Skip to main content

Thank you for visiting 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.

Repurposing human kinase inhibitors to create an antibiotic active against drug-resistant Staphylococcus aureus, persisters and biofilms


New drugs are desperately needed to combat methicillin-resistant Staphylococcus aureus (MRSA) infections. Here, we report screening commercial kinase inhibitors for antibacterial activity and found the anticancer drug sorafenib as major hit that effectively kills MRSA strains. Varying the key structural features led to the identification of a potent analogue, PK150, that showed antibacterial activity against several pathogenic strains at submicromolar concentrations. Furthermore, this antibiotic eliminated challenging persisters as well as established biofilms. PK150 holds promising therapeutic potential as it did not induce in vitro resistance, and shows oral bioavailability and in vivo efficacy. Analysis of the mode of action using chemical proteomics revealed several targets, which included interference with menaquinone biosynthesis by inhibiting demethylmenaquinone methyltransferase and the stimulation of protein secretion by altering the activity of signal peptidase IB. Reduced endogenous menaquinone levels along with enhanced levels of extracellular proteins of PK150-treated bacteria support this target hypothesis. The associated antibiotic effects, especially the lack of resistance development, probably stem from the compound’s polypharmacology.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Antibacterial properties of SFN and PK150.
Fig. 2: Target identification by chemical proteomic profiling in S. aureus.
Fig. 3: Validation of cellular targets with putative roles in the antibiotic mechanism.
Fig. 4: SAR study of SFN and mode of action analysis by chemical proteomics.
Fig. 5: FESEM and TEM of S. aureus NCTC 8325.
Fig. 6: In-depth analysis of SFN-resistant S. aureus isolates and accompanying consequences for compound-induced SpsB stimulation.
Fig. 7: Pharmacokinetic and pharmacodynamic parameters of PK150 and in vivo efficacy.

Data availability

The mass spectrometry proteomics data have been deposited at the ProteomeXchange Consortium via the PRIDE59 partner repository with the dataset identifier PXD012946. Whole-genome sequencing data and metadata are available on the SRA repository under the Bioproject number PRJNA525411. Bacterial strains and plasmids used in this work are readily available from the authors, or can be purchased commercially as stated in the Supplementary Information.

Code availability

All computer code used is either publicly available software, described in prior publications31 or available from the authors upon request. For details on the versions and parameters used, please refer to the respective sections in the Supplementary Information.


  1. 1.

    Cassini, A. et al. Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European Economic Area in 2015: a population-level modelling analysis. Lancet Infect. Dis. 19, 56–66 (2019).

    PubMed  PubMed Central  Google Scholar 

  2. 2.

    Tacconelli, E. et al. Discovery, research, and development of new antibiotics: the WHO priority list of antibiotic-resistant bacteria and tuberculosis. Lancet Infect. Dis. 18, 318–327 (2018).

    PubMed  Google Scholar 

  3. 3.

    Tong, S. Y. C., Davis, J. S., Eichenberger, E., Holland, T. L. & Fowler, V. G. Staphylococcus aureus infections: epidemiology, pathophysiology, clinical manifestations, and management. Clin. Microbiol. Rev. 28, 603–661 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Harms, A., Maisonneuve, E. & Gerdes, K. Mechanisms of bacterial persistence during stress and antibiotic exposure. Science 354, aaf4268 (2016).

    PubMed  Google Scholar 

  5. 5.

    Ling, L. L. et al. A new antibiotic kills pathogens without detectable resistance. Nature 517, 455–459 (2015).

    CAS  PubMed  Google Scholar 

  6. 6.

    Sass, P. et al. Antibiotic acyldepsipeptides activate ClpP peptidase to degrade the cell division protein FtsZ. Proc. Natl Acad. Sci. USA 108, 17474–17479 (2011).

    CAS  PubMed  Google Scholar 

  7. 7.

    Smith, P. A. et al. Optimized arylomycins are a new class of Gram-negative antibiotics. Nature 561, 189–194 (2018).

    CAS  PubMed  Google Scholar 

  8. 8.

    Kurosu, M. & Begari, E. Bacterial protein kinase inhibitors. Drug Dev. Res 71, 168–187 (2010).

    CAS  Google Scholar 

  9. 9.

    Miller, J. R. et al. A class of selective antibacterials derived from a protein kinase inhibitor pharmacophore. Proc. Natl Acad. Sci. USA 106, 1737–1742 (2009).

    CAS  PubMed  Google Scholar 

  10. 10.

    Chang, H.-C. et al. In vitro and in vivo activity of a novel sorafenib derivative SC5005 against MRSA. J. Antimicrob. Chemother. 71, 449–459 (2016).

    CAS  PubMed  Google Scholar 

  11. 11.

    Roberts, J. L. et al. GRP78/DNA K is a target for Nexavar/Stivarga/Votrient in the treatment of human malignancies, viral infections and bacterial diseases. J. Cell. Physiol. 230, 2552–2578 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Pujol, E. et al. Pentafluorosulfanyl-containing triclocarban analogues with potent antimicrobial activity. Molecules 23, 2853 (2018).

    PubMed Central  Google Scholar 

  13. 13.

    Walsh, S. E. et al. Activity and mechanisms of action of selected biocidal agents on Gram-positive and -negative bacteria. J. Appl. Microbiol. 94, 240–247 (2003).

    CAS  PubMed  Google Scholar 

  14. 14.

    Conlon, B. P. et al. Activated ClpP kills persisters and eradicates a chronic biofilm infection. Nature 503, 365–370 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Springer, M. T., Singh, V. K., Cheung, A. L., Donegan, N. P. & Chamberlain, N. R. Effect of clpP and clpC deletion on persister cell number in Staphylococcus aureus. J. Med. Microbiol. 65, 848–857 (2016).

    CAS  PubMed  Google Scholar 

  16. 16.

    Waters, E. M., Rowe, S. E., O’Gara, J. P. & Conlon, B. P. Convergence of Staphylococcus aureus persister and biofilm research: can biofilms be defined as communities of adherent persister cells? PLoS Pathog. 12, e1006012 (2016).

    PubMed  PubMed Central  Google Scholar 

  17. 17.

    Hamamoto, H. et al. Lysocin E is a new antibiotic that targets menaquinone in the bacterial membrane. Nat. Chem. Biol. 11, 127–133 (2015).

    CAS  PubMed  Google Scholar 

  18. 18.

    Evans, M. J. & Cravatt, B. F. Mechanism-based profiling of enzyme families. Chem. Rev. 106, 3279–3301 (2006).

    CAS  PubMed  Google Scholar 

  19. 19.

    Fonović, M. & Bogyo, M. Activity-based probes as a tool for functional proteomic analysis of proteases. Expert Rev. Proteomics 5, 721–730 (2008).

    PubMed  PubMed Central  Google Scholar 

  20. 20.

    Kleiner, P., Heydenreuter, W., Stahl, M., Korotkov, V. S. & Sieber, S. A. A whole proteome inventory of background photocrosslinker binding. Angew. Chem. Int. Ed. 56, 1396–1401 (2017).

    CAS  Google Scholar 

  21. 21.

    Boersema, P. J., Raijmakers, R., Lemeer, S., Mohammed, S. & Heck, A. J. R. Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics. Nat. Protoc. 4, 484–494 (2009).

    CAS  PubMed  Google Scholar 

  22. 22.

    Rao, C. V. S., Waelheyns, E. D., Economou, A. & Anné, J. Antibiotic targeting of the bacterial secretory pathway. Biochim. Biophys. Acta 1843, 1762–1783 (2014).

    Google Scholar 

  23. 23.

    Cox, J. et al. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol. Cell. Proteomics 13, 2513–2526 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Boersch, M., Rudrawar, S., Grant, G. & Zunk, M. Menaquinone biosynthesis inhibition: a review of advancements toward a new antibiotic mechanism. RSC Adv. 8, 5099–5105 (2018).

    CAS  Google Scholar 

  25. 25.

    Kurosu, M. & Begari, E. Vitamin K2 in electron transport system: are enzymes involved in vitamin K2 biosynthesis promising drug targets? Molecules 15, 1531–1553 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Fey, P. D. et al. A genetic resource for rapid and comprehensive phenotype screening of nonessential Staphylococcus aureus genes. mBio 4, e00537 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Craney, A., Dix, M. M., Adhikary, R., Cravatt, B. F. & Romesberg, F. E. An alternative terminal step of the general secretory pathway in Staphylococcus aureus. mBio 6, e01178 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Benkovic, S. J. et al. Identification of borinic esters as inhibitors of bacterial cell growth and bacterial methyltransferases, CcrM and MenH. J. Med. Chem. 48, 7468–7476 (2005).

    CAS  PubMed  Google Scholar 

  29. 29.

    Rao, C. V. S. et al. Enzymatic investigation of the Staphylococcus aureus type I signal peptidase SpsB—implications for the search for novel antibiotics. FEBS J. 276, 3222–3234 (2009).

    PubMed  Google Scholar 

  30. 30.

    Therien, A. G. et al. Broadening the spectrum of β-lactam antibiotics through inhibition of signal peptidase type I. Antimicrob. Agents Chemother. 56, 4662–4670 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Antes, I. DynaDock: a new molecular dynamics-based algorithm for protein–peptide docking including receptor flexibility. Proteins 78, 1084–1104 (2010).

    CAS  PubMed  Google Scholar 

  32. 32.

    Craney, A. & Romesberg, F. E. The inhibition of type I bacterial signal peptidase: biological consequences and therapeutic potential. Bioorg. Med. Chem. Lett. 25, 4761–4766 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Smith, P. A. & Romesberg, F. E. Mechanism of action of the arylomycin antibiotics and effects of signal peptidase I inhibition. Antimicrob. Agents Chemother. 56, 5054–5060 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Walsh, S. I., Craney, A. & Romesberg, F. E. Not just an antibiotic target: exploring the role of type I signal peptidase in bacterial virulence. Bioorg. Med. Chem. 24, 6370–6378 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Schallenberger, M. A., Niessen, S., Shao, C., Fowler, B. J. & Romesberg, F. E. Type I signal peptidase and protein secretion in Staphylococcus aureus. J. Bacteriol. 194, 2677–2686 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. 36.

    Chao, M. C. et al. Protein complexes and proteolytic activation of the cell wall hydrolase RipA regulate septal resolution in mycobacteria. PLoS Pathog. 9, e1003197 (2013).

    PubMed  PubMed Central  Google Scholar 

  37. 37.

    Frankel, M. B., Hendrickx, A. P. A., Missiakas, D. M. & Schneewind, O. LytN, a murein hydrolase in the cross-wall compartment of Staphylococcus aureus, is involved in proper bacterial growth and envelope assembly. J. Biol. Chem. 286, 32593–32605 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Pinho, M. G., Kjos, M. & Veening, J.-W. How to get (a)round: mechanisms controlling growth and division of coccoid bacteria. Nat. Rev. Microbiol. 11, 601–614 (2013).

    CAS  PubMed  Google Scholar 

  39. 39.

    Makhlin, J. et al. Staphylococcus aureus ArcR controls expression of the arginine deiminase operon. J. Bacteriol. 189, 5976–5986 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Ernst, C. M. & Peschel, A. Broad-spectrum antimicrobial peptide resistance by MprF-mediated aminoacylation and flipping of phospholipids. Mol. Microbiol 80, 290–299 (2011).

    CAS  PubMed  Google Scholar 

  41. 41.

    Jones, T. et al. Failures in clinical treatment of Staphylococcus aureus infection with daptomycin are associated with alterations in surface charge, membrane phospholipid asymmetry, and drug binding. Antimicrob. Agents Chemother. 52, 269–278 (2008).

    CAS  PubMed  Google Scholar 

  42. 42.

    Roy, H. Tuning the properties of the bacterial membrane with aminoacylated phosphatidylglycerol. IUBMB Life 61, 940–953 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Médard, G. et al. Optimized chemical proteomics assay for kinase inhibitor profiling. J. Proteome Res. 14, 1574–1586 (2015).

    PubMed  Google Scholar 

  44. 44.

    Fish, D. N. & Chow, A. T. The clinical pharmacokinetics of levofloxacin. Clin. Pharmacokinet. 32, 101–119 (1997).

    CAS  PubMed  Google Scholar 

  45. 45.

    Scaglione, F., Mouton, J. W., Mattina, R. & Fraschini, F. Pharmacodynamics of levofloxacin and ciprofloxacin in a murine pneumonia model: peak concentration/MIC versus area under the curve/MIC ratios. Antimicrob. Agents Chemother. 47, 2749–2755 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Nosengo, N. Can you teach old drugs new tricks? Nature 534, 314–316 (2016).

    PubMed  Google Scholar 

  47. 47.

    Xu, H. H. et al. Staphylococcus aureus TargetArray: comprehensive differential essential gene expression as a mechanistic tool to profile antibacterials. Antimicrob. Agents Chemother. 54, 3659–3670 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. 48.

    Wan, P. T. C. et al. Mechanism of activation of the RAF-ERK signaling pathway by oncogenic mutations of B-RAF. Cell 116, 855–867 (2004).

    CAS  PubMed  Google Scholar 

  49. 49.

    Wu, P., Nielsen, T. E. & Clausen, M. H. FDA-approved small-molecule kinase inhibitors. Trends Pharmacol. Sci. 36, 422–439 (2015).

    CAS  PubMed  Google Scholar 

  50. 50.

    Sukheja, P. et al. A novel small-molecule inhibitor of the Mycobacterium tuberculosis demethylmenaquinone methyltransferase MenG is bactericidal to both growing and nutritionally deprived persister cells. mBio 8, e02022 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. 51.

    Paetzel, M., Dalbey, R. E. & Strynadka, N. C. J. Crystal structure of a bacterial signal peptidase in complex with a β-lactam inhibitor. Nature 396, 186–190 (1998).

    CAS  PubMed  Google Scholar 

  52. 52.

    Dreisbach, A., van Dijl, J. M. & Buist, G. The cell surface proteome of Staphylococcus aureus. Proteomics 11, 3154–3168 (2011).

    CAS  PubMed  Google Scholar 

  53. 53.

    Gatlin, C. L. et al. Proteomic profiling of cell envelope-associated proteins from Staphylococcus aureus. Proteomics 6, 1530–1549 (2006).

    CAS  PubMed  Google Scholar 

  54. 54.

    Hempel, K. et al. Quantitative cell surface proteome profiling for SigB-dependent protein expression in the human pathogen Staphylococcus aureus via biotinylation approach. J. Proteome Res. 9, 1579–1590 (2010).

    CAS  PubMed  Google Scholar 

  55. 55.

    Eirich, J. et al. Pretubulysin derived probes as novel tools for monitoring the microtubule network via activity-based protein profiling and fluorescence microscopy. Mol. BioSyst. 8, 2067–2075 (2012).

    CAS  PubMed  Google Scholar 

  56. 56.

    Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. 57.

    Cox, J. et al. Andromeda: a peptide search engine integrated into the MaxQuant environment. J. Proteome Res. 10, 1794–1805 (2011).

    CAS  PubMed  Google Scholar 

  58. 58.

    Vizcaíno, J. A. et al. 2016 update of the PRIDE database and its related tools. Nucleic Acids Res. 44, 11033–11033 (2016).

    PubMed  PubMed Central  Google Scholar 

  59. 59.

    Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 13, 731–740 (2016).

    CAS  Google Scholar 

  60. 60.

    Finn, R. D. et al. The Pfam protein families database: towards a more sustainable future. Nucleic Acids Res. 44, D279–D285 (2016).

    CAS  PubMed  Google Scholar 

  61. 61.

    Nielsen, H. Predicting secretory proteins with SignalP. Methods Mol. Biol. 1611, 59–73 (2017).

    CAS  PubMed  Google Scholar 

Download references


We thank the Network on Antimicrobial Resistance in Staphylococcus aureus (NARSA) for the supply of the Nebraska Transposon Mutant Library (NTML). Furthermore, we thank S. Grond for providing arylomycin and F. Romesberg for providing S. aureus N315 ARC0001ΔSpsB. We also thank S. Miami and E. Rubin for determining the antimicrobial activities against M. tuberculosis. We thank A. Klaschwitz, F. Kortmann, S. Hifinger and C. Lierse von Gostomski for the scintillation measurement of radioactively labelled menaquinone. S.A.S. was funded by the Center for Integrated Protein Science Munich (CIPSM), Deutsche Forschungsgemeinschaft SFB1035 and European Research Council (ERC) and the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 725085, CHEMMINE, ERC consolidator grant). E.K. was supported by a doctoral fellowship of the Fonds der Chemischen Industrie. R.M. was supported by a doctoral fellowship of the Boehringer Ingelheim Fonds. K.R. was supported by the German Centre for Infection Research (DZIF) (TTU 09.710). I.A. acknowledges funding by Deutsche Forschungsgemeinschaft SFB1035. W.M.W. was funded by the National Science Foundation (CHE-1454116) and the National Institute of General Medical Sciences (R35 GM119426). M.C.J. acknowledges a National Science Foundation predoctoral grant (DGE-1144462). S.M.H. acknowledges financial support by a Liebig fellowship of the Fonds der Chemischen Industrie. M.W.H., C.F. and F.A.M.M. were funded by the Federal Ministry for Education and Research (BMBF) under the framework programme ‘VIP+’—project ‘aBacter’. We thank D. Mostert for excellent experimental support, M. Wolff, K. Bäuml, K. Gliesche, L. Nguyen and J. Schreiber for excellent technical support and M. Stahl for critical comments on the manuscript.

Author information




P.L., E.K., R.M. and S.A.S. designed the experiments, interpreted the results and wrote the manuscript with input from all the authors. P.L. synthesized the library compounds and probes and performed SAR studies. V.S.K. assisted in the chemical synthesis of the AfBPP probes. E.K. and P.L. performed gel- and MS-based labelling and analysis of the MS data, as well as SpsB target deconvolution and validation experiments. E.K. analysed mass spectrometry-based data and conducted bioinformatics analyses. R.M. performed target identification, MS data analysis and validation experiments in the context of the menaquinone biosynthesis pathway and assisted in further validation experiments. E.K., P.L. and S.M.H. performed the bacterial resistance development studies. E.K. carried out persister assays and time-kill assays. M.W.H., C.F. and F.A.M.M. performed time-kill assays as well as biofilm and persister studies. M.C.J. and W.M.W. helped in the biofilm studies. J.L. performed microbiological studies in mycobacteria. D.C.-M. and D.H.P. conducted the whole-genome sequencing of resistant bacterial isolates and analysed the related data. I.U. and I.A. performed molecular docking and dynamic studies and interpreted the related data. K.R. and M.Rohde performed electron microscopy studies and analysed the related data. M.Reinecke and B.K. performed kinobead pull-down experiments and analysed the related data. K.R. and E.M. performed animal studies and analysed the related data.

Corresponding author

Correspondence to Stephan A. Sieber.

Ethics declarations

Competing interests

P.L., E.K. and S.A.S. are co-inventors on a European patent (EP 16 171 906.7) that covers the structure of PK150. All the other authors declare no competing interests.

Additional information

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

Supplementary information

Supplementary Information

Reporting Summary

Supplementary Data 1

Kinase inhibitor and SFN analogues libraries.

Supplementary Data 2

Antibacterial activities.

Supplementary Data 3

Target identification related proteomic data.

Supplementary Data 4

Proteome, secretome, surfaceome related proteomic data.

Supplementary Data 5

Genome sequencing of SFN-resistant isolates.

Supplementary Data 6

Kinobead pull-down related proteomic data.

Supplementary Data 7

NMR data.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Le, P., Kunold, E., Macsics, R. et al. Repurposing human kinase inhibitors to create an antibiotic active against drug-resistant Staphylococcus aureus, persisters and biofilms. Nat. Chem. 12, 145–158 (2020).

Download citation

Further reading


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