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Proteolysis-targeting chimeras with reduced off-targets

Nature Chemistry volume 16, pages 218–228 (2024)Cite this article

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Abstract

Proteolysis-targeting chimeras (PROTACs) are molecules that induce proximity between target proteins and E3 ligases triggering target protein degradation. Pomalidomide, a widely used E3 ligase recruiter in PROTACs, can independently degrade other proteins, including zinc-finger (ZF) proteins, with vital roles in health and disease. This off-target degradation hampers the therapeutic applicability of pomalidomide-based PROTACs, requiring development of PROTAC design rules that minimize off-target degradation. Here we developed a high-throughput platform that interrogates off-target degradation and found that reported pomalidomide-based PROTACs induce degradation of several ZF proteins. We generated a library of pomalidomide analogues to understand how functionalizing different positions of the phthalimide ring, hydrogen bonding, and steric and hydrophobic effects impact ZF protein degradation. Modifications of appropriate size on the C5 position reduced off-target ZF degradation, which we validated through target engagement and proteomics studies. By applying these design principles, we developed anaplastic lymphoma kinase oncoprotein-targeting PROTACs with enhanced potency and minimal off-target degradation.

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Fig. 1: Development of a high-throughput assay for evaluating off-target ZF degradation of pomalidomide-based PROTACs.
Fig. 2: Validation of image-based results using NanoBRET and immunoblotting.
Fig. 3
Fig. 4: Synthesis of imide analogs using bromo- and amino- imide building blocks.
Fig. 5: Degradation score as metric to nominate the imide analogues with reduced off-targets and cellular target engagement studies.
Fig. 6: Validation of image-based platform by global proteomics.
Fig. 7: Re-engineering of ALK PROTACs based on the design principles.

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Data availability

Data generated in this study are provided in the manuscript, supplementary information and source data. The raw data corresponding to all the proteomics studies presented in this manuscript are available under the accession code PXD046264. Plasmid from Addgene (plasmid 74450; www.addgene.org/74450/) was used in this study. Structural information from PDB (ID: 6H0F) was used in this study. All other data supporting the findings of this study are available from the corresponding author on reasonable request. Source data are provided with this paper.

References

  1. Chamberlain, P. P. & Cathers, B. E. Cereblon modulators: low molecular weight inducers of protein degradation. Drug Discov. Today Technol. 31, 29–34 (2019).

    Article  PubMed  Google Scholar 

  2. Kozicka, Z. & Thomä, N. H. Haven’t got a glue: protein surface variation for the design of molecular glue degraders. Cell Chem. Biol. 28, 1032–1047 (2021).

    Article  CAS  PubMed  Google Scholar 

  3. Finley, D. Recognition and processing of ubiquitin–protein conjugates by the proteasome. Annu. Rev. Biochem. 78, 477–513 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Ito, T. et al. Identification of a primary target of thalidomide teratogenicity. Science 327, 1345–1350 (2010).

    Article  ADS  CAS  PubMed  Google Scholar 

  5. Krönke, J. et al. Lenalidomide causes selective degradation of IKZF1 and IKZF3 in multiple myeloma cells. Science 343, 301–305 (2014).

    Article  ADS  PubMed  Google Scholar 

  6. Lu, G. et al. The myeloma drug lenalidomide promotes the cereblon-dependent destruction of Ikaros proteins. Science 343, 305–309 (2014).

    Article  ADS  CAS  PubMed  Google Scholar 

  7. Chamberlain, P. P. & Hamann, L. G. Development of targeted protein degradation therapeutics. Nat. Chem. Biol. 15, 937–944 (2019).

    Article  CAS  PubMed  Google Scholar 

  8. 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).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  9. Winter, G. E. et al. Drug development. Phthalimide conjugation as a strategy for in vivo target protein degradation. Science 348, 1376–1381 (2015).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  10. Jiang, B. et al. Development of dual and selective degraders of cyclin-dependent kinases 4 and 6. Angew. Chem. 58, 6321–6326 (2019).

    Article  CAS  Google Scholar 

  11. Teng, M. et al. Development of CDK2 and CDK5 Dual Degrader TMX-2172. Angew. Chem. 59, 13865–13870 (2020).

    Article  CAS  Google Scholar 

  12. Matyskiela, M. E. et al. A novel cereblon modulator recruits GSPT1 to the CRL4(CRBN) ubiquitin ligase. Nature 535, 252–257 (2016).

    Article  ADS  CAS  PubMed  Google Scholar 

  13. Petzold, G., Fischer, E. S. & Thomä, N. H. Structural basis of lenalidomide-induced CK1α degradation by the CRL4(CRBN) ubiquitin ligase. Nature 532, 127–130 (2016).

    Article  ADS  CAS  PubMed  Google Scholar 

  14. Krönke, J. et al. Lenalidomide induces ubiquitination and degradation of CK1α in del(5q) MDS. Nature 523, 183–188 (2015).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  15. Wang, A. et al. ZFP91 is required for the maintenance of regulatory T cell homeostasis and function. J. Exp. Med. 218, e20201217 (2021).

    Article  CAS  PubMed  Google Scholar 

  16. Fu, M. & Blackshear, P. J. RNA-binding proteins in immune regulation: a focus on CCCH zinc finger proteins. Nat. Rev. Immunol. 17, 130–143 (2017).

    Article  CAS  PubMed  Google Scholar 

  17. Cassandri, M. et al. Zinc-finger proteins in health and disease. Cell Death Discov. 3, 17071 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Wang, E. S. et al. Acute pharmacological degradation of Helios destabilizes regulatory T cells. Nat. Chem. Biol. 17, 711–717 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Ito, T., Ando, H. & Handa, H. Teratogenic effects of thalidomide: molecular mechanisms. Cell Mol. Life Sci. 68, 1569–1579 (2011).

    Article  CAS  PubMed  Google Scholar 

  20. Therapontos, C., Erskine, L., Gardner, E. R., Figg, W. D. & Vargesson, N. Thalidomide induces limb defects by preventing angiogenic outgrowth during early limb formation. Proc. Natl Acad. Sci. USA 106, 8573–8578 (2009).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  21. Donovan, K. A. et al. Thalidomide promotes degradation of SALL4, a transcription factor implicated in Duane Radial Ray syndrome. eLife 7, e38430 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Matyskiela, M. E. et al. SALL4 mediates teratogenicity as a thalidomide-dependent cereblon substrate. Nat. Chem. Biol. 14, 981–987 (2018).

    Article  CAS  PubMed  Google Scholar 

  23. Mullard, A. Targeted protein degraders crowd into the clinic. Nat. Rev. Drug Discov. 20, 247–250 (2021).

    Article  CAS  PubMed  Google Scholar 

  24. Nguyen, P. A., Born, D. A., Deaton, A. M., Nioi, P. & Ward, L. D. Phenotypes associated with genes encoding drug targets are predictive of clinical trial side effects. Nat. Commun. 10, 1579 (2019).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  25. Deaton, A. M. et al. Rationalizing secondary pharmacology screening using human genetic and pharmacological evidence. Toxicol. Sci. 167, 593–603 (2019).

    Article  CAS  PubMed  Google Scholar 

  26. Zhang, A. X. et al. The vital role of proteomics in characterizing novel protein degraders. SLAS Discov. 26, 518–523 (2021).

    Article  CAS  PubMed  Google Scholar 

  27. Beveridge, R. et al. Native mass spectrometry can effectively predict PROTAC efficacy. ACS Cent. Sci. 6, 1223–1230 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Grandi, P. & Bantscheff, M. Advanced proteomics approaches to unravel protein homeostasis. Drug Discov. Today Technol. 31, 99–108 (2019).

    Article  PubMed  Google Scholar 

  29. Liu, X. et al. A proteomic platform to identify off-target proteins associated with therapeutic modalities that induce protein degradation or gene silencing. Sci. Rep. 11, 15856 (2021).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  30. Reinders, J., Lewandrowski, U., Moebius, J., Wagner, Y. & Sickmann, A. Challenges in mass spectrometry-based proteomics. Proteomics 4, 3686–3703 (2004).

    Article  CAS  PubMed  Google Scholar 

  31. Donovan, K. A. et al. Mapping the degradable kinome provides a resource for expedited degrader development. Cell 183, 1714–1731.e10 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Sievers, Q. L. et al. Defining the human C2H2 zinc finger degrome targeted by thalidomide analogs through CRBN. Science 362, eaat0572 (2018).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  33. Riching, K. M. et al. Quantitative live-cell kinetic degradation and mechanistic profiling of PROTAC mode of action. ACS Chem. Biol. 13, 2758–2770 (2018).

    Article  CAS  PubMed  Google Scholar 

  34. Zhang, C. et al. Proteolysis targeting chimeras (PROTACs) of Anaplastic Lymphoma Kinase (ALK). Eur. J. Med. Chem. 151, 304–314 (2018).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  35. Nabet, B. et al. The dTAG system for immediate and target-specific protein degradation. Nat. Chem. Biol. 14, 431–441 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Sreekanth, V. et al. Chemogenetic system demonstrates that Cas9 longevity impacts genome editing outcomes. ACS Cent. Sci. 6, 2228–2237 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. ImageJ user guide. (2012) NIH https://imagej.nih.gov/ij/docs/guide/

  38. Meier, F. et al. diaPASEF: parallel accumulation–serial fragmentation combined with data-independent acquisition. Nat. Methods 17, 1229–1236 (2020).

    Article  CAS  PubMed  Google Scholar 

  39. Demichev, V., Messner, C. B., Vernardis, S. I., Lilley, K. S. & Ralser, M. DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput. Nat. Methods 17, 41–44 (2020).

    Article  CAS  PubMed  Google Scholar 

  40. R Development Core Team (R Foundation for Statistical Computing, 2014).

  41. Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank P. Byrne (Broad Institute) for assistance with automated imaging screening experiments. This work was supported by DARPA (N66001-17-2-4055) and NIH (R01 GM137606 and R01 GM132825 to A.C.; NIH CA214608 and CA218278 to E.S.F.; R01 EB031172, R01 EB027793, and R35 GM118062 to D.R.L.). J.A.M.M. is a Ruth L. Kirchstein National Research Service Award Postdoctoral Fellow (F32 GM133088). D.R.L. and B.L.E. are investigators of the Howard Hughes Medical Institute. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Author notes

  1. These authors contributed equally: Tuan M. Nguyen, Vedagopuram Sreekanth, Arghya Deb, Praveen Kokkonda.

Authors and Affiliations

  1. Chemical Biology and Therapeutics Science, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Tuan M. Nguyen, Vedagopuram Sreekanth, Arghya Deb, Praveen Kokkonda, Praveen K. Tiwari, Veronika Shoba, Santosh K. Chaudhary, Sophia Lai, Ananthan Sadagopan & Amit Choudhary

  2. Department of Medicine, Harvard Medical School, Boston, MA, USA

    Tuan M. Nguyen, Vedagopuram Sreekanth, Arghya Deb, Praveen Kokkonda, Praveen K. Tiwari, Veronika Shoba, Santosh K. Chaudhary & Amit Choudhary

  3. Divisions of Renal Medicine and Engineering, Brigham and Women’s Hospital, Boston, MA, USA

    Tuan M. Nguyen, Vedagopuram Sreekanth, Praveen K. Tiwari & Amit Choudhary

  4. Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA

    Katherine A. Donovan & Eric S. Fischer

  5. Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA

    Katherine A. Donovan & Eric S. Fischer

  6. Merkin Institute of Transformative Technologies in Healthcare, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Jaron A. M. Mercer & David R. Liu

  7. Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA

    Jaron A. M. Mercer, Sophia Lai & David R. Liu

  8. Howard Hughes Medical Institute, Harvard University, Cambridge, MA, USA

    Jaron A. M. Mercer & David R. Liu

  9. Massachusetts Institute of Technology, Cambridge, MA, USA

    Ananthan Sadagopan

  10. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA

    Max Jan & Benjamin L. Ebert

  11. Cancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Max Jan & Benjamin L. Ebert

  12. Howard Hughes Medical Institute, Boston, MA, USA

    Max Jan & Benjamin L. Ebert

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  1. Tuan M. Nguyen
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Contributions

T.M.N., V.Sr., A.D., P.K., J.A.M.M. and A.C. planned the research. T.M.N., V.Sr., A.D., P.K., K.A.D., J.A.M.M. and A.C. designed the experiments. T.M.N., V.Sr., A.D., P.K., P.K.T., K.A.D., V.Sh. and S.K.C. performed the experiments. T.M.N., V.Sr., A.D., P.K., P.K.T., K.A.D., V.Sh., S.K.C., J.A.M.M., S.L., A.S., M.J., E.S.F., D.R.L., B.L.E. and A.C. analysed the data. T.M.N., V.Sr., A.D., P.K. and A.C. wrote the manuscript. A.C. supervised the research.

Corresponding author

Correspondence to Amit Choudhary.

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Competing interests

Broad Institute has filed a patent application including the work described herein. A.C. is a founder and Scientific Advisory Board (SAB) member in Photys therapeutics. E.S.F. is a founder, SAB member, and equity holder in Civetta, Lighthorse, Proximity and Neomorph (board of directors), SAB member and equity holder in Photys and Avilar, and a consultant to Astellas, Novartis, Sanofi, Deerfield and EcoR1. The Fischer lab receives or has received research funding from Novartis, Astellas, Interline and Deerfield. D.R.L. is a consultant and co-founder of Exo Therapeutics, a company that develops small-molecule therapeutics. K.A.D. is a consultant to Kronos Bio and Neomorph Inc. The remaining authors declare no competing financial interests.

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Extended data

Extended Data Fig. 1 Establishment and validation of automated imaging assay for the degradation of ZFs.

a) Representative readouts of the imaging assay in 384-well plates, demonstrating robust detection of ZF-tagged eGFP degradation as induced by pomalidomide. Shown are images of U2OS cells with stable expression of pomalidomide-sensitive ZFP91 degron reporter. Z′ value was calculated using an in-built module in the Harmony software (See materials and methods). b, c) Immunoblots (from at least two independent replicates) quantifying off-target degradation of endogenous ZF proteins ZFP91 by MS4078 (ALK PROTAC) in a dose-dependent manner across cell lines SU-DHL-1 (b) and H2228 (c). d) Label-free proteomic analysis of MS4078 in MOLT4 cells.

Source data

Extended Data Fig. 2 Off-target ZF degradation assessed by mass spectrometry-based proteomics.

Identification of the same group of exit vectors on pomalidomide with minimal off-target ZF degradation assessed by mass spectrometry-based proteomics for entire data set (a) and top 10 most degraded proteins (b). Relative abundance of endogenous ZF proteins in cells treated with pomalidomide-based PROTACs as arranged based on pomalidomide’s exit vector groups. Data were extracted from proteomics datasets published in Donovan et al.31.

Extended Data Fig. 3 Docking scores and topological polar surface area of C4 and C5 pomalidomide analogs.

a–c) Structural docking of pomalidomide analogs with C4 (a) and C5 (b) modifications on the phthalimide ring. Docking score (c) of each pair of modifications on C4 and C5 (paired Wilcoxon test, p = 8.8 × e-05). (d) Distribution of the physicochemical properties of the pomalidomide analog library. The topological polar surface area (TPSA) of each molecule is indicated by color and size (see legend). Note that each dot in the scatter plot represents a pair of compounds with the same modification on C4 and C5 positions, except the SNAr fluoro group. Synthetic routes are represented by different shapes shown in the legend).

Source data

Extended Data Fig. 4 Degradation of validated pomalidomide-sensitive ZF degrons induced by the pomalidomide analogs.

(a) Normalized eGFP intensity in 14 ZF reporter cell lines treated with different doses of 81 pomalidomide analogs ranging from 4.3 nM to 20 μM. Each block of 4.3 nM to 20 μM doses on the x axis represents one ZF reporter cell line. Data are mean of at least 3 independent replicates. (See source data for replicates, mean, SD) (b–d) Box-and-Whisker plots with statistical analysis for pomalidomide analogs arranged in pairs of C4 and C5 modifications such as acylation (b), Suzuki/Sonogashira coupling (c) and effect of -F group (d) on the phthalimide ring. Data are shown for cells treated with 5 μM of each compound (for acylated and Suzuki/Sonogashira couplings) and 20 µM data of each compound for deciphering the -F group effect. For b-d figure panels data points are the mean of at least 3 independent replicates. Centre of the box plot is median. Minima and maxima are 1.5 times the interquartile range over the 75th and under the 25th percentile, respectively.

Source data

Extended Data Fig. 5

Structures of IMiD analogs with the least degradation score (close to 0).

Extended Data Fig. 6

NanoBRET based ternary complex analysis of all the IMiD analogs and PROTACs reported in this study.

Source data

Extended Data Fig. 7

Global Proteomic analysis in KELLY cells. a–h, Global proteomic analysis of Kelly cells treated with analogues 1 (a), 39 (b), 37 (c), 56 (d), 38 (e), 32 (f), 36 (g) and 61 (h). FC, fold change.

Source data

Extended Data Fig. 8 Cellular characterization of dALK PROTACs.

a, b) Global Proteomic analysis of selected PROTACs, MS4078 (a) and dALK-10 (b) in SU-DHL-1 cells. c) Viability dose curves for the redesigned ALK PROTACs in SU-DHL-1 cells. Data are the mean ± SD of 3 independent replicates.

Source data

Extended Data Table 1 Amino acid sequences of the zinc finger motifs cloned in cilantro 2 vector
Full size table

Supplementary information

Supplementary Information

Supplementary Figs. 1–8, methods and materials, NMR spectra and supplementary references.

Reporting Summary

Source data

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Source Data Extended Data Fig. 1

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Nguyen, T.M., Sreekanth, V., Deb, A. et al. Proteolysis-targeting chimeras with reduced off-targets. Nat. Chem. 16, 218–228 (2024). https://doi.org/10.1038/s41557-023-01379-8

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