Exploring Secondary Metabolites Database of Apocynaceae, Menispermaceae, and Annonaceae to Select Potential Anti-HCV Compounds

Author(s): Renata P.C. Barros, Luciana Scotti, Marcus T. Scotti*

Journal Name: Current Topics in Medicinal Chemistry

Volume 19 , Issue 11 , 2019

Become EABM
Become Reviewer
Call for Editor

Graphical Abstract:


Background: Hepatitis C is a disease that constitutes a serious global health problem, is often asymptomatic and difficult to diagnose and about 60-80% of infected patients develop chronic diseases over time. As there is no vaccine against hepatitis C virus (HCV), developing new cheap treatments is a big challenge.

Objective: The search for new drugs from natural products has been outstanding in recent years. The aim of this study was to combine structure-based and ligand-based virtual screening (VS) techniques to select potentially active molecules against four HCV target proteins from in-house secondary metabolite dataset (SistematX).

Materials and Methods: From the ChEMBL database, we selected four sets of 1199, 355, 290 and 237chemical structures with inhibitory activity against different targets of HCV to create random forest models with an accuracy value higher than 82% for cross-validation and test sets. Afterward, a ligandbased virtual screen of the entire 1848 secondary metabolites database stored in SistematX was performed. In addition, a structure-based virtual screening was also performed for the same set of secondary metabolites using molecular docking.

Results: Finally, using consensus analyses approach combining ligand-based and structure-based VS, three alkaloids were selected as potential anti-HCV compounds.

Conclusion: The selected structures are a starting point for further studies in order to develop new anti- HCV compounds based on natural products.

Keywords: Hepatitis C virus, Alkaloids, Terpenes, Ligand-based virtual screening, Structure-based virtual screening, Molecular dynamics.

Ismail, N.S.M.; Elzahabi, H.S.A.; Sabry, P.; Baselious, F.N. AbdelMalaK, A.S.; Hanna, F. A study of the allosteric inhibition of HCV RNA-dependent RNA polymerase and implementing virtual screening for the selection of promising dual-site inhibitors with low resistance potential. J. Recept. Sig. Transd., 2016, 37(4), 335-341. [doi: 10.1080/10799893.2016.1248293].
World Health Organization (WHO) Global hepatitis report. 2017 (Available at: https://www.who.int/hepatitis/publications/global-hepatitis-report2017/en/).
Ministério da Saúde. Coletiva Hepatites (ASCOM): Plano para eliminar hepatite C até 2030. 2017.
Ganesan, A.; Barakat, K. Applications of computer-aided approaches in the development of hepatitis C antiviral agents. Expert Opin. Drug Discov., 2017, 12(4), 407-425. [http://dx.doi.org/10.1080/17460441.2017.1291628]. [PMID: 28164720].
El-Hasab, M.A.E.; El-Bastawissy, E.E.; El-Moselhy, T.F. Identification of potential inhibitors for HCV NS3 genotype 4a by combining protein-ligand interaction fingerprint, 3D pharmacophore, docking, and dynamic simulation. J. Biomol. Struct. Dyn., 2018, 36(7), 1713-1727. [http://dx.doi.org/10.1080/07391102.2017.1332689]. [PMID: 28531373].
Wang, M.; Xuan, S.; Yan, A.; Yu, C. Classification models of HCV NS3 protease inhibitors based on support vector machine (SVM). Comb. Chem. High Throughput Screen., 2015, 18(1), 24-32. [http://dx.doi.org/10.2174/1386207317666141120122554]. [PMID: 25410306].
Cheung, M.C.M.; Walker, A.J.; Hudson, B.E.; Verma, S.; McLauchlan, J.; Mutimer, D.J.; Brown, A.; Gelson, W.T.H.; MacDonald, D.C.; Agarwal, K.; Foster, G.R.; Irving, W.L. Outcomes after successful direct-acting antiviral therapy for patients with chronic hepatitis C and decompensated cirrhosis. J. Hepatol., 2016, 65(4), 741-747. [http://dx.doi.org/10.1016/j.jhep.2016.06.019]. [PMID: 27388925].
Manns, M.; Samuel, D.; Gane, E.J.; Mutimer, D.; McCaughan, G.; Buti, M.; Prieto, M.; Calleja, J.L.; Peck-Radosavljevic, M.; Müllhaupt, B.; Agarwal, K.; Angus, P.; Yoshida, E.M.; Colombo, M.; Rizzetto, M.; Dvory-Sobol, H.; Denning, J.; Arterburn, S.; Pang, P.S.; Brainard, D.; McHutchison, J.G.; Dufour, J.F.; Van Vlierberghe, H.; van Hoek, B.; Forns, X. Ledipasvir and sofosbuvir plus ribavirin in patients with genotype 1 or 4 hepatitis C virus infection and advanced liver disease: a multicentre, open-label, randomised, phase 2 trial. Lancet Infect. Dis., 2016, 16(6), 685-697. [http://dx.doi.org/10.1016/S1473-3099(16)00052-9]. [PMID: 26907736].
Foster, G.R.; Irving, W.L.; Cheung, M.C.; Walker, A.J.; Hudson, B.E.; Verma, S.; McLauchlan, J.; Mutimer, D.J.; Brown, A.; Gelson, W.T.; MacDonald, D.C.; Agarwal, K. Impact of direct acting antiviral therapy in patients with chronic hepatitis C and decompensated cirrhosis. J. Hepatol., 2016, 64(6), 1224-1231. [http://dx.doi.org/10.1016/j.jhep.2016.01.029]. [PMID: 26829205].
Curry, M.P.; O’Leary, J.G.; Bzowej, N.; Muir, A.J.; Korenblat, K.M.; Fenkel, J.M.; Reddy, K.R.; Lawitz, E.; Flamm, S.L.; Schiano, T.; Teperman, L.; Fontana, R.; Schiff, E.; Fried, M.; Doehle, B.; An, D.; McNally, J.; Osinusi, A.; Brainard, D.M.; McHutchison, J.G.; Brown, R.S., Jr; Charlton, M. ASTRAL-4 Investigators Sofosbuvir and velpatasvir for HCV in patients with decompensated cirrhosis. N. Engl. J. Med., 2015, 373(27), 2618-2628. [http://dx.doi.org/10.1056/NEJMoa1512614]. [PMID: 26569658].
Belli, L.S.; Berenguer, M.; Cortesi, P.A.; Strazzabosco, M.; Rockenschaub, S.R.; Martini, S.; Morelli, C.; Donato, F.; Volpes, R.; Pageaux, G.P.; Coilly, A.; Fagiuoli, S.; Amaddeo, G.; Perricone, G.; Vinaixa, C.; Berlakovich, G.; Facchetti, R.; Polak, W.; Muiesan, P.; Duvoux, C. Delisting of liver transplant candidates with chronic hepatitis C after viral eradication: A European study. J. Hepatol., 2016, 65(3), 524-531. [http://dx.doi.org/10.1016/j.jhep.2016.05.010]. [PMID: 27212241].
Pascasio, J.M.; Vinaixa, C.; Ferrer, M.T.; Colmenero, J.; Rubin, A.; Castells, L.; Manzano, M.L.; Lorente, S.; Testillano, M.; Xiol, X.; Molina, E.; González-Diéguez, L.; Otón, E.; Pascual, S.; Santos, B.; Herrero, J.I.; Salcedo, M.; Montero, J.L.; Sánchez-Antolín, G.; Narváez, I.; Nogueras, F.; Giráldez, Á.; Prieto, M.; Forns, X.; Londoño, M.C. Clinical outcomes of patients undergoing antiviral therapy while awaiting liver transplantation. J. Hepatol., 2017, 67(6), 1168-1176. [http://dx.doi.org/10.1016/j.jhep.2017.08.008]. [PMID: 28842296].
Belli, L.S.; Duvoux, C.; Berenguer, M.; Berg, T.; Coilly, A.; Colle, I.; Fagiuoli, S.; Khoo, S.; Pageaux, G.P.; Puoti, M.; Samuel, D.; Strazzabosco, M. ELITA consensus statements on the use of DAAs in liver transplant candidates and recipients. J. Hepatol., 2017, 67(3), 585-602. [http://dx.doi.org/10.1016/j.jhep.2017.03.006]. [PMID: 28323126].
Carreño, V.; Bartolomé, J.; Castillo, I.; Quiroga, J.A. New perspectives in occult hepatitis C virus infection. World J. Gastroenterol., 2012, 18(23), 2887-2894. [http://dx.doi.org/10.3748/wjg.v18.i23.2887]. [PMID: 22736911].
Chou, R.; Hartung, D.; Rahman, B.; Wasson, N.; Cottrell, E.B.; Fu, R. Comparative effectiveness of antiviral treatment for hepatitis C virus infection in adults: a systematic review. Ann. Intern. Med., 2013, 158(2), 114-123. [http://dx.doi.org/10.7326/0003-4819-158-2-201301150-00576]. [PMID: 23437439].
Abd Alla, M.D.A.; El Awady, M.K.; Dawood, R.M.; Elhawary, M.A.; Al-Azhari, S.S.; Galal, A.G.M. Hepatitis C virus serologic relapse after treatment with direct-acting antivirals is dependent on viral RNA levels in peripheral blood mononuclear cells and the grade of liver cirrhosis. Arch. Virol., 2018, 163(10), 2765-2774. [http://dx.doi.org/10.1007/s00705-018-3922-7]. [PMID: 29971486].
Faillaci, F.; Marzi, L.; Critelli, R.; Milosa, F.; Schepis, F.; Turola, E.; Andreani, S.; Vandelli, G.; Bernabucci, V.; Lei, B. DÁmbrosio, F.; Bristot, L.; Cavalletto, L.; Chamello, L.; Sighinolfi, P.; Manni, P.; Maionara, A.; Caporali, C.; Bianchini, M.; Marsico, M.; Turco, L.; de Maria, N.; Del Buono; M., Todesca, P.; di Lena, L.; Romagnoli, D.; Magistri, P.; di Benedetto, F.; Bruno, S.; Taliani, G.; Gianneli, G.; Martinez-Chantar, M.L.; Villa, E. Liver angiopoietin-2 is a key predictor of de novo or recurrent hepatocellular cancer after hepatitis C virus direct-acting antivirals. Hepatol, 2018, 68, 1010-1024. [http://dx.doi.org/10.1002/hep.29911].
Ikeda, K.; Kawamura, Y.; Kobayashi, M.; Kominami, Y.; Fujiyama, S.; Sezaki, H.; Hosaka, T.; Akuta, N.; Saitoh, S.; Suzuki, F.; Suzuki, Y.; Arase, Y.; Kumada, H. Direct-acting antivirals decreased tumor recurrence after initial treatment of hepatitis C virus-related hepatocellular carcinoma. Dig. Dis. Sci., 2017, 62(10), 2932-2942. [http://dx.doi.org/10.1007/s10620-017-4739-z]. [PMID: 28884320].
Waziry, R.; Hajarizadeh, B.; Grebely, J.; Amin, J.; Law, M.; Danta, M.; George, J.; Dore, G.J. Hepatocellular carcinoma risk following direct-acting antiviral HCV therapy: A systematic review, meta-analyses, and meta-regression. J. Hepatol., 2017, 67(6), 1204-1212. [http://dx.doi.org/10.1016/j.jhep.2017.07.025]. [PMID: 28802876].
Alberti, A.; Piovesan, S. Increased incidence of liver cancer after successful DAA treatment of chronic hepatitis C: Fact or fiction? Liver Int., 2017, 37(6), 802-808. [http://dx.doi.org/10.1111/liv.13390]. [PMID: 28544696].
Serti, E.; Park, H.; Keane, M.; O’Keefe, A.C.; Rivera, E.; Liang, T.J.; Ghany, M.; Rehermann, B. Rapid decrease in hepatitis C viremia by direct acting antivirals improves the natural killer cell response to IFNα. Gut, 2017, 66(4), 724-735. [http://dx.doi.org/10.1136/gutjnl-2015-310033]. [PMID: 26733671].
Meissner, E.G.; Wu, D.; Osinusi, A.; Bon, D.; Virtaneva, K.; Sturdevant, D.; Porcella, S.; Wang, H.; Herrmann, E.; McHutchison, J.; Suffredini, A.F.; Polis, M.; Hewitt, S.; Prokunina-Olsson, L.; Masur, H.; Fauci, A.S.; Kottilil, S. Endogenous intrahepatic IFNs and association with IFN-free HCV treatment outcome. J. Clin. Invest., 2014, 124(8), 3352-3363. [http://dx.doi.org/10.1172/JCI75938]. [PMID: 24983321].
Ponder, E.L.; Freundlich, J.S.; Sarker, M.; Ekins, S. Computational models for neglected diseases: Gaps and opportunities. Pharm. Res., 2014, 31(2), 271-277. [http://dx.doi.org/10.1007/s11095-013-1170-9]. [PMID: 23990313].
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. An online web-based cheminformatics tool for data management of secondary metabolites. Molecules, 2018, 23(1), 103-113. [http://dx.doi.org/10.3390/molecules23010103]. [PMID: 29301376].
Cruciani, G.; Crivori, P.; Carrupt, P.A.; Testa, B. Predicting blood-brain barrier permeation from three-dimensional molecular structure. J. Mol. Struct., 2000, 503, 17-30. [http://dx.doi.org/10.1016/S0166-1280(99)00360-7].
Steven, L. Book Review: C4.5: Programs for machine learning. Morgan Kaufmann, 1993, 16, 235-240.
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].
Scotti, M.T.; Scotti, L.; Ishiki, H.M.; Peron, L.M.; Rezende, L.; Amaral, A.T. Variable selection approaches to generate QSAR models for a set of antichagasic semicarbazones and analogues. Chemom. Intell. Lab. Syst., 2016, 154, 137-149. [http://dx.doi.org/10.1016/j.chemolab.2016.03.023].
Jiang, Y.; Andrews, S.W.; Condroski, K.R.; Buckman, B.; Serebryany, V.; Wenglowsky, S.; Kennedy, A.L.; Madduru, M.R.; Wang, B.; Lyon, M.; Doherty, G.A.; Woodard, B.T.; Lemieux, C.; Geck Do, M.; Zhang, H.; Ballard, J.; Vigers, G.; Brandhuber, B.J.; Stengel, P.; Josey, J.A.; Beigelman, L.; Blatt, L.; Seiwert, S.D. Discovery of danoprevir (ITMN-191/R7227), a highly selective and potent inhibitor of hepatitis C virus (HCV) NS3/4A protease. J. Med. Chem., 2014, 57(5), 1753-1769. [http://dx.doi.org/10.1021/jm400164c]. [PMID: 23672640].
Venkatraman, S.; Wu, W.; Prongay, A.; Girijavallabhan, V.; George Njoroge, F. Potent inhibitors of HCV-NS3 protease derived from boronic acids. Bioorg. Med. Chem. Lett., 2009, 19(1), 180-183. [http://dx.doi.org/10.1016/j.bmcl.2008.10.124]. [PMID: 19022670].
de Vicente, J.; Hendricks, R.T.; Smith, D.B.; Fell, J.B.; Fischer, J.; Spencer, S.R.; Stengel, P.J.; Mohr, P.; Robinson, J.E.; Blake, J.F.; Hilgenkamp, R.K.; Yee, C.; Adjabeng, G.; Elworthy, T.R.; Li, J.; Wang, B.; Bamberg, J.T.; Harris, S.F.; Wong, A.; Leveque, V.J.; Najera, I.; Le Pogam, S.; Rajyaguru, S.; Ao-Ieong, G.; Alexandrova, L.; Larrabee, S.; Brandl, M.; Briggs, A.; Sukhtankar, S.; Farrell, R. Non-nucleoside inhibitors of HCV polymerase NS5B. Part 4: structure-based design, synthesis, and biological evaluation of benzo[d]isothiazole-1,1-dioxides. Bioorg. Med. Chem. Lett., 2009, 19(19), 5652-5656. [http://dx.doi.org/10.1016/j.bmcl.2009.08.022]. [PMID: 19709881].
Schiering, N.; D’Arcy, A.; Villard, F.; Simic, O.; Kamke, M.; Monnet, G.; Hassiepen, U.; Svergun, D.I.; Pulfer, R.; Eder, J.; Raman, P.; Bodendorf, U. A macrocyclic HCV NS3/4A protease inhibitor interacts with protease and helicase residues in the complex with its full-length target. Proc. Natl. Acad. Sci. USA, 2011, 108(52), 21052-21056. [http://dx.doi.org/10.1073/pnas.1110534108]. [PMID: 22160684].
Abraham, M.U.; Murtola, T.; Schulz, R.; Páll, S.; Smith, J.C.; Hess, B.; Lingahl, E. Gromacs: High performance molecular simulations through multi-level paralleslism from laptotops to supercomputers. SoftwareX, 2015, 1-2, 19-25. [http://dx.doi.org/10.1016/j.softx.2015.06.001].
Berendsen, H.J.C.; Van der Spoel, D.; Van Drunem, R. GROMACS: A message-passing parallel molecular dynamics implementation. Comput. Phys. Commun., 1995, 91, 1995. [http://dx.doi.org/10.1016/0010-4655(95)00042-E].
Schüttelkopf, A.W.; van Aalten, D.M.F. PRODRG: a tool for high-throughput crystallography of protein-ligand complexes. Acta Crystallogr. D Biol. Crystallogr., 2004, 60(Pt 8), 1355-1363. [http://dx.doi.org/10.1107/S0907444904011679]. [PMID: 15272157].
Bondi, A. Van der Waals Volumes and Radii. J. Phys., 1994, 68, 441-451. [DOI: 10.1021/j100785a001].
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].
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].
Silva, F.C. (Federal University of Pernambuco, Recife, Pernambuco, Brazil).Análise ROC; , 2006.
Lorenzo, V.P.; Lúcio, A.S.; Scotti, L.; Tavares, J.F.; Filho, J.M.; Lima, T.K.; Rocha, J.D.; Scotti, M.T. Structure-and ligand-based approaches to evaluate aporphynic alkaloids from annonaceae as multi-target agent against Leishmania donovani. Curr. Pharm. Des., 2016, 22(34), 5196-5203. [http://dx.doi.org/10.2174/1381612822666160513144853]. [PMID: 27174814].
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].
Razzaghi-Asl, N.; Mirzayi, S.; Mahnam, K.; Sepehri, S. Identification of COX-2 inhibitors via structure-based virtual screening and molecular dynamics simulation. J. Mol. Graph. Model., 2018, 83, 138-152. [http://dx.doi.org/10.1016/j.jmgm.2018.05.010]. [PMID: 29936228].
Huang, H.; Hu, G.; Wang, C.; Xu, H.; Chen, X.; Qian, A. Cepharanthine, an alkaloid from stephania cepharantha hayata, inhibits the inflammatory response in the RAW264.7 cell and mouse models, 2013, 37(1), 235-246.
Toyama, M.; Hamasaki, T.; Uto, T.; Aoyama, H.; Okamoto, M.; Hashmoto, Y.; Baba, M. Synergistic inhibition of HTLV-1-infected cell proliferation by combination of cepharanthine and a tetramethylnaphthalene derivative. Anticancer Res., 2012, 32(7), 2639-2645. [PMID: 22753721].
Rogosnitzky, M.; Danks, R. Therapeutic potential of the biscoclaurine alkaloid, cepharanthine, for a range of clinical conditions. Pharmacol. Rep., 2011, 63(2), 337-347. [http://dx.doi.org/10.1016/S1734-1140(11)70500-X]. [PMID: 21602589].
Verpoorte, R.; Ruigrok, C.L.; Svendsen, A.B. Medicinal plants of Surinam. II: Antimicrobial active alkaloids from Aspidosperma marcgravianum. Planta Med., 1982, 46(3), 149-152. [http://dx.doi.org/10.1055/s-2007-970040]. [PMID: 7178295].
Zhao, M.M.; McNamara, J.M.; Ho, G.J.; Emerson, K.M.; Song, Z.J.; Tschaen, D.M.; Brands, K.M.; Dolling, U.H.; Grabowski, E.J.; Reider, P.J.; Cottrell, I.F.; Ashwood, M.S.; Bishop, B.C. Practical asymmetric synthesis of aprepitant, a potent human NK-1 receptor antagonist, via a stereoselective Lewis acid-catalyzed trans acetalization reaction. J. Org. Chem., 2002, 67(19), 6743-6747. [http://dx.doi.org/10.1021/jo0203793]. [PMID: 12227806].
Aly, Y.; Galal, A.; Wong, L.K.; Fu, E.W.; Lin, F.; Duah, F.K.; Schiff, P.L. A revision of the structure of the isoquinolone alkaloid thalflavine. Phytochemistry, 1989, 28, 1967-1971. [http://dx.doi.org/10.1016/S0031-9422(00)97896-8].
López, J.A.; Laurito, J.G.; Brenes, A.M.; Lin, F.; Sharaf, M.; Wong, L.K.; Schiff, P.L. Aporphinoid alkaloids of Guatteria oliviformis and G. Tonduzii. Phytochemistry, 1990, 29, 1899-1901. [http://dx.doi.org/10.1016/0031-9422(90)85037-G].
Talete srl, Dragon - Software for Molecular Descriptor Calculation) Version 6.0. (Available at: http://www.talete.mi.it/.
Todeschini, R.; Consonni, V. Molecular descriptors for chemoinformatics, 1st ed; Wiley-VCH, 2009. [http://dx.doi.org/10.1002/9783527628766]
Scotti, M.T.; Speck-Planche, A.; Tavares, J.F.; Sobral, M.S.; Cordeiro, M.N.S. Virtual screening of alkaloids from apocynaceae with potential antitrypanosomal activity. Curr. Bioinform., 2015, 10, 509-519. [http://dx.doi.org/10.2174/1574893610666151008011042].
Oprea, T.I. Property distribution of drug-related chemical databases. J. Comput. Aided Mol. Des., 2000, 14(3), 251-264. [http://dx.doi.org/10.1023/A:1008130001697]. [PMID: 10756480].
Walters, W.P.; Murcko, M.A. Prediction of ‘drug-likeness’. Adv. Drug Deliv. Rev., 2002, 54(3), 255-271. [http://dx.doi.org/10.1016/S0169-409X(02)00003-0]. [PMID: 11922947].
Chen, G.; Zheng, S.; Luo, X.; Shen, J.; Zhu, W.; Liu, H.; Gui, C.; Zhang, J.; Zheng, M.; Puah, C.M.; Chen, K.; Jiang, H. Focused combinatorial library design based on structural diversity, druglikeness and binding affinity score. J. Comb. Chem., 2005, 7(3), 398-406. [http://dx.doi.org/10.1021/cc049866h]. [PMID: 15877468].
Zheng, S.; Luo, X.; Chen, G.; Zhu, W.; Shen, J.; Chen, K.; Jiang, H.; Zheng, M.; Puah, C.M.; Chen, K.; Jiang, H. A new rapid and effective chemistry space filter in recognizing a druglike database. J. Chem. Inf. Model., 2005, 45(4), 856-862. [http://dx.doi.org/10.1021/ci050031j]. [PMID: 16045278].
Rishton, G.M. Nonleadlikeness and leadlikeness in biochemical screening. Drug Discov. Today, 2003, 8(2), 86-96. [http://dx.doi.org/10.1016/S1359644602025722]. [PMID: 12565011].
Veber, D.F.; Johnson, S.R.; Cheng, H.Y.; Smith, B.R.; Ward, K.W.; Kopple, K.D. Molecular properties that influence the oral bioavailability of drug candidates. J. Med. Chem., 2002, 45(12), 2615-2623. [http://dx.doi.org/10.1021/jm020017n]. [PMID: 12036371].
Wahyuni, T.S.; Utsubo, C.A.; Hotta, H. Promising anti-hepatitis c virus compounds from natural resources. Nat. Prod. Commun., 2016, 11(8), 1193-1200. [http://dx.doi.org/10.1177/1934578X1601100840]. [PMID: 30725589].
Koutsoudakis, G.; Romero-Brey, I.; Berger, C.; Pérez-Vilaró, G.; Monteiro Perin, P.; Vondran, F.W.; Kalesse, M.; Harmrolfs, K.; Müller, R.; Martinez, J.P.; Pietschmann, T.; Bartenschlager, R.; Brönstrup, M.; Meyerhans, A.; Díez, J.; Soraphen, A.; Soraphen, A. A broad-spectrum antiviral natural product with potent anti-hepatitis C virus activity. J. Hepatol., 2015, 63(4), 813-821. [http://dx.doi.org/10.1016/j.jhep.2015.06.002]. [PMID: 26070407].
Elsebai, M.F.; Koutsoudakis, G.; Saludes, V.; Pérez-Vilaró, G.; Turpeinen, A.; Mattila, S.; Pirttilä, A.M.; Fontaine-Vive, F.; Mehiri, M.; Meyerhans, A.; Díez, J. Pan-genotypic hepatitis c virus inhibition by natural products derived from the wild egyptian artichoke. J. Virol., 2015, 90(4), 1918-1930. [http://dx.doi.org/10.1128/JVI.02030-15]. [PMID: 26656684].

Rights & PermissionsPrintExport Cite as

Article Details

Year: 2019
Published on: 24 July, 2019
Page: [900 - 913]
Pages: 14
DOI: 10.2174/1568026619666190510094228
Price: $65

Article Metrics

PDF: 34
PRC: 2