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.

Functional characterization of a PROTAC directed against BRAF mutant V600E

Abstract

The RAF family kinases function in the RAS–ERK pathway to transmit signals from activated RAS to the downstream kinases MEK and ERK. This pathway regulates cell proliferation, differentiation and survival, enabling mutations in RAS and RAF to act as potent drivers of human cancers. Drugs targeting the prevalent oncogenic mutant BRAF(V600E) have shown great efficacy in the clinic, but long-term effectiveness is limited by resistance mechanisms that often exploit the dimerization-dependent process by which RAF kinases are activated. Here, we investigated a proteolysis-targeting chimera (PROTAC) approach to BRAF inhibition. The most effective PROTAC, termed P4B, displayed superior specificity and inhibitory properties relative to non-PROTAC controls in BRAF(V600E) cell lines. In addition, P4B displayed utility in cell lines harboring alternative BRAF mutations that impart resistance to conventional BRAF inhibitors. This work provides a proof of concept for a substitute to conventional chemical inhibition to therapeutically constrain oncogenic BRAF.

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: Design strategy for BRAF PROTACs.
Fig. 2: Functional analysis of BRAF PROTACs in cells.
Fig. 3: Benchmark comparisons of PROTAC function.
Fig. 4: Identification of BRAF-driven tumor cell lines sensitive to P4B.
Fig. 5: Activated RAS confers BRAF(V600E) resistance to degradation by P4B.
Fig. 6: Analysis of ternary complex formation induced by P4B.

Data availability

Coordinates and structure factors (6UUO) are available at the Protein Data Bank, www.rcsb.org. The kinase inhibitor competition data used for the protein kinase-biased analysis were also submitted as an incomplete submission to the MassIVE respository (https://massive.ucsd.edu/ProteoSAFe/static/massive.jsp) and assigned the accession number MSV000085271. The dataset is available at ftp://massive.ucsd.edu/MSV000085271/. Data for the proteome-wide protein level analysis have been deposited as an incomplete submission to the MassIVE repository (https://massive.ucsd.edu/ProteoSAFe/static/massive.jsp) and assigned the accession number MSV000084551. The dataset is available at ftp://massive.ucsd.edu/MSV000084551/.. The RNA-seq data reported in this paper are available at the Gene Expression Omnibus database with accession number GSE148500. All data supporting the findings are available in the paper and Supplementary Information files. Source data are provided with this paper.

References

  1. 1.

    Lavoie, H. & Therrien, M. Regulation of RAF protein kinases in ERK signalling. Nat. Rev. Mol. Cell Biol. 16, 281–298 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Simanshu, D. K., Nissley, D. V. & McCormick, F. RAS proteins and their regulators in human disease. Cell 170, 17–33 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  3. 3.

    Terrell, E. M. & Morrison, D. K. Ras-mediated activation of the Raf family kinases. Cold Spring Harb. Perspect. Med. 9, a033746 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  4. 4.

    Nazarian, R. et al. Melanomas acquire resistance to B-RAF(V600E) inhibition by RTK or N-RAS upregulation. Nature 468, 973–977 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  5. 5.

    Kemper, K. et al. BRAF(V600E) kinase domain duplication identified in therapy-refractory melanoma patient-derived xenografts. Cell Rep. 16, 263–277 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  6. 6.

    Poulikakos, P. I. et al. RAF inhibitor resistance is mediated by dimerization of aberrantly spliced BRAF(V600E). Nature 480, 387–390 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  7. 7.

    Poulikakos, P. I. & Rosen, N. Mutant BRAF melanomas—dependence and resistance. Cancer Cell 19, 11–15 (2011).

    CAS  PubMed  Article  Google Scholar 

  8. 8.

    Haarberg, H. E. & Smalley, K. S. Resistance to Raf inhibition in cancer. Drug Disco. Today Technol. 11, 27–32 (2014).

    Article  Google Scholar 

  9. 9.

    Rajakulendran, T., Sahmi, M., Lefrancois, M., Sicheri, F. & Therrien, M. A dimerization-dependent mechanism drives RAF catalytic activation. Nature 461, 542–545 (2009).

    CAS  PubMed  Article  Google Scholar 

  10. 10.

    Thevakumaran, N. et al. Crystal structure of a BRAF kinase domain monomer explains basis for allosteric regulation. Nat. Struct. Mol. Biol. 22, 37–43 (2015).

    CAS  PubMed  Article  Google Scholar 

  11. 11.

    Lavoie, H. et al. Inhibitors that stabilize a closed RAF kinase domain conformation induce dimerization. Nat. Chem. Biol. 9, 428–436 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  12. 12.

    Karoulia, Z. et al. An integrated model of Raf inhibitor action predicts inhibitor activity against oncogenic BRAF signaling. Cancer Cell 30, 485–498 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  13. 13.

    Yao, Z. et al. BRAF mutants evade ERK-dependent feedback by different mechanisms that determine their sensitivity to pharmacologic inhibition. Cancer Cell 28, 370–383 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  14. 14.

    Peng, S. B. et al. Inhibition of RAF isoforms and active dimers by LY3009120 leads to anti-tumor activities in RAS or BRAF mutant cancers. Cancer Cell 28, 384–398 (2015).

    CAS  PubMed  Article  Google Scholar 

  15. 15.

    Sakamoto, K. M. et al. Protacs: chimeric molecules that target proteins to the Skp1-Cullin-F box complex for ubiquitination and degradation. Proc. Natl Acad. Sci. USA 98, 8554–8559 (2001).

    CAS  Article  Google Scholar 

  16. 16.

    Pettersson, M. & Crews, C. M. PROteolysis TArgeting Chimeras (PROTACs)—past, present and future. Drug Disco. Today Technol. 31, 15–27 (2019).

    Article  Google Scholar 

  17. 17.

    Paiva, S. L. & Crews, C. M. Targeted protein degradation: elements of PROTAC design. Curr. Opin. Chem. Biol. 50, 111–119 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  18. 18.

    Waizenegger, I. C. et al. A novel RAF kinase inhibitor with DFG-Out-binding mode: high efficacy in BRAF-mutant tumor xenograft models in the absence of normal tissue hyperproliferation. Mol. Cancer Ther. 15, 354–365 (2016).

    CAS  PubMed  Article  Google Scholar 

  19. 19.

    Lu, J. et al. Hijacking the E3 ubiquitin ligase cereblon to efficiently target BRD4. Chem. Biol. 22, 755–763 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  20. 20.

    Buckley, D. L. et al. Small-molecule inhibitors of the interaction between the E3 ligase VHL and HIF1ɑ. Angew. Chem. Int. Ed. Engl. 51, 11463–11467 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  21. 21.

    Buckley, D. L. et al. HaloPROTACS: use of small molecule PROTACs to induce degradation of halotag fusion proteins. ACS Chem. Biol. 10, 1831–1837 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  22. 22.

    Douglass, E. F. Jr., Miller, C. J., Sparer, G., Shapiro, H. & Spiegel, D. A. A comprehensive mathematical model for three-body binding equilibria. J. Am. Chem. Soc. 135, 6092–6099 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  23. 23.

    Nissan, M. H. et al. Loss of NF1 in cutaneous melanoma is associated with RAS activation and MEK dependence. Cancer Res. 74, 2340–2350 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  24. 24.

    Corcoran, R. B. et al. EGFR-mediated re-activation of MAPK signaling contributes to insensitivity of BRAF mutant colorectal cancers to RAF inhibition with vemurafenib. Cancer Disco. 2, 227–235 (2012).

    CAS  Article  Google Scholar 

  25. 25.

    Prahallad, A. et al. Unresponsiveness of colon cancer to BRAF(V600E) inhibition through feedback activation of EGFR. Nature 483, 100–103 (2012).

    CAS  PubMed  Article  Google Scholar 

  26. 26.

    Drosten, M. et al. Genetic analysis of Ras signalling pathways in cell proliferation, migration and survival. EMBO J. 29, 1091–1104 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  27. 27.

    Chung, C. I., Zhang, Q. & Shu, X. Dynamic imaging of small molecule induced protein–protein interactions in living cells with a fluorophore phase transition based approach. Anal. Chem. 90, 14287–14293 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  28. 28.

    Haling, J. R. et al. Structure of the BRAF-MEK complex reveals a kinase activity independent role for BRAF in MAPK signaling. Cancer Cell 26, 402–413 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  29. 29.

    Lavoie, H. et al. MEK drives BRAF activation through allosteric control of KSR proteins. Nature 554, 549–553 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  30. 30.

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

    CAS  Article  Google Scholar 

  31. 31.

    Zhang, L. et al. Characterization of the novel broad-spectrum kinase inhibitor CTx-0294885 as an affinity reagent for mass spectrometry-based kinome profiling. J. Proteome Res. 12, 3104–3116 (2013).

    CAS  PubMed  Article  Google Scholar 

  32. 32.

    Park, E. et al. Architecture of autoinhibited and active BRAF-MEK1-14-3-3 complexes. Nature 575, 545–550 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  33. 33.

    Kondo, Y. et al. Cryo-EM structure of a dimeric B-Raf:14-3-3 complex reveals asymmetry in the active sites of B-Raf kinases. Science 366, 109–115 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  34. 34.

    Tsai, J. et al. Discovery of a selective inhibitor of oncogenic B-Raf kinase with potent antimelanoma activity. Proc. Natl Acad. Sci. USA 105, 3041–3046 (2008).

    CAS  PubMed  Article  Google Scholar 

  35. 35.

    Assadieskandar, A. et al. Rigidification dramatically improves inhibitor selectivity for RAF kinases. ACS Med. Chem. Lett. 10, 1074–1080 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  36. 36.

    Subedi, G. P., Johnson, R. W., Moniz, H. A., Moremen, K. W. & Barb, A. High yield expression of recombinant human proteins with the transient transfection of HEK293 cells in suspension. J. Vis. Exp. 2015, e53568 (2015).

    Google Scholar 

  37. 37.

    Kabsch, W. Xds. Acta Crystallogr. D Biol. Crystallogr. 66, 125–132 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  38. 38.

    Assadieskandar, A. et al. Effects of rigidity on the selectivity of protein kinase inhibitors. Eur. J. Med. Chem. 146, 519–528 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  39. 39.

    McCoy, A. J. et al. Phaser crystallographic software. J. Appl. Crystallogr. 40, 658–674 (2007).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Moriarty, N. W., Grosse-Kunstleve, R. W. & Adams, P. D. electronic ligand builder and optimization workbench (eLBOW): a tool for ligand coordinate and restraint generation. Acta Crystallogr. D Biol. Crystallogr. 65, 1074–1080 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  41. 41.

    Emsley, P. & Cowtan, K. Coot: model-building tools for molecular graphics. Acta Crystallogr. D Biol. Crystallogr. 60, 2126–2132 (2004).

    Article  CAS  Google Scholar 

  42. 42.

    Adams, P. D. et al. PHENIX: a comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr. D Biol. Crystallogr. 66, 213–221 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  43. 43.

    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  Article  Google Scholar 

  44. 44.

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

    CAS  Article  Google Scholar 

  45. 45.

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

    CAS  Article  Google Scholar 

  46. 46.

    Ritz, C., Baty, F., Streibig, J. C. & Gerhard, D. Dose–response analysis using R. PLoS ONE 10, e0146021 (2015).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  47. 47.

    Wingett, S. W. & Andrews, S. FastQ Screen: a tool for multi-genome mapping and quality control. F1000Res 7, 1338 (2018).

    PubMed  PubMed Central  Article  Google Scholar 

  48. 48.

    Ewels, P., Magnusson, M., Lundin, S. & Kaller, M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics 32, 3047–3048 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  49. 49.

    Trapnell, C., Pachter, L. & Salzberg, S. L. TopHat: discovering splice junctions with RNA-seq. Bioinformatics 25, 1105–1111 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  50. 50.

    Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  51. 51.

    Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  52. 52.

    Liu, Y. et al. Next-generation RNA sequencing of archival formalin-fixed paraffin-embedded urothelial bladder cancer. Eur. Urol. 66, 982–986 (2014).

    CAS  PubMed  Article  Google Scholar 

  53. 53.

    Galili, T., O’Callaghan, A., Sidi, J. & Sievert, C. heatmaply: an R package for creating interactive cluster heatmaps for online publishing. Bioinformatics 34, 1600–1602 (2018).

    CAS  PubMed  Article  Google Scholar 

  54. 54.

    Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank G. Seabrook for technical assistance and access to the NMR Core Facility of Princess Margaret Cancer Center. Research was supported by grants from the Canadian Cancer Society (CCSRI-Impact grant no. 704116 to F.S. and grant no. 706165 to M. Therrien), the Canadian Institutes of Health Research (grant no. FDN 143277 to F.S.; grant no. FDN 388023 to M. Therrien; grant no. FRN 414829 to P. Maisonneuve; grant no. FDN 144301 to A.-C.G.; grant no. FDN 143343 to D.D.), the Ontario Research Fund (grant no. RE08-065 to F.S., D.D., J.W., A.-C.G.) and the Terry Fox Research Institute to F.S., J.W. and A.-C.G. M. Therrien, A.-C.G., D.D. and F.S. are recipients of Tier1 Canada Research Chairs. S.D. is a recipient of the Banting Postdoctoral Fellowship. Proteomics and RNA-seq work were performed at the Network Biology Collaborative Centre at the Lunenfeld-Tanenbaum Research Institute, a facility supported by Canada Foundation for Innovation funding, by the Ontarian Government and by Genome Canada and Ontario Genomics (grant no. OGI-139). Diffraction work conducted at the Northeastern Collaborative Access Team beamlines was funded by the National Institute of General Medical Sciences from the National Institutes of Health (grant no. P41 GM103403) and by an NIH-ORIP HEI grant (grant no. S10 RR029205).

Author information

Affiliations

Authors

Contributions

F.S., P. Maisonneuve, G. Posternak and X.T. conceived the idea and directed the project. G. Posternak, X.T., P. Maisonneuve, T.J., H.L., S.O., T.G.R., A.A., M.P., G. Poda, J.K., K.C., R.A.B., M. Taipale, D.U., J.W., A.-C.G., D.D., R.A.-A., M. Therrien and F.S. designed the experiments and interpreted results. G. Posternak, X.T., P. Maisonneuve, T.J., H.L., S.D., S.O., T.G.R., L.C., K.C., Z.Y., A.A., M.P., G. Poda, P. Mader, D.F.C., C.W., S.M., J.K., B.L. and I.K. performed experiments. F.S., P. Maisonneuve, G. Posternak, H.L. and M. Therrien wrote the manuscript with input from all other authors.

Corresponding authors

Correspondence to Marc Therrien or Frank Sicheri.

Ethics declarations

Competing interests

F.S. and D.D. are founders and consultants for Repare Therapeutics. Host institutions LTRI and OICR have filed a patent relating to the PROTAC molecules presented in this study and their uses (pending USPA No. 62/812,567; applicants are G. Poda, G. Posternak and F.S.). No competing interests were disclosed by the other authors.

Additional information

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

Extended data

Extended Data Fig. 1 Structure of the BRAF kinase domain bound to P4B.

a, Stereo-view of an unbiased |Fo-Fc| electron density map contoured at 2.5σ colored green with P4B and the BRAF kinase domain colored orange and blue, respectively. b, Stereo-view of the superimposition of P4B (orange) bound to BRAF (dark blue) and BI 882370 (light green) bound to BRAF (light blue) (PDB of BRAF:BI 882370 structure is 5CSX). c, d, Comparison of the binding mode of P4B (c) and BI 882370 (d) to the BRAF kinase domain. P4B, BI 882370, glucose and the BRAF contacting residues are shown as sticks. e, f, Flat schematic representation of the binding mode of P4B (e) and BI 882370 (f) to the BRAF kinase domain. Blue eyelashes represent hydrophobic interactions and yellow dashed lines represent hydrogen bonds.

Extended Data Fig. 2 Functional analysis of P4B in cells and in vitro.

a, P4B dose response analysis in A375 cells. Cells were treated for 24 h with P4B, PEG4-BI, or pomalidomide at the indicated concentrations. p27 accumulation is reflective of G1 cell cycle arrest upon BRAF degradation by P4B treatment. b, Immunoblot analysis of BRAF, CRAF, ARAF, KSR1, SRMS, pMEK and MEK levels in A375 cells after 24 h treatment cells with P4B, P4BME and pomalidomide at the indicated concentrations. c, Immunoblot analysis of BRAF, CRAF, pMEK and MEK levels in SKMEL-28 cells after 24 h treatment with P4B, P4BME and Pmd at the indicated concentrations. Tubulin served as a loading control. d, Time course analysis. A375 cells were treated with 100 nM P4B for the indicated time. e, Anti-BRAF immunoblot of in vitro ubiquitinatated full-length BRAF(V600E). Ubiquitination reactions were carried out + /- the indicated components. The white signal at the bottom of blot corresponds to saturation of BRAF signal. Data shown are representative of minimally two independent experiments. Source data

Extended Data Fig. 3 Survey of PROTAC potency in cell lines with different RAS-ERK pathway lesions.

aj, Dose-dependent inhibition of proliferation (left panel) and phospho-ERK (right panel) following P4B, P4BME and BI 882370* treatment in COLO-205 (a), RKO (b), HT-29 (c), MeWo (d), NCI-H508 (e), NCI-H1755 (f), HCT116 (g), SK-MEL-2 (h), MDA-MB-231 (i), and NCI-H2087 (j) cell lines. Data shown are representative of a minimum of three independent experiments performed in technical duplicates.

Extended Data Fig. 4 Immunoblot survey of PROTAC potency in cell lines with different RAS-ERK pathway lesions.

a-c, Immunoblot analysis of COLO-205 (a), HT-29 (b), and MeWo (c), cell lines after 24 h treatment at the indicated compound concentrations. (d), Washout analysis of A375 cells treated with P4B or non-PROTAC controls. Cells were treated with DMSO (0.1%), P4B (100 nM), P4BME (500 nM), or BI 882370* (500 nM) for 22 h followed by washing in medium to remove compounds. Note that a lower concentration of P4B was employed to enable similar starting points of pathway inhibition for comparison. Cells were incubated in fresh medium for the indicated time periods prior to harvesting and immunoblot analysis. Data shown in d are representative of minimally two independent experiments. e, Comparative immunoblot analysis of P4B, P4BME and BI 882370* function in HCT116 cells after 24 h treatment at the indicated compound concentrations. Data shown are representative of minimally two independent experiments. Source data

Extended Data Fig. 5 Identification of BRAF-driven tumor cell lines sensitive to P4B.

a–c, Dose-dependent analysis of P4B and P4BME treatment on BRAF, MEK, ERK, pMEK and pERK levels in WM266–4 (a), NCI-H1666 (b) and A375-VR (c) cell lines. Data shown are representative of minimally three independent experiments performed in technical duplicates. Quantification of BRAF levels shown below blots. Source data

Extended Data Fig. 6 Influence of RAS expression on the sensitivity of BRAF to degradation by P4B.

a, Over-expression of individual RAS(G12V) mutant isoforms in A375 cells. Lysates of A375 cells transduced with the indicated lentivirus were analysed by immunoblot. b, Immunoblot analyses of A375 cells transduced with the indicated lentivirus after 24 h treatment with P4B at the indicated concentrations. c, The MEF Hras-/-, Nras-/-, Kraslox/lox cell line (KrasWT-lox/lox) was treated with 1 µM 4-OHT for 18 days to knock out the KRAS isoform (RASless). Immunoblot was performed on whole cell extracts using the indicated antibodies. d, Immunoblot analyses of BRAF levels in KrasWT-lox/lox and RASless cells treated for 24 h with the indicated concentration of P4B. e, Dose-dependent inhibition of proliferation of KrasWT-lox/lox cells (left panel) and RASless cells (right panel) with increasing concentration of P4B and P4BME. f, Dose-dependent inhibition of proliferation (left panel) and phospho-ERK (right panel) following P4B and P4BME treatment of RASless cells stably expressing BRAF(V600E). g, Immunoblot analyses of BRAF(V600E) (anti-RM8) and total BRAF (WT + V600E) levels in RASless cells stably expressing BRAF(V600E) and treated for 24 h with the indicated concentration of P4B. Data shown in e and f are representative of minimally three independent experiments performed in technical duplicates. Source data

Extended Data Fig. 7 Analysis of PROTAC induced ternary complexes between the isolated protein kinase domain of BRAF and CRBN/DDB1 in vitro.

a, Binding of CRBN/DDB1 to a fluorescein-labelled pomalidomide probe assessed by fluorescence polarization. b-h, Competitive displacement of fluorescein-labelled pomalidomide probe from CRBN-DDB1 (at 100 nM and 400 nM, respectively, corresponding to 80% saturated binding) by pomalidomide (Pmd) (b), P4B (c), 2 (d), 4 (e), 5 (f), 6 (g), 7 (h) assessed in the absence or in the presence of BRAF16mut(WT) kinase domain, or BRAF16mut(V600E) kinase domain. IC50 values were obtained by fitting FP signal using a variable slope - four parameter equation in GraphPad Prism. Data shown are representative of two independent experiments each performed in triplicate. Data represent mean values ± s.d.

Extended Data Fig. 8 P4B induced ternary complexes in cells.

a, A375 cells ectopically expressing flag-tagged CRBN/DDB1 were treated with P4B or BI 882370* at the indicated experimental conditions. Flag-tagged CRBN was immunoprecipitated using anti-Flag magnetic beads. Lysates and immunoprecipitates were subjected to immunoblot analysis with the indicated antibodies. * indicates nonspecific signal. Data are representative of two independent experiments. b. GFP-fluorescence images of HEK293T cells expressing CRBN-EGFP-HO-Tag6 and BRAF-EGFP-HO-Tag3 (WT or V600E) at the indicated time point after treatment with 0.5 µM of P4B, BI 882370* and P4BME or equivalent volume of DMSO. Data are representative of two independent experiments. Scale bars represent 10 µm. Source data

Extended Data Fig. 9 Kinase specificity profiles of P4B and BI 882370*.

a, Summary table of the competition assay. A375 cell lysate was preincubated with DMSO (control), CTx-0294885, P4B or BI 882370* prior to CTx-0294885-based affinity purification and mass spectrometric analysis; only proteins (and kinases) passing the 1% FDR threshold set in MaxQuant are reported (as number of unique genes). The threshold for reporting kinase inhibitor efficiency was a minimal reduction to 60% of its initial recovery value at the highest dose (30 µM). b–d, Individual curves for those kinases that meet the 60% threshold of displacement with both P4B and BI 882370* (b), only with P4B (c) or only with BI 882370* (d). Both Swiss-Prot protein names and NCBI gene names are listed.

Extended Data Fig. 10 Proteome wide protein level analysis.

a, Immunoblot analysis of A375 whole cell lysates used in proteome wide analyses in b and c. Data are representative of two independent duplicates. Changes in protein levels between P4B and P4BME treatments (b) and between P4B and DMSO treatments (c). A375 cells were incubated for 24 h with 200 µM of P4B, P4BME or DMSO only, prior to lysis, TMT labeling, and mass spectrometric analysis. Blue and red vertical lines are representative of log2 fold change cutoffs of - and + 1.5 and the dotted horizontal line is representative of a p-value cutoff of 0.01. Coloured points represent proteins that are considered significantly decreased (blue) and increased (red), respectively. Only proteins passing these thresholds are listed. Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–8, Tables 1–4 and Note, and Source Data Supplementary Figs. 1–3, 5, 7 and 8.

Reporting Summary

Supplementary Table 5

Lists of genes identified in the transcriptome-wide analyses

Source data

Source Data Fig. 2

Unprocessed western blots and/or gels

Source Data Fig. 3

Unprocessed western blots and/or gels

Source Data Fig. 6

Unprocessed western blots and/or gels

Source Data Extended Data Fig. 2

Unprocessed western blots and/or gels

Source Data Extended Data Fig. 4

Unprocessed western blots and/or gels

Source Data Extended Data Fig. 5

Unprocessed western blots and/or gels

Source Data Extended Data Fig. 6

Unprocessed western blots and/or gels

Source Data Extended Data Fig. 8

Unprocessed western blots and/or gels

Source Data Extended Data Fig. 10

Unprocessed western blots and/or gels

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Posternak, G., Tang, X., Maisonneuve, P. et al. Functional characterization of a PROTAC directed against BRAF mutant V600E. Nat Chem Biol 16, 1170–1178 (2020). https://doi.org/10.1038/s41589-020-0609-7

Download citation

Further reading

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