The neutralization effect of montelukast on SARS-CoV-2 is shown by multiscale in silico simulations and combined in vitro studies

Serdar Durdagi, Timucin Avsar, Muge Didem Orhan, Muge Serhatli, Bertan Koray Balcioglu, Hasan Umit Ozturk, Alisan Kayabolen, Yuksel Cetin, Seyma Aydinlik, Tugba Bagci-Onder, Saban Tekin, Hasan Demirci, Mustafa Guzel, Atilla Akdemir, Seyma Calis, Lalehan Oktay, Ilayda Tolu, Yasar Enes Butun, Ece Erdemoglu, Alpsu Olkan, Nurettin Tokay, Şeyma Işık, Aysenur Ozcan, Elif Acar, Sehriban Buyukkilic, Yesim Yumak, Serdar Durdagi, Timucin Avsar, Muge Didem Orhan, Muge Serhatli, Bertan Koray Balcioglu, Hasan Umit Ozturk, Alisan Kayabolen, Yuksel Cetin, Seyma Aydinlik, Tugba Bagci-Onder, Saban Tekin, Hasan Demirci, Mustafa Guzel, Atilla Akdemir, Seyma Calis, Lalehan Oktay, Ilayda Tolu, Yasar Enes Butun, Ece Erdemoglu, Alpsu Olkan, Nurettin Tokay, Şeyma Işık, Aysenur Ozcan, Elif Acar, Sehriban Buyukkilic, Yesim Yumak

Abstract

Small molecule inhibitors have previously been investigated in different studies as possible therapeutics in the treatment of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). In the current drug repurposing study, we identified the leukotriene (D4) receptor antagonist montelukast as a novel agent that simultaneously targets two important drug targets of SARS-CoV-2. We initially demonstrated the dual inhibition profile of montelukast through multiscale molecular modeling studies. Next, we characterized its effect on both targets by different in vitro experiments including the enzyme (main protease) inhibition-based assay, surface plasmon resonance (SPR) spectroscopy, pseudovirus neutralization on HEK293T/hACE2+TMPRSS2, and virus neutralization assay using xCELLigence MP real-time cell analyzer. Our integrated in silico and in vitro results confirmed the dual potential effect of montelukast both on the main protease enzyme inhibition and virus entry into the host cell (spike/ACE2). The virus neutralization assay results showed that SARS-CoV-2 virus activity was delayed with montelukast for 20 h on the infected cells. The rapid use of new small molecules in the pandemic is very important today. Montelukast, whose pharmacokinetic and pharmacodynamic properties are very well characterized and has been widely used in the treatment of asthma since 1998, should urgently be completed in clinical phase studies and, if its effect is proved in clinical phase studies, it should be used against coronavirus disease 2019 (COVID-19).

Keywords: COVID-19; MD simulations; drug repurposing; molecular docking; montelukast; pseudovirus neutralization; virus neutralization.

Conflict of interest statement

Declaration of interests The authors declare no competing interests.

Copyright © 2021 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

Figures

Graphical abstract
Graphical abstract
Figure 1
Figure 1
Representative complex structure of montelukast at the binding pocket of the SARS-CoV-2 Mpro obtained from saved trajectories of MD simulations initiated with its covalent top-docking pose A 2D ligand interaction diagram is also shown.
Figure 2
Figure 2
Representative complex structure of montelukast at the SARS-CoV-2 spike/ACE-2 interface obtained from saved trajectories of MD simulations initiated with its noncovalent top-docking pose
Figure 3
Figure 3
(left) 3CL Protease activity in the presence of montelukast with ranging concentrations Inhibitory activity is the inhibited 3CL (Mpro) enzyme activity percentage. “No Inhibitor” represents the 3CL protease activity without any inhibitors, and GC376 inhibitor is a broad-spectrum antiviral used for comparison. (Right) Dose-response curve of montelukast against 3CL protease. Experiments are repeated at least three times.
Figure 4
Figure 4
Subtracted and correction sensograms of montelukast binding curves for 3C-like protease
Figure 5
Figure 5
Pseudovirus neutralization on HEK293T/hACE2+TMPRSS2 cells by montelukast (A) Effects of montelukast on the entry of pseudoviruses into HEK293T/hACE2+TMPRSS2 cells were examined in three ways: (1) the cell + pseudovirus was pretreated for 1 h at 37°C and then drug was added, (2) the cell + drug was pretreated for 1 h at 37°C and then pseudovirus was added, (3) the drug + pseudovirus was pretreated for 1 h at 37°C and then added to the cells. The fluorescence and luminescence levels were measured 72 h post transduction. The entry efficiency of SARS-CoV-2 pseudoviruses without any treatment was taken as 100%. Each dose was tested in triplicate and error bars indicate SEM of triplicates. (B) The representative images for the cell viability and neutralization were shown upon neutralization period, 72 h. Magnification 10×.
Figure 6
Figure 6
Real-time cell analysis result of montelukast Data were collected for 130 h with intervals of 15 min. In the different methods tested and within those three methods, the effective concentration on the SARS-CoV-2 virus was found to be 25 μM. At the end of the period, the experiment was terminated, and the data obtained were analyzed using RTCA Software Pro software. CIT50 values are presented for comparison, and the method, depicted as (cell + virus)Drug, becomes prominent, with 20 h of retention of the viral effects.

References

    1. Huang Y., Yang C., Xu X.F., Xu W., Liu S.W. Structural and functional properties of SARS-CoV-2 spike protein: potential antivirus drug development for COVID-19. Acta Pharmacol. Sin. 2020;41:1141–1149.
    1. Ahn D.G., Shin H.J., Kim M.H., Lee S., Kim H.S., Myoung J., Kim B.T., Kim S.J. Current status of epidemiology, diagnosis, therapeutics, and vaccines for novel coronavirus disease 2019 (COVID-19) J. Microbiol. Biotechnol. 2020;30:313–324.
    1. Shereen M.A., Khan S., Kazmi A., Bashir N., Siddique R. COVID-19 infection: origin, transmission, and characteristics of human coronaviruses. J. Adv. Res. 2020;24:91–98.
    1. Zhang Y.Z., Holmes E.C. A genomic perspective on the origin and emergence of SARS-CoV-2. Cell. 2020;181:223–227.
    1. Durdaği S. Virtual drug repurposing study against SARS-CoV-2 TMPRSS2 target. Turkish J. Biol. 2020;44:185–191.
    1. Durdagi S., Orhan M.D., Aksoydan B., Calis S., Dogan B., Sahin K., Shahraki A., Iyison N.B., Avsar T. Screening of clinically approved and investigation drugs as potential inhibitors of SARS-CoV-2: a combined in silico and in vitro study. Mol. Inf. 2021;40:2100062. doi: 10.1002/minf.202100062.
    1. Alyammahi S.K., Abdin S.M., Alhamad D.W., Elgendy S.M., Altell A.T., Omar H.A. The dynamic association between COVID-19 and chronic disorders: an updated insight into prevalence, mechanisms and therapeutic modalities. Infect. Genet. Evol. 2021;87:104647. doi: 10.1016/j.meegid.2020.104647.
    1. Chen G., Wu D., Guo W., Cao Y., Huang D., Wang H., Wang T., Zhang X., Chen H., Yu H., et al. Clinical and immunological features of severe and moderate coronavirus disease 2019. J. Clin. Invest. 2020;130:2620–2629.
    1. Huang C., Wang Y., Li X., Ren L., Zhao J., Hu Y., Zhang L., Fan G., Xu J., Gu X., et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395:497–506.
    1. Wan S., Yi Q., Fan S., Lv J., Zhang X., Guo L., Lang C., Xiao Q., Xiao K., Yi Z., et al. Characteristics of lymphocyte subsets and cytokines in peripheral blood of 123 hospitalized patients with 2019 novel coronavirus pneumonia (NCP) medRxiv. 2020 doi: 10.1101/2020.02.10.20021832.
    1. Diao B., Wang C., Tan Y., Chen X., Liu Y., Ning L., Chen L., Li M., Liu Y., Wang G., et al. Reduction and functional exhaustion of T cells in patients with coronavirus disease 2019 (COVID-19) Front. Immunol. 2020;11:827. doi: 10.3389/fimmu.2020.00827.
    1. Williamson E.J., Walker A.J., Bhaskaran K., Bacon S., Bates C., Morton C.E., Curtis H.J., Mehrkar A., Evans D., Inglesby P., et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature. 2020;584:430–436.
    1. Oliver B.G.G., Robinson P., Peters M., Black J. Viral infections and asthma: an inflammatory interface? Eur. Respir. J. 2014;44:1666–1681.
    1. Johnston N.W., Johnston S.L., Duncan J.M., Greene J.M., Kebadze T., Keith P.K., Roy M., Waserman S., Sears M.R. The September epidemic of asthma exacerbations in children: a search for etiology. J. Allergy Clin. Immunol. 2005;115:132–138.
    1. Zheng X.-Y., Xu Y.-J., Guan W.-J., Lin L.-F. Regional, age and respiratory-secretion-specific prevalence of respiratory viruses associated with asthma exacerbation: a literature review. Arch. Virol. 2018;163:845–853.
    1. Gentile D.A., Fireman P., Skoner D.P. Elevations of local leukotriene C4 levels during viral upper respiratory tract infections. Ann. Allergy Asthma Immunol. 2003;91:270–274.
    1. Almerie M.Q., Kerrigan D.D. The association between obesity and poor outcome after COVID-19 indicates a potential therapeutic role for montelukast. Med. Hypotheses. 2020;143:109883. doi: 10.1016/j.mehy.2020.109883.
    1. Barré J., Sabatier J.M., Annweiler C. Montelukast drug may improve COVID-19 prognosis: a review of evidence. Front. Pharmacol. 2020;11:1344. doi: 10.3389/fphar.2020.01344.
    1. Sanghai N., Tranmer G.K. Taming the cytokine storm: repurposing montelukast for the attenuation and prophylaxis of severe COVID-19 symptoms. Drug Discov. Today. 2020;25:2076–2079.
    1. Citron F., Perelli L., Deem A.K., Genovese G., Viale A. Leukotrienes, a potential target for Covid-19. Prostaglandins Leukot. Essent. Fat. Acids. 2020;161:102174. doi: 10.1016/j.plefa.2020.102174.
    1. Funk C.D., Ardakani A. A novel strategy to mitigate the hyperinflammatory response to COVID-19 by targeting leukotrienes. Front. Pharmacol. 2020;11:1214. doi: 10.3389/fphar.2020.01214.
    1. Reiss T.F., Altman L.C., Chervinsky P., Bewtra A., Stricker W.E., Noonan G.P., Kundu S., Zhang J. Effects of montelukast (MK-0476), a new potent cysteinyl leukotriene (LTD4) receptor antagonist, in patients with chronic asthma. J. Allergy Clin. Immunol. 1996;98:528–534.
    1. Altman L.C., Munk Z., Seltzer J., Noonan N., Shingo S., Zhang J., Reiss T.F. A placebo-controlled, dose-ranging study of montelukast, a cysteinyl leukotriene-receptor antagonist. J. Allergy Clin. Immunol. 1998;102:50–56.
    1. Knorr B., Holland S., Schwartz J., Douglas Rogers J., Reiss T.F. Clinical pharmacology of montelukast. Clin. Exp. Allergy Rev. 2001;1:254–260.
    1. Ikram S., Ahmad J., Durdagi S. Screening of FDA approved drugs for finding potential inhibitors against Granzyme B as a potent drug-repurposing target. J. Mol. Graph. Model. 2020;95:107642. doi: 10.1016/j.jmgm.2019.107462.
    1. Sahaboglu A., Miranda M., Canjuga D., Avci-Adali M., Savytska N., Secer E., Feria-Pliego J.A., Kayık G., Durdagi S. Drug repurposing studies of PARP inhibitors as a new therapy for inherited retinal degeneration. Cell. Mol. Life Sci. 2020;77:2199–2216.
    1. Dogan B., Durdagi S. Drug re-positioning studies for novel HIV-1 inhibitors using binary QSAR models and multi-target-driven in silico studies. Mol. Inform. 2021;40:e2000012. doi: 10.1002/minf.202000012.
    1. Duarte R.R.R., Copertino D.C., Iñiguez L.P., Marston J.L., Bram Y., Han Y., Schwartz R.E., Chen S., Nixon D.F., Powell T.R. Identifying FDA-approved drugs with multimodal properties against COVID-19 using a data-driven approach and a lung organoid model of SARS-CoV-2 entry. Mol. Med. 2021;27:105. doi: 10.1186/s10020-021-00356-6.
    1. Bharath B.R., Damle H., Ganju S., Damle L. In silico screening of known small molecules to bind ACE2 specific RBD on spike glycoprotein of SARS-CoV-2 for repurposing against COVID-19. F1000Research. 2020;9:663. doi: 10.12688/f1000research.24143.1.
    1. Jang W.D., Jeon S., Kim S., Lee S.Y. Drugs repurposed for COVID-19 by virtual screening of 6,218 drugs and cell-based assay. Proc. Natl. Acad. Sci. U S A. 2021;118 doi: 10.1073/pnas.2024302118. e2024302118.
    1. Nie J., Li Q., Wu J., Zhao C., Hao H., Liu H., Zhang L., Nie L., Qin H., Wang M., et al. Establishment and validation of a pseudovirus neutralization assay for SARS-CoV-2. Emerg. Microbes Infect. 2020;9:680–686.
    1. Durdagi S., Dag C., Dogan B., Yigin M., Avsar T., Buyukdag C., Erol I., Ertem B., Calis S., Yildirim G., et al. Near-physiological-temperature serial femtosecond X-ray crystallography reveals novel conformations of SARS-CoV-2 main protease active site for improved drug repurposing. Structure. 2021;S0969-2126:00257–264. doi: 10.1016/j.str.2021.07.007.
    1. Ramsay R.R., Popovic-Nikolic M.R., Nikolic K., Uliassi E., Bolognesi M.L. A perspective on multi-target drug discovery and design for complex diseases. Clin. Transl. Med. 2018;7:3. doi: 10.1186/s40169-017-0181-2.
    1. Witkowski P.T., Schuenadel L., Wiethaus J., Bourquain D.R., Kurth A., Nitsche A. Cellular impedance measurement as a new tool for poxvirus titration, antibody neutralization testing and evaluation of antiviral substances. Biochem. Biophys. Res. Commun. 2010;401:37–41.
    1. Charretier C., Saulnier A., Benair L., Armanet C., Bassard I., Daulon S., Bernigaud B., Rodrigues de Sousa E., Gonthier C., Zorn E., et al. Robust real-time cell analysis method for determining viral infectious titers during development of a viral vaccine production process. J. Virol. Methods. 2018;252:57–64.
    1. Teng Z., Kuang X., Wang J., Zhang X. Real-time cell analysis - a new method for dynamic, quantitative measurement of infectious viruses and antiserum neutralizing activity. J. Virol. Methods. 2013;193:364–370.
    1. Fang Y., Ye P., Wang X., Xu X., Reisen W. Real-time monitoring of flavivirus induced cytopathogenesis using cell electric impedance technology. J. Virol. Methods. 2011;173:251–258.
    1. Fidan C., Aydoğdu A. As a potential treatment of COVID-19: montelukast. Med. Hypotheses. 2020;142:109828. doi: 10.1016/j.mehy.2020.109828.
    1. Aigner L., Pietrantonio F., Bessa de Sousa D.M., Michael J., Schuster D., Reitsamer H.A., Zerbe H., Studnicka M. The leukotriene receptor antagonist montelukast as a potential COVID-19 therapeutic. Front. Mol. Biosci. 2020;7:610132. doi: 10.3389/fmolb.2020.610132.
    1. Farag A., Wang P., Ahmed M., Sadek H. Identification of FDA approved drugs targeting COVID-19 virus by structure-based drug repositioning. ChemRxiv. 2020 doi: 10.26434/chemrxiv.12003930.v3.
    1. Wu C., Liu Y., Yang Y., Zhang P., Zhong W., Wang Y., Wang Q., Xu Y., Li M., Li X., et al. Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods. Acta Pharm. Sin. B. 2020;10:766–788.
    1. Copertino D.C., Duarte R.R.R., Powell T.R., de Mulder Rougvie M., Nixon D.F. Montelukast drug activity and potential against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) J. Med. Virol. 2021;93:187–189.
    1. Neerukonda S.N., Vassell R., Herrup R., Liu S., Wang T., Takeda K., Yang Y., Lin T.L., Wang W., Weiss C.D. Establishment of a well-characterized SARSCoV-2 lentiviral pseudovirus neutralization assay using 293T cells with stable expression of ACE2 and TMPRSS2. PLoS One. 2021;16:e0248348. doi: 10.1371/journal.pone.0248348.
    1. Cifuentes-Muñoz N., Darlix J.L., Tischler N.D. Development of a lentiviral vector system to study the role of the Andes virus glycoproteins. Virus Res. 2010;153:29–35.
    1. Johnson M.C., Lyddon T.D., Suarez R., Salcedo B., LePique M., Graham M., Ricana C., Robinson C., Ritter D.G. Optimized pseudotyping conditions for the SARS-COV-2 spike glycoprotein. J. Virol. 2020;94 doi: 10.1128/JVI.01062-20. e01062–20.
    1. Xiong H.L., Wu Y.T., Cao J.L., Yang R., Liu Y.X., Ma J., Qiao X.Y., Yao X.Y., Zhang B.H., Zhang Y.L., et al. Robust neutralization assay based on SARS-CoV-2 S-protein-bearing vesicular stomatitis virus (VSV) pseudovirus and ACE2-overexpressing BHK21 cells. Emerg. Microbes Infect. 2020;9:2105–2113.
    1. Kumar S., Singh B., Kumari P., Kumar P.V., Agnihotri G., Khan S., Kant Beuria T., Syed G.H., Dixit A. Identification of multipotent drugs for COVID-19 therapeutics with the evaluation of their SARS-CoV2 inhibitory activity. Comput. Struct. Biotechnol. J. 2021;19:1998–2017.
    1. Shelley J.C., Cholleti A., Frye L.L., Greenwood J.R., Timlin M.R., Uchimaya M. Epik: a software program for pKa prediction and protonation state generation for drug-like molecules. J. Comput. Aided. Mol. Des. 2007;21:681–691.
    1. Jacobson M.P., Pincus D.L., Rapp C.S., Day T.J.F., Honig B., Shaw D.E., Friesner R.A. A hierarchical approach to all-atom protein loop prediction. Proteins Struct. Funct. Genet. 2004;55:351–367.
    1. Friesner R.A., Murphy R.B., Repasky M.P., Frye L.L., Greenwood J.R., Halgren T.A., Sanschagrin P.C., Mainz D.T. Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. J. Med. Chem. 2006;49:6177–6196.
    1. Ali A., Vijayan R. Dynamics of the ACE2–SARS-CoV-2/SARS-CoV spike protein interface reveal unique mechanisms. Sci. Rep. 2020;10:14214. doi: 10.1038/s41598-020-71188-3.
    1. Zhu K., Borrelli K.W., Greenwood J.R., Day T., Abel R., Farid R.S., Harder E. Docking covalent inhibitors: a parameter free approach to pose prediction and scoring. J. Chem. Inf. Model. 2014;54:1932–1940.
    1. Bowers K.J., Chow E., Xu H., Dror R.O., Eastwood M.P., Gregersen B.A., Klepeis J.L., Kolossvary I., Moraes M.A., Sacerdoti F.D., et al. Proceedings of the ACM/IEEE Conference on Supercomputing (SC’06), Tampa, Florida, USA. 2006. Scalable Algorithms for Molecular Dynamics Simulations on Commodity Clusters.
    1. Nosé S. A unified formulation of the constant temperature molecular dynamics methods. J. Chem. Phys. 1984;81:511–519.
    1. Hoover W.G. Canonical dynamics: equilibrium phase-space distributions. Phys. Rev. A. 1985;31:1695–1697.
    1. Martyna G.J., Tobias D.J., Klein M.L. Constant pressure molecular dynamics algorithms. J. Chem. Phys. 1994;101:4177–4189.
    1. Essmann U., Perera L., Berkowitz M.L., Darden T., Lee H., Pedersen L.G. A smooth particle mesh Ewald method. J. Chem. Phys. 1995;103:8577–8593.
    1. Harder E., Damm W., Maple J., Wu C., Reboul M., Xiang J.Y., Wang L., Lupyan D., Dahlgren M.K., Knight J.L., et al. OPLS3: a force field providing broad coverage of drug-like small molecules and proteins. J. Chem. Theor. Comput. 2016;12:281–296.
    1. Grehan K., Ferrara F., Temperton N. An optimised method for the production of MERS-CoV spike expressing viral pseudotypes. MethodsX. 2015;2:379–384.
    1. Millet J.K., Tang T., Nathan L., Jaimes J.A., Hsu H.L., Daniel S., Whittaker G.R. Production of pseudotyped particles to study highly pathogenic coronaviruses in a biosafety level 2 setting. J. Vis. Exp. 2019;145 doi: 10.3791/59010.

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