Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

A pan-serotype dengue virus inhibitor targeting the NS3–NS4B interaction

A Publisher Correction to this article was published on 20 October 2021

This article has been updated

Abstract

Dengue virus causes approximately 96 million symptomatic infections annually, manifesting as dengue fever or occasionally as severe dengue1,2. There are no antiviral agents available to prevent or treat dengue. Here, we describe a highly potent dengue virus inhibitor (JNJ-A07) that exerts nanomolar to picomolar activity against a panel of 21 clinical isolates that represent the natural genetic diversity of known genotypes and serotypes. The molecule has a high barrier to resistance and prevents the formation of the viral replication complex by blocking the interaction between two viral proteins (NS3 and NS4B), thus revealing a previously undescribed mechanism of antiviral action. JNJ-A07 has a favourable pharmacokinetic profile that results in outstanding efficacy against dengue virus infection in mouse infection models. Delaying start of treatment until peak viraemia results in a rapid and significant reduction in viral load. An analogue is currently in further development.

This is a preview of subscription content

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Identification of a molecular target of JNJ-A07.
Fig. 2: In vivo efficacy of JNJ-A07 on viraemia and survival in a prophylactic setting.
Fig. 3: In vivo efficacy of JNJ-A07 on the kinetics of DENV replication in a therapeutic setting.

Data availability

The genome sequence of DENV-2 RL is deposited at GenBank (accession MW741553). The synthesis and chemical characterization of all compounds described in this paper is provided as Supplementary Information (Supplementary Methods). The uncropped images of the western blots shown in Fig. 1, Extended Data Figs. 5 and 6 are presented in Supplementary Figs. 1–6. All data supporting the findings of this study are available within the Article, the source data or the Supplementary Information.  Source data are provided with this paper.

Code availability

A custom script43 was used to derive the amino acid composition of each sample for all coding sequences per DENV genotype, which was not specifically developed for this research but for all similar analyses. The code for the custom script is deposited as part of the pipeline VirVarSeq but is individually accessible on the Open Source software platform SourceForge at https://sourceforge.net/projects/virtools/?source=directory. The code for this specific variant detection script is ‘codon_table.pl’. Graphs and figures were generated using Microsoft PowerPoint, GraphPad Prism (v.9.0.0) or Adobe Illustrator (v.25.4.1); the software is made available by KU Leuven through a group licence. In some figures, basic templates obtained from the Servier Medical Art library (https://smart.servier.com/) were used.

Change history

References

  1. 1.

    Dengue and Severe Dengue. World Health Organization, https://www.who.int/news-room/fact-sheets/detail/dengue-and-severe-dengue (15 April 2019).

  2. 2.

    Bhatt, S. et al. The global distribution and burden of dengue. Nature 496, 504–507 (2013).

    ADS  CAS  Article  Google Scholar 

  3. 3.

    Ayukekbong, J. A., Oyero, O. G., Nnukwu, S. E., Mesumbe, H. N. & Fobisong, C. N. Value of routine dengue diagnosis in endemic countries. World J. Virol. 6, 9–16 (2017).

    Article  Google Scholar 

  4. 4.

    Paixão, E. S., Teixeira, M. G. & Rodrigues, L. C. Zika, chikungunya and dengue: the causes and threats of new and re-emerging arboviral diseases. BMJ Glob. Health 3, e000530 (2018).

    Article  Google Scholar 

  5. 5.

    Simmons, C. P., Farrar, J. J., van Nguyen, V. & Wills, B. Dengue. N. Engl. J. Med. 366, 1423–1432 (2012).

    CAS  Article  Google Scholar 

  6. 6.

    Messina, J. P. et al. The current and future global distribution and population at risk of dengue. Nat. Microbiol. 4, 1508–1515 (2019).

    CAS  Article  Google Scholar 

  7. 7.

    Duong, V. et al. Asymptomatic humans transmit dengue virus to mosquitoes. Proc. Natl Acad. Sci. USA 112, 14688–14693 (2015).

    ADS  CAS  Article  Google Scholar 

  8. 8.

    ten Bosch, Q. A. et al. Contributions from the silent majority dominate dengue virus transmission. PLoS Pathog. 14, e1006965 (2018).

    Article  Google Scholar 

  9. 9.

    Halstead, S. B. Pathogenesis of dengue: dawn of a new era. F1000Research 4, 1353 (2015).

    Article  Google Scholar 

  10. 10.

    Katzelnick, L. C. et al. Antibody-dependent enhancement of severe dengue disease in humans. Science 358, 929–932 (2017).

    ADS  CAS  Article  Google Scholar 

  11. 11.

    Dengue vaccine: WHO position paper—July 2016. Wkly Epidemiol. Rec. 91, 349-364 (2016).

  12. 12.

    Wilder-Smith, A. et al. Deliberations of the strategic advisory group of experts on immunization on the use of CYD-TDV dengue vaccine. Lancet Infect. Dis. 19, e31–e38 (2019).

    CAS  Article  Google Scholar 

  13. 13.

    Dengue vaccine: WHO position paper—September 2018. Wkly Epidemiol. Rec. 93, 457–476 (2018).

  14. 14.

    Low, J. G., Gatsinga, R., Vasudevan, S. G. & Sampath, A. In Dengue and Zika: Control and Antiviral Treatment Strategies. Advances in Experimental Medicine and Biology (eds Hilgenfeld, R. & Vasudevan, S. G.) 319–332 (Springer, 2018).

  15. 15.

    Whitehorn, J. et al. Dengue therapeutics, chemoprophylaxis, and allied tools: state of the art and future directions. PLoS Negl. Trop. Dis. 8, e3025 (2014).

    Article  Google Scholar 

  16. 16.

    Bardiot, D. et al. Discovery of indole derivatives as novel and potent dengue virus inhibitors. J. Med. Chem. 61, 8390–8401 (2018).

    CAS  Article  Google Scholar 

  17. 17.

    Schmid, M. A. & Harris, E. Monocyte recruitment to the dermis and differentiation to dendritic cells increases the targets for dengue virus replication. PLoS Pathog. 10, e1004541 (2014).

    Article  Google Scholar 

  18. 18.

    Touret, F. et al. Phylogenetically based establishment of a dengue virus panel, representing all available genotypes, as a tool in dengue drug. Antiviral Res. 168, 109–113 (2019).

    CAS  Article  Google Scholar 

  19. 19.

    Płaszczyca, A. et al. A novel interaction between dengue virus nonstructural protein 1 and the NS4A-2K–4B precursor is required for viral RNA replication but not for formation of the membranous replication organelle. PLoS Pathog. 15, e10077362019 (2019).

    Article  Google Scholar 

  20. 20.

    Chatel-Chaix, L. et al. A combined genetic–proteomic approach identifies residues within dengue virus NS4B critical for interaction with NS3 and viral replication. J. Virol. 89, 7170-7186 (2015).

    CAS  Article  Google Scholar 

  21. 21.

    Moquin, S. A. et al. NITD-688, a pan-serotype inhibitor of the dengue virus NS4B protein, shows favorable pharmacokinetics and efficacy in preclinical animal models. Sci. Transl. Med. 13, eabb2181 (2021).

    CAS  Article  Google Scholar 

  22. 22.

    Clapham, H. E., Tricou, V., Van Vinh Chau, N., Simmons, C. P. & Ferguson, N. M. Within-host viral dynamics of dengue serotype 1 infection. J. R. Soc. Interface 11, 20140094 (2014).

    Article  Google Scholar 

  23. 23.

    Sim, S. et al. Tracking dengue virus intra-host genetic diversity during human-to-mosquito transmission. PLoS Negl. Trop. Dis. 9, e0004052 (2015).

    Article  Google Scholar 

  24. 24.

    Simmons, C. P. et al. Recent advances in dengue pathogenesis and clinical management. Vaccine 33, 7061–7068 (2015).

    CAS  Article  Google Scholar 

  25. 25.

    Nguyen, N. M. et al. Host and viral features of human dengue cases shape the population of infected and infectious Aedes aegypti mosquitoes. Proc. Natl Acad. Sci. USA 110, 9072–9077 (2013).

    ADS  CAS  Article  Google Scholar 

  26. 26.

    Simmons, C. P. et al. Therapeutics for dengue: recommendations for design and conduct of early-phase clinical trials. PLoS Negl. Trop. Dis. 6, e1752 (2012).

    Article  Google Scholar 

  27. 27.

    Low, J. G., Ooi, E. E. & Vasudevan, S. G. Current status of dengue therapeutics research and development. J. Infect. Dis. 215, S96–S102 (2017).

    CAS  Article  Google Scholar 

  28. 28.

    Unlocking the Potential of Preventive Therapies for Malaria. World Health Organization, https://www.who.int/malaria/media/preventive-therapies/en/ (7 April 2017).

  29. 29.

    Zou, J. et al. Characterization of dengue virus NS4A and NS4B protein interaction. J. Virol. 89, 3455–3470 (2015).

    CAS  Article  Google Scholar 

  30. 30.

    Miller, S., Sparacio, S. & Bartenschlager, R. Subcellular localization and membrane topology of the dengue virus type 2 non-structural protein 4B. J. Biol. Chem. 281, 8854–8863 (2006).

    CAS  Article  Google Scholar 

  31. 31.

    Chatel-Chaix, L. et al. Dengue virus perturbs mitochondrial morphodynamics to dampen innate immune responses. Cell Host Microbe 20, 342–356 (2016).

    CAS  Article  Google Scholar 

  32. 32.

    Zmurko, J., Neyts, J. & Dallmeier, K. Flaviviral NS4B, chameleon and jack-in-the-box roles in viral replication and pathogenesis, and a molecular target for antiviral intervention. Rev. Med. Virol. 25, 205–223 (2015).

    CAS  Article  Google Scholar 

  33. 33.

    Umareddy, I., Chao, A., Sampath, A., Gu, F. & Vasudevan, S. G. Dengue virus NS4B interacts with NS3 and dissociates it from single-stranded RNA. J. Gen. Virol. 87, 2605–2614 (2006).

    CAS  Article  Google Scholar 

  34. 34.

    Janssen Pharmaceuticals & KU Leuven. Preparation of mono- or di-substituted derivatives as dengue viral replication inhibitors. Patent WO/2016/050841 (2016).

  35. 35.

    Janssen Pharmaceuticals & KU Leuven. Preparation of mono- or di-substituted derivatives as dengue viral replication inhibitors. Patent WO/2016/050831 (2016).

  36. 36.

    Janssen Pharmaceuticals & KU Leuven. Preparation of substituted indoline derivatives as dengue viral replication inhibitors. Patent WO/2017/167951 (2017).

  37. 37.

    Novartis. N-substituted tetrahydrothienopyridine derivatives as antiviral agents and their preparation. Patent WO/2019/244047 (2019).

  38. 38.

    Fischl, W. & Bartenschlager, R. High-throughput screening using dengue virus reporter genomes. Methods Mol. Biol. 1030, 205–219 (2013).

    CAS  Article  Google Scholar 

  39. 39.

    Aubry, F. et al. Single-stranded positive-sense RNA viruses generated in days using infectious subgenomic amplicons. J. Gen. Virol. 95, 2462–2467 (2014).

    Article  Google Scholar 

  40. 40.

    Kum, D. B. et al. A yellow fever–Zika chimeric virus vaccine candidate protects against Zika infection and congenital malformations in mice. NPJ Vaccines 3, 56 (2018).

    CAS  Article  Google Scholar 

  41. 41.

    De Burghgraeve, T. et al. 3′,5′Di-O-trityluridine inhibits in vitro flavivirus replication. Antiviral Res. 98, 242–247 (2013).

    Article  Google Scholar 

  42. 42.

    Kaptein, S. J. F. et al. A derivate of the antibiotic doxorubicin is a selective inhibitor of dengue and yellow fever virus replication in vitro. Antimicrob. Agents Chemother. 54, 5269–5280 (2010).

    CAS  Article  Google Scholar 

  43. 43.

    Verbist, B. M. et al. VirVarSeq: a low-frequency virus variant detection pipeline for Illumina sequencing using adaptive base-calling accuracy filtering. Bioinformatics 31, 94–101 (2015).

    CAS  Article  Google Scholar 

  44. 44.

    Münster, M. et al. A reverse genetics system for Zika virus based on a simple molecular cloning strategy. Viruses 10, E368 (2018).

    Article  Google Scholar 

  45. 45.

    Zmurko, J. et al. The viral polymerase inhibitor 7-deaza-2′-C-methyladenosine is a potent inhibitor of in vitro Zika virus replication and delays disease progression in a robust mouse infection model. PLoS Negl. Trop. Dis. 10, e0004695 (2016).

    Article  Google Scholar 

  46. 46.

    Jaki, T. & Wolfsegger, M. J. Estimation of pharmacokinetic parameters with the R package PK. Pharm. Stat. 10, 284–288 (2011).

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by a Seeding Drug Discovery Strategic Award from the Wellcome Trust (grant 089328/Z/09 and grant 106327/Z/14) and received funding from the Flanders Agency Innovation & Entrepreneurship (VLAIO O&O grants IWT 150863 and HBC.2019.2906). Part of this research work was performed using the ‘Caps-It’ research infrastructure (project ZW13-02) that was financially supported by the Hercules Foundation (FWO) and Rega Foundation, KU Leuven. We thank M. Flament, R. Pholien, C. De Keyzer, C. Vanderheydt, E. Maas, S. Claes and the staff at the Rega animal facility at KU Leuven; E. Peeters, S. De Bruyn, N. Verheyen, C. Van Hove, E. Coesemans, B. De Boeck, A. Beckers, P. Gysemberg, T. Loomans and K. Allaerts at Janssen Pharmaceutica; and J. Fortin, F. Doublet and P. Muller at Janssen-Cilag for technical assistance.

Author information

Affiliations

Authors

Contributions

S.J.F.K. and J.N. planned, coordinated and executed the experimental virology work at KU Leuven. O.G. and M.V.L. planned, coordinated and executed the experimental virology work at Janssen Pharmaceutica. P.G. executed the experimental virology work at Janssen Pharmaceutica. D.K., L.C.-C., M.M. and R.B. planned, coordinated and executed the experimental virology work at Heidelberg University. D.B. planned, coordinated and executed the medicinal chemistry work at Cistim. K.D. did experimental work at KU Leuven and advised on the design of experiments. K.T. performed whole-genome sequence analysis at Janssen Pharmaceutica. M.C. performed the statistical analyses at Janssen Pharmaceutica. G.Q., F.T. and X.d.L. planned, coordinated and executed the experimental work at UVE. B.K., J.-F.B., T.H.M.J. and P.R. planned, coordinated and executed the medicinal chemistry work at Janssen Pharmaceutica. B.S. planned and coordinated the pharmacokinetics and pharmacodynamics work at Janssen Pharmaceutica. A.M. and P.C. coordinated and guided the experimental medicinal chemistry work at CD3. P.C. and J.N. designed and initiated the project. K.S. and M.V.L. initiated the project at Janssen Pharmaceutica. J.N., P.C., A.M., S.J.F.K., O.G., R.B., M.V.L. and K.S. secured funding from external organizations. S.J.F.K., O.G., M.V.L. and J.N. wrote the manuscript with contributions from K.S., D.K. and R.B., and comments from all authors.

Corresponding authors

Correspondence to Marnix Van Loock or Johan Neyts.

Ethics declarations

Competing interests

S.J.F.K., O.G., A.M., B.K., J.-F.B., D.B., B.S., T.H.M.J., K.D., P.R., K.S., P.C., M.V.L. and J.N. have filed a patent application claiming the discovery of this class of antiviral molecules as DENV replication inhibitors (WO/2017/167951). The other authors declare no competing interests.

Additional information

Peer review information Nature thanks Brett Lindenbach, R. Guy and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Dose-response curves of the antiviral activity of JNJ-A07 against DENV-2 on various cell types.

a-f, The antiviral effect (% Inhibition viral RNA replication, % Inhibition eGFP expression, or % Inhibition of infected cells) is depicted by white dots. The effect of JNJ-A07 on cell growth is depicted by grey dots. Assays were performed on Vero cells (a and c), Huh-7 hepatoma cells (b), C6/36 mosquito cells (d), human monocytic leukemia THP-1 cells expressing the DC-SIGN receptor (e), and immature dendritic cells (imDCs) (f). Cells were infected with either the DENV-2/16681/eGFP strain (a-b, e), DENV-2/16681 (f) or the DENV-2 RL strain (c-d). Data represent mean values ± s.d. from two (for Vero and C6/36 cells using DENV-2 RL, and for imDCs using DENV-2/16681), three (for THP-1/DC-SIGN cells using DENV-2/16681), and at least five (for Vero and Huh-7 cells using DENV-2/16681) independent experiments.

Source data

Extended Data Fig. 2 JNJ-A07 is highly specific for DENV.

a, Antiviral activity of JNJ-A07 against various of RNA and DNA viruses. CHIKV, chikungunya virus; HadV, human adenovirus; HBV, hepatitis B virus; HCV, hepatitis C virus; HIV, human immunodeficiency virus; hRV, human rhinovirus; IVA, influenza virus A; IVB, influenza virus B; RSV, respiratory syncytial virus; rVSV, recombinant vescular stomatitis virus; VACV, vaccinia virus; JEV, Japanese encephalitis virus; WNV, West Nile virus; YFV, yellow fever virus; ZIKV, Zika virus. ND, not determined. b, NS4B sequence alignment of related flaviviruses. The NS4B protein sequence of DENV-2/16681 was aligned with corresponding sequences from JEV strain JEV CNS769 Laos 2009 (GenBank KC196115), tick-borne encephalitis virus strain Oshima 5.10 polyprotein gene (GenBank MF374487), WNV isolate R94224 CDC polyprotein gene (GenBank MF004388), YFV isolate Bolivia 88 1999 polyprotein gene (GenBank MF004382) and ZIKV strain HPF 2013 (GenBank KJ776791) using Clustal Omega Version 2.1. Post-processing was conducted with Jalview 2.11.1.3. The DENV NS4B topology model was added manually based on Miller et al.30. Black arrowheads are pointing at locations associated with compound-resistance.

Source data

Extended Data Fig. 3 Time-of-drug-addition and in vitro resistance selection.

a, Experimental setup of the time-of-drug-addition assay (TOA). b, TOA and in vitro kinetics of DENV-2 replication. In vitro DENV RNA replication in the absence of compound is depicted by the red curve. Onset of intracellular viral replication is at 10 h post-infection (p.i.), as shown in the inset. The inhibitory effect of JNJ-A07 on DENV replication when added at different time points p.i. is depicted by the blue curves (0.0001 µM, light blue; 0.001 µM, dark blue). The broad-spectrum RNA virus inhibitor 7-deaza-2’-C-methyladenosine (7DMA) served as positive control (black curve with white circles). Data (mean ± s.d.) from at least three independent experiments. c, Experimental approach of in vitro resistance selection. d-e, The dynamics of appearance of mutations was studied using whole genome sequencing. JNJ-A07 selected for mutations in NS4B, which were not present in the wild-type (WT) viruses that were passaged along without any drug pressure, of two independently selected resistant strains. Results for the A and B sample are shown in (d-e), respectively. Each coloured line shows the dynamics of appearance of a certain mutation during passaging of the virus in presence of JNJ-A07; the mutation is depicted in the same colour. Whole genome sequencing was performed on DENV variants harvested at every 5th passage (P) and at the end of the experiment (i.e., passage 43). One passage represents a one-week time span. The dotted line represents the cut off (15%) for the detection of variants compared with WT in the virus population. The increasing EC50 values, as determined by microscopic evaluation of virus-induced CPE, are depicted below the graphs. f, Mutations in DENV NS4B identified at end point after in vitro resistance selection using JNJ-A07 and Analogue 1. g, Natural occurrence of the NS4B mutations in clinical isolates.

Source data

Extended Data Fig. 4 Replication properties of resistant subgenomic replicons and DENV strains.

a, Schematic representation of the subgenomic DENV-2/16681 reporter replicon sgDVs-R2A38. b, Effect of resistance mutations in NS4B on replication fitness. Resistance mutations identified in Extended Data Fig. 3 were introduced into sgDVs-R2A. A replication-deficient replicon containing an inactivating mutation in the NS5 RNA-dependent RNA polymerase domain (GND) served as negative control. Huh-7 cells were transfected with in vitro transcribed RNA of WT or mutant sgDVs-R2A and lysed at the time points given at the top right and Renilla luciferase activity was measured as marker of replication. Relative light units (RLU) were normalized to the 4 h value, reflecting transfection efficiency. Plotted are the mean ± s.d. from at least three independent experiments, each carried out with independent RNA preparations. c, In vitro growth kinetics of resistant DENV (blue bars) compared to WT DENV (grey bars) on Vero E6 cells for the A sample. The virus titer in the supernatant was determined by plaque assay. d, In vitro growth kinetics of resistant DENV (blue bars) compared to WT DENV (grey bars) on C6/36 cells for the A sample. Viral RNA load in the supernatant was determined by RT-qPCR. e, Infectious virus on day 11 p.i. in the supernatant of C6/36 cells infected with resistant DENV (blue bars) or WT DENV (grey bars) for the A sample, as determined by plaque assay. f, In vitro growth kinetics of resistant DENV (dark blue bars) compared to WT DENV (light grey bars) on C6/36 cells for the B sample. Viral RNA load in the supernatant collected on day 1–10 p.i. was determined by RT-qPCR. Data are from a single experiment (d-f) or mean values ± s.d. from three independent experiments (c). LOD, limit of detection; LLOQ, lowest limit of quantification.

Source data

Extended Data Fig. 5 Impact of JNJ-A07 on the interaction between NS3 and various NS4B species.

a, Experimental design to study the impact of JNJ-A07 on the interaction between NS3 and WT or mutant NS4B. b, Captured protein complexes were analyzed by Western blot. A representative Western blot is shown. c-d, Western blot analysis to determine the NS3-NS4B interaction strength. The uncropped images of b-d are presented in Supplementary Fig. 1-3. Numbers on the left are molecular weights (kDa). GAPDH served as loading control for cell lysates (input). e-g, Signal intensities (from three independent blots) of NS3, NS4A-2K-NS4B, 2K-NS4B and NS4B were normalized to WT NS4A-2K-NS4B-HACt in DMSO-treated control cells. Protein ratios (mean ± s.e.m.) were calculated for each sample. Repeated measures one-way ANOVA with subsequent Dunnett’s multiple comparisons test was used for statistical analysis. ns, not significant. h-j, Protein intensities (mean ± s.e.m.; three independent experiments) for WT (h) and compound-resistant NS4B-mutants V91A (i) and T108I (j), normalized to an untreated WT control. For statistical analysis, JNJ-A07-treated samples were compared with the corresponding untreated control (left of the dashed line) using ordinary one-way ANOVA with subsequent Dunnett’s multiple comparisons test. k, EC50 values (mean ± s.e.m.) for protein ratios in (e-g) obtained by fitting four-parameter dose-response curves to the results from each individual experiment. Fold change in EC50 is the ratio between the mean EC50 for WT and the respective mutant constructs. l, JNJ-A07 potentially slows down the processing dynamics of the NS4A-2K-NS4B precursor (illustrated by the hourglass icon), which is first cleaved by the NS2B-NS3 protease at the NS4A-2K cleavage site. 2K-NS4B is subsequently processed by the host signal peptidase complex into mature NS4B and 2K.

Source data

Extended Data Fig. 6 JNJ-A07 does not disrupt existing NS3–NS4B complexes.

a, Experimental setup to study the kinetics of JNJ-A07-induced block of the NS3–NS4B interaction. b, Impact of JNJ-A07 on forming or pre-formed NS3–NS4B complexes. Huh-7 T7 NS2B-NS3 cells treated with 0.035 µM JNJ-A07 or equal amounts of DMSO were harvested at 1, 8, or 24 h after drug addition. Lysates were subjected to HA-specific pull-down and analyzed by Western blot (enrichment factor 5). A representative Western blot is shown. Numbers on the left represent molecular weights (kDa). c, Experimental setup of the in cellulo assay, in which Huh-7 cells were infected with DENV-2(NS4B-HA*)20 at an MOI of 1. At 48 h p.i., cells were treated for given periods with 500 nM of Analogue 2 or DMSO. d, NS3–NS4B complexes were enriched by NS4B-HA* pull-down and total lysates (input) and immune complexes (pull-down) were analysed by Western blot. NS3/NS4B ratios (depicted below the picture) were normalized to non-drug treated samples (n = 1). e, Experimental setup of the in vitro drug assay to investigate the effect of the drug on established NS3–NS4B complexes. Cell lysates were treated with 1 µM of Analogue 2 or equal amounts of DMSO added to the lysis buffer and incubated for 2 h at different temperatures in order to test complex stability. Subsequently, NS4B-HACt pull-down was performed. f, Western blot analysis (n = 1) analogous to the one shown in (d). The lower protein amount observed with the sample incubated at 37 °C was most likely due to proteolytic degradation in spite of adding protease inhibitors. For uncropped images of the representative blots in (b, d, f), see Supplementary Fig. 4-6. GAPDH (b, f) or β-actin (d) served as loading control for cell lysates (input).

Source data

Extended Data Fig. 7 In vivo efficacy of JNJ-A07 on viral RNA and cytokine levels.

a-c, Inhibitory effect of JNJ-A07 on viral RNA levels in spleen (a), kidney (b) and liver (c) on day 3 p.i. from AG129 mice treated twice-daily with 30 (white dots), 10 (light blue dots), 3 (dark blue dots) or 1 (grey dots) mg/kg JNJ-A07, as compared to vehicle-treated mice (red dots). Data are from two independent studies with n = 8 per group in each study. d-g, IL-18 (d), IFNγ (e), TNF (f), and IL-6 (g) levels in plasma on day 3 p.i. (from one of the viremia studies in Fig. 2b). h, Inhibitory effect of JNJ-A07 on viral RNA levels in plasma on day 3 p.i. in the survival study (also see Fig. 2c). Dosing groups were similar to those in (a-c). Treatment started 1 h before infection. Mice were injected with the Anti-Flavivirus antibody one day before infection. Data are from one study with n = 10 per group. i, Inhibitory effect of NITD-688 on viral RNA levels on day 3 p.i. in AG129 mice treated twice-daily with 100 (yellow dots), 30 (white dots), 10 (light blue dots) or 3 (dark blue dots) mg/kg NITD-688, as compared to vehicle-treated mice (red dots). Treatment started 1 h before infection. Data are from one study with n = 8 per group. Individual data and median values are presented. Undetermined Ct values were imputed at a Ct value of 40 (which is the LOD), corresponding to 2.6 log10 viral RNA copies/mL. Statistical analysis was performed using the two-sided Kruskal-Wallis test (a-c, i) or a Tobit regression model (h). P values were adjusted using the Holm’s (a-c), Dunn’s (d-g) or Bonferroni’s (h-i) multiple comparisons correction method. ns, not significant, as compared to vehicle-treated mice. LLOQ, lowest level of quantification.

Source data

Extended Data Fig. 8 Efficacy of JNJ-A07 in the in vivo kinetics study.

a, Schematic outline of the in vivo kinetics study. Each treatment group was sub-divided in group A and B (n = 8, per group) for blood collection on alternating days. b, Weight curves (mean values ± s.d.) of AG129 mice for the different treatment groups during the in vivo kinetics study (two independent studies). Colours of the dots represent the different treatment groups, as specified in (c-g). c-g, Inhibitory effect of JNJ-A07 on viremia on various days p.i. in mice treated twice-daily with 30 mg/kg (white dots, n = 8), 10 mg/kg (light blue dots, n = 8), 3 mg/kg (dark blue dots, n = 16), 1 mg/kg (grey dots, n = 8), or 0.3 mg/kg (green dots, n = 8) JNJ-A07, as compared to vehicle-treated mice (red dots, n = 16). Treatment was initiated 1 h before intraperitoneal infection. Data (median ± s.d.) are from two independent studies. Undetermined Ct values were imputed at a Ct value of 40 (which is the limit of detection), corresponding to 2.6 log10 viral RNA copies/mL. The mean AUC value and 95% CI was determined for each group. In case the CIs did not overlap, groups were considered to differ markedly. LLOQ, lowest level of quantification.

Source data

Extended Data Table 1 Antiviral activity of analogues of JNJ-A07 and NITD-688 against DENV-2
Extended Data Table 2 Pharmacokinetic properties of JNJ-A07 in mice and rats after intravenous (a) and oral (b) dosing

Supplementary information

Supplementary Information

This file contains Supplementary Methods and Supplementary Figs. 1–6.

Reporting Summary

Peer Review File

Source data

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Kaptein, S.J.F., Goethals, O., Kiemel, D. et al. A pan-serotype dengue virus inhibitor targeting the NS3–NS4B interaction. Nature 598, 504–509 (2021). https://doi.org/10.1038/s41586-021-03990-6

Download citation

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing