, L.S.; do Nascimento, Y.M.; Costa, R.D.S.; Guedes, M.L.S.; Souza, B.N.R.F.; Pena, L.J.; Costa, V.C.O.; Scotti, M.T.; Braz-Filho, R.; Barbosa-Filho, J.M.; da Silva, M.S.; Velozo, E.D.S.; Tavares, J.F. Tri- and diterpenoids from Stillingia loranthacea as inhibitors of zika virus replication. J. Nat. Prod., 2019, 82(10), 2721-2730.
[http://dx.doi.org/10.1021/acs.jnatprod.9b00251 ] [PMID: 31599155]
[23]
Frezza, C.; Venditti, A.; Serafini, M.; Bianco, A. Phytochemistry, chemotaxonomy, ethnopharmacology, and nutraceutics of Lamiaceae. In: Studies in natural products chemistry; Elsevier: Amsterdam, 2019, Vol. 62, pp. 125-178.
[http://dx.doi.org/10.1016/B978-0-444-64185-4.00004-6]
[24]
Li, B.; Cantino, P.D.; Olmstead, R.G.; Bramley, G.L.C.; Xiang, C-L.; Ma, Z-H.; Tan, Y-H.; Zhang, D-X. A large-scale chloroplast phylogeny of the Lamiaceae sheds new light on its subfamilial classification. Sci. Rep., 2016, 6, 34343.
[http://dx.doi.org/10.1038/srep34343 ] [PMID: 27748362]
[25]
Barbosa Silva Cavalcanti, A.; Costa Barros, R.P.; Costa, V.C. de O.; Sobral da Silva, M.; Fechine Tavares, J.; Scotti, L.; Scotti, M.T. Computer-aided chemotaxonomy and bioprospecting study of diterpenes of the lamiaceae family. Molecules, 2019, 24, 1-16.
[http://dx.doi.org/10.3390/molecules24213908]
[26]
Bernstein, F.C.; Koetzle, T.F.; Williams, G.J.B.; Meyer, E.F., Jr; Brice, M.D.; Rodgers, J.R.; Kennard, O.; Shimanouchi, T.; Tasumi, M. The Protein Data Bank. A computer-based archival file for macromolecular structures. Eur. J. Biochem., 1977, 80(2), 319-324.
[http://dx.doi.org/10.1111/j.1432-1033.1977.tb11885.x ] [PMID: 923582]
[27]
RCSB; Protein Data Bank., Available from: . https://www.rcsb.org/. (Accessed in Feb, 2020)
[28]
Tomar, S.; Johnston, M.L.; St John, S.E.; Osswald, H.L.; Nyalapatla, P.R.; Paul, L.N.; Ghosh, A.K.; Denison, M.R.; Mesecar, A.D. Ligand-induced Dimerization of Middle East Respiratory Syndrome (MERS) Coronavirus nsp5 Protease (3CLpro) implications for nsp5 regulation and the development of antivirals. J. Biol. Chem., 2015, 290(32), 19403-19422.
[http://dx.doi.org/10.1074/jbc.M115.651463 ] [PMID: 26055715]
[29]
Pettersen, E.F.; Goddard, T.D.; Huang, C.C.; Couch, G.S.; Greenblatt, D.M.; Meng, E.C.; Ferrin, T.E. UCSF Chimera--a visualization system for exploratory research and analysis. J. Comput. Chem., 2004, 25(13), 1605-1612.
[http://dx.doi.org/10.1002/jcc.20084 ] [PMID: 15264254]
[30]
Scotti, M.T.; Herrera-Acevedo, C.; Oliveira, T.B.; Costa, R.P.O.; Santos, S.Y.K.O.; Rodrigues, R.P.; Scotti, L.; Da-Costa, F.B.; Sistemat, X. SistematX, an online web-based cheminformatics tool for data management of secondary Metabolites. Molecules, 2018, 23(1), 1-10.
[http://dx.doi.org/10.3390/molecules23010103 ] [PMID: 29301376]
[31]
Talete srl. Dragon - Software for Molecular Descriptor Calculation) Version 7 , Pisa: Italy..
[32]
Salzberg, S.; Quinlan, R. Book Review: C4. 5: Programs for machine learning by J. Ross Quinlan, 1994, 1, 1-6.
[33]
Hall, M.; Frank, E.; Holmes, G.; Pfahringer, B.; Reutemann, P.; Witten, I.H. The WEKA data mining software: an update. SIGKDD Explor., 2009, 11, 10-18.
[http://dx.doi.org/10.1145/1656274.1656278]
[34]
Matthews, B.W. Comparison of the predicted and observed secondary structure of T4 phage lysozyme. Biochim. Biophys. Acta, 1975, 405(2), 442-451.
[http://dx.doi.org/10.1016/0005-2795(75)90109-9 ] [PMID: 1180967]
[35]
Scotti, L.; Ishiki, H.; Mendonça Júnior, F.J.B.; Da Silva, M.S.; Scotti, M.T. In-silico analyses of natural products on leishmania enzyme targets. Mini Rev. Med. Chem., 2015, 15(3), 253-269.
[http://dx.doi.org/10.2174/138955751503150312141854 ] [PMID: 25769973]
[36]
Alves, V.M.; Golbraikh, A.; Capuzzi, S.J.; Liu, K.; Lam, W.I.; Korn, D.R.; Pozefsky, D.; Andrade, C.H.; Muratov, E.N.; Tropsha, A. Multi-descriptor read across (mudra): a simple and transparent approach for developing accurate quantitative structure-activity relationship models. J. Chem. Inf. Model., 2018, 58(6), 1214-1223.
[http://dx.doi.org/10.1021/acs.jcim.8b00124 ] [PMID: 29809005]
[37]
Albert, M.K.; Aha, D.W. Analyses of instace-based learning algorithms. AAAI-91 Proc , 1991, 1, pp. 553-558.
[38]
Low, Y.; Sedykh, A.; Fourches, D.; Golbraikh, A.; Whelan, M.; Rusyn, I.; Tropsha, A. Integrative chemical-biological read-across approach for chemical hazard classification. Chem. Res. Toxicol., 2013, 26(8), 1199-1208.
[http://dx.doi.org/10.1021/tx400110f ] [PMID: 23848138]
[39]
Barros, R.P.C.; da Cunha, E.V.L.; Catão, R.M.R.; Scotti, L.; Souza, M.S.R.; Brás, A.A.Q.; Scotti, M.T. Virtual screening of secondary metabolites of the genus Solanum with potential antimicrobial activity. Rev. Bras. Farmacogn., 2018, 28, 686-691.
[http://dx.doi.org/10.1016/j.bjp.2018.08.003]
[40]
Acevedo, C.H.; Scotti, L.; Scotti, M.T. In silico studies designed to select sesquiterpene lactones with potential antichagasic activity from an in-house asteraceae database. ChemMedChem, 2018, 13(6), 634-645.
[http://dx.doi.org/10.1002/cmdc.201700743 ] [PMID: 29323468]
[41]
Thomsen, R.; Christensen, M.H. MolDock: a new technique for high-accuracy molecular docking. J. Med. Chem., 2006, 49(11), 3315-3321.
[http://dx.doi.org/10.1021/jm051197e ] [PMID: 16722650]
[42]
Mandal, S.; Moudgil, M.; Mandal, S.K. Rational drug design. Eur. J. Pharmacol., 2009, 625(1-3), 90-100.
[http://dx.doi.org/10.1016/j.ejphar.2009.06.065 ] [PMID: 19835861]
[43]
Lee, C-C.; Kuo, C-J.; Ko, T-P.; Hsu, M-F.; Tsui, Y-C.; Chang, S-C.; Yang, S.; Chen, S-J.; Chen, H-C.; Hsu, M-C.; Shih, S.R.; Liang, P.H.; Wang, A.H. Structural basis of inhibition specificities of 3C and 3C-like proteases by zinc-coordinating and peptidomimetic compounds. J. Biol. Chem., 2009, 284(12), 7646-7655.
[http://dx.doi.org/10.1074/jbc.M807947200 ] [PMID: 19144641]
[44]
Wei, W.J.; Zhou, P.P.; Lin, C.J.; Wang, W.F.; Li, Y.; Gao, K. Diterpenoids from salvia miltiorrhiza and their immune-modulating activity. J. Agric. Food Chem., 2017, 65(29), 5985-5993.
[http://dx.doi.org/10.1021/acs.jafc.7b02384 ] [PMID: 28679204]
[45]
Lipinski, C.F.; Maltarollo, V.G.; Oliveira, P.R.; Silva, A.B.F. Advances and perspectives in applying deep learning for drug design and discovery. Frontiers in Robotics and AI, 2019, 6, 1-6.
[46]
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. Adv. Drug Deliv. Rev., 2001, 46(1-3), 3-26.
[http://dx.doi.org/10.1016/S0169-409X(00)00129-0 ] [PMID: 11259830]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy