Quantitative cross-linking/mass spectrometry to elucidate structural changes in proteins and their complexes


Quantitative cross-linking/mass spectrometry (QCLMS/QXL-MS) probes structural changes of proteins in solution. This method has revealed induced conformational changes, composition shifts in conformational ensembles and changes in protein interactions. It illuminates different structural states of proteins or protein complexes by comparing which residue pairs can be cross-linked in these states. Cross-links provide information about structural changes that may be inaccessible by alternative technologies. Small local conformational changes affect relative abundances of nearby cross-links, whereas larger conformational changes cause new cross-links to be formed. Distinguishing between minor and major changes requires a robust analysis based on carefully selected replicates and, when using isotope-labeled cross-linkers, replicated analysis with a permutated isotope-labeling scheme. A label-free workflow allows for application of a wide range of cross-linking chemistries and enables parallel comparison of multiple conformations. In this protocol, we demonstrate both label-free and isotope-labeled cross-linker-based workflows using the cross-linker bis(sulfosuccinimidyl)suberate (BS3). The software XiSearch, developed by our group, is used to identify cross-linked residue pairs, although the workflow is not limited to this search software. The open-access software Skyline is used for automated quantitation. Note that additional manual correction greatly enhances quantitation accuracy. The protocol has been applied to purified multi-protein complexes but is not necessarily limited to that level of sample complexity. Optimizing the cross-linker/protein ratio and fractionating peptides increase the data density of quantified cross-links, and thus the resolution of QCLMS. The entire procedure takes ~1–3 weeks.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: QCLMS workflows.
Fig. 2: Linearization of cross-linked peptide sequences.
Fig. 3: Applications of QCLMS workflows.


  1. 1.

    Sinz, A. Chemical cross-linking and mass spectrometry to map three-dimensional protein structures and protein-protein interactions. Mass Spectrom. Rev. 25, 663–682 (2006).

    CAS  Article  Google Scholar 

  2. 2.

    Leitner, A. et al. Probing native protein structures by chemical cross-linking, mass spectrometry, and bioinformatics. Mol. Cell. Proteomics 9, 1634–1649 (2010).

    CAS  Article  Google Scholar 

  3. 3.

    Rappsilber, J. The beginning of a beautiful friendship: cross-linking/mass spectrometry and modelling of proteins and multi-protein complexes. J. Struct. Biol. 173, 530–540 (2011).

    CAS  Article  Google Scholar 

  4. 4.

    Yu, C. & Huang, L. Cross-linking mass spectrometry: an emerging technology for interactomics and structural biology. Anal. Chem. 90, 144–165 (2018).

    CAS  Article  Google Scholar 

  5. 5.

    Sinz, A. Cross-linking/mass spectrometry for studying protein structures and protein-protein interactions: where are we now and where should we go from here? Angew. Chem. Int. Ed Engl. 57, 6390–6396 (2018).

    CAS  Article  Google Scholar 

  6. 6.

    O’Reilly, F. & Rappsilber, J. Cross-linking/mass spectrometry: methods and applications to structural, molecular and systems biology. Nat. Struct. Mol. Biol. https://doi.org/10.1038/s41594-018-0147-0 (2018).

  7. 7.

    Chen, Z. et al. Quantitative cross-linking/mass spectrometry reveals subtle protein conformational changes. Wellcome Open Res. 1, 5 (2016).

    Article  Google Scholar 

  8. 8.

    Walzthoeni, T. et al. xTract: software for characterizing conformational changes of protein complexes by quantitative cross-linking mass spectrometry. Nat. Methods 12, 1185–1190 (2015).

    CAS  Article  Google Scholar 

  9. 9.

    Kukacka, Z., Rosulek, M., Strohalm, M., Kavan, D. & Novak, P. Mapping protein structural changes by quantitative cross-linking. Methods 89, 112–120 (2015).

    CAS  Article  Google Scholar 

  10. 10.

    Zheng, Q., Zhang, H., Wu, S. & Chen, H. Probing protein 3D structures and conformational changes using electrochemistry-assisted isotope labeling cross-linking mass spectrometry. J. Am. Soc. Mass Spectrom. 27, 864–875 (2016).

    CAS  Article  Google Scholar 

  11. 11.

    Rampler, E. et al. Comprehensive cross-linking mass spectrometry reveals parallel orientation and flexible conformations of plant HOP2-MND1. J. Proteome Res. 14, 5048–5062 (2015).

    CAS  Article  Google Scholar 

  12. 12.

    Boelt, S. G. et al. Mapping the Ca(2+) induced structural change in calreticulin. J. Proteomics 142, 138–148 (2016).

    CAS  Article  Google Scholar 

  13. 13.

    Huang, B. X. & Kim, H.-Y. Probing Akt-inhibitor interaction by chemical cross-linking and mass spectrometry. J. Am. Soc. Mass Spectrom. 20, 1504–1513 (2009).

    CAS  Article  Google Scholar 

  14. 14.

    Schmidt, C. et al. Comparative cross-linking and mass spectrometry of an intact F-type ATPase suggest a role for phosphorylation. Nat. Commun. 4, 1985 (2013).

    Article  Google Scholar 

  15. 15.

    Yu, C. et al. Gln40 deamidation blocks structural reconfiguration and activation of SCF ubiquitin ligase complex by Nedd8. Nat. Commun. 6, 10053 (2015).

    CAS  Article  Google Scholar 

  16. 16.

    Beilsten-Edmands, V. et al. eIF2 interactions with initiator tRNA and eIF2B are regulated by post-translational modifications and conformational dynamics. Cell Discov. 1, 15020 (2015).

    CAS  Article  Google Scholar 

  17. 17.

    Koehler, C. et al. Genetic code expansion for multiprotein complex engineering. Nat. Methods 13, 997–1000 (2016).

    CAS  Article  Google Scholar 

  18. 18.

    Tomko, R. J. Jr et al. A single α helix drives extensive remodeling of the proteasome lid and completion of regulatory particle assembly. Cell 163, 432–444 (2015).

    CAS  Article  Google Scholar 

  19. 19.

    Herbert, A. P. et al. Complement evasion mediated by enhancement of captured factor H: implications for protection of self-surfaces from complement. J. Immunol. 195, 4986–4998 (2015).

    CAS  Article  Google Scholar 

  20. 20.

    Chen, Z. A. et al. Structure of complement C3(H2O) revealed by quantitative cross-linking/mass spectrometry and modeling. Mol. Cell. Proteomics 15, 2730–2743 (2016).

    CAS  Article  Google Scholar 

  21. 21.

    Chavez, J. D. et al. Quantitative interactome analysis reveals a chemoresistant edgotype. Nat. Commun. 6, 7928 (2015).

    CAS  Article  Google Scholar 

  22. 22.

    Chavez, J. D., Schweppe, D. K., Eng, J. K. & Bruce, J. E. In vivo conformational dynamics of Hsp90 and its interactors. Cell Chem. Biol. 23, 716–726 (2016).

    CAS  Article  Google Scholar 

  23. 23.

    Müller, D. R. et al. Isotope-tagged cross-linking reagents. A new tool in mass spectrometric protein interaction analysis. Anal. Chem. 73, 1927–1934 (2001).

    Article  Google Scholar 

  24. 24.

    Fischer, L., Chen, Z. A. & Rappsilber, J. Quantitative cross-linking/mass spectrometry using isotope-labelled cross-linkers. J. Proteomics 88, 120–128 (2013).

    CAS  Article  Google Scholar 

  25. 25.

    Chen, Z. A., Fischer, L., Cox, J. & Rappsilber, J. Quantitative cross-linking/mass spectrometry using isotope-labeled cross-linkers and MaxQuant. Mol. Cell. Proteomics 15, 2769–2778 (2016).

    CAS  Article  Google Scholar 

  26. 26.

    Zhong, X. et al. Large-scale and targeted quantitative cross-linking MS using isotope-labeled protein interaction reporter (PIR) cross-linkers. J. Proteome Res. 16, 720–727 (2017).

    CAS  Article  Google Scholar 

  27. 27.

    Schmidt, C. & Robinson, C. V. A comparative cross-linking strategy to probe conformational changes in protein complexes. Nat. Protoc. 9, 2224–2236 (2014).

    CAS  Article  Google Scholar 

  28. 28.

    Barysz, H. et al. Three-dimensional topology of the SMC2/SMC4 subcomplex from chicken condensin I revealed by cross-linking and molecular modelling. Open Biol. 5, 150005 (2015).

    Article  Google Scholar 

  29. 29.

    Yu, C. et al. Developing a multiplexed quantitative cross-linking mass spectrometry platform for comparative structural analysis of protein complexes. Anal. Chem. 88, 10301–10308 (2016).

    CAS  Article  Google Scholar 

  30. 30.

    Leitner, A., Walzthoeni, T. & Aebersold, R. Lysine-specific chemical cross-linking of protein complexes and identification of cross-linking sites using LC-MS/MS and the xQuest/xProphet software pipeline. Nat. Protoc. 9, 120–137 (2014).

    CAS  Article  Google Scholar 

  31. 31.

    MacLean, B. et al. Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 26, 966–968 (2010).

    CAS  Article  Google Scholar 

  32. 32.

    Valot, B., Langella, O., Nano, E. & Zivy, M. MassChroQ: a versatile tool for mass spectrometry quantification. Proteomics 11, 3572–3577 (2011).

    CAS  Article  Google Scholar 

  33. 33.

    Strohalm, M., Kavan, D., Novák, P., Volný, M. & Havlícek, V. mMass 3: a cross-platform software environment for precise analysis of mass spectrometric data. Anal. Chem. 82, 4648–4651 (2010).

    CAS  Article  Google Scholar 

  34. 34.

    Liu, C. et al. pQuant improves quantitation by keeping out interfering signals and evaluating the accuracy of calculated ratios. Anal. Chem. 86, 5286–5294 (2014).

    CAS  Article  Google Scholar 

  35. 35.

    Müller, F., Fischer, L., Chen, Z. A., Auchynnikava, T. & Rappsilber, J. On the reproducibility of label-free quantitative cross-linking/mass spectrometry. J. Am. Soc. Mass Spectrom. 29, 405–412 (2017).

  36. 36.

    Chen, Z. A. et al. Architecture of the RNA polymerase II-TFIIF complex revealed by cross-linking and mass spectrometry. EMBO J. 29, 717–726 (2010).

    CAS  Article  Google Scholar 

  37. 37.

    Fritzsche, R., Ihling, C. H., Götze, M. & Sinz, A. Optimizing the enrichment of cross-linked products for mass spectrometric protein analysis. Rapid Commun. Mass Spectrom. 26, 653–658 (2012).

    CAS  Article  Google Scholar 

  38. 38.

    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 

  39. 39.

    Rappsilber, J., Mann, M. & Ishihama, Y. Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips. Nat. Protoc. 2, 1896–1906 (2007).

    CAS  Article  Google Scholar 

  40. 40.

    Kolbowski, L., Mendes, M. L. & Rappsilber, J. Optimizing the parameters governing the fragmentation of cross-linked peptides in a tribrid mass spectrometer. Anal. Chem. 89, 5311–5318 (2017).

    CAS  Article  Google Scholar 

  41. 41.

    Giese, S. H., Fischer, L. & Rappsilber, J. A study into the collision-induced dissociation (CID) behavior of cross-linked peptides. Mol. Cell. Proteomics 15, 1094–1104 (2016).

    CAS  Article  Google Scholar 

  42. 42.

    Rinner, O. et al. Identification of cross-linked peptides from large sequence databases. Nat. Methods 5, 315–318 (2008).

    CAS  Article  Google Scholar 

  43. 43.

    Anderson, G. A., Tolic, N., Tang, X., Zheng, C. & Bruce, J. E. Informatics strategies for large-scale novel cross-linking analysis. J. Proteome Res. 6, 3412–3421 (2007).

    CAS  Article  Google Scholar 

  44. 44.

    Liu, F., Rijkers, D. T. S., Post, H. & Heck, A. J. R. Proteome-wide profiling of protein assemblies by cross-linking mass spectrometry. Nat. Methods 12, 1179–1184 (2015).

    CAS  Article  Google Scholar 

  45. 45.

    Yuan, Z. et al. Structural basis of Mcm2-7 replicative helicase loading by ORC-Cdc6 and Cdt1. Nat. Struct. Mol. Biol. 24, 316–324 (2017).

    CAS  Article  Google Scholar 

  46. 46.

    Yang, B. et al. Identification of cross-linked peptides from complex samples. Nat. Methods 9, 904–906 (2012).

    CAS  Article  Google Scholar 

  47. 47.

    Hoopmann, M. R. et al. Kojak: efficient analysis of chemically cross-linked protein complexes. J. Proteome Res. 14, 2190–2198 (2015).

    CAS  Article  Google Scholar 

  48. 48.

    Götze, M. et al. StavroX--a software for analyzing crosslinked products in protein interaction studies. J. Am. Soc. Mass Spectrom. 23, 76–87 (2012).

    Article  Google Scholar 

  49. 49.

    Xu, H., Hsu, P.-H., Zhang, L., Tsai, M.-D. & Freitas, M. A. Database search algorithm for identification of intact cross-links in proteins and peptides using tandem mass spectrometry. J. Proteome Res. 9, 3384–3393 (2010).

    CAS  Article  Google Scholar 

  50. 50.

    Götze, M. et al. Automated assignment of MS/MS cleavable cross-links in protein 3D-structure analysis. J. Am. Soc. Mass Spectrom. 26, 83–97 (2015).

    Article  Google Scholar 

  51. 51.

    Liu, F., Lössl, P., Scheltema, R., Viner, R. & Heck, A. J. R. Optimized fragmentation schemes and data analysis strategies for proteome-wide cross-link identification. Nat. Commun. 8, 15473 (2017).

    CAS  Article  Google Scholar 

  52. 52.

    Petrotchenko, E. V., Makepeace, K. A. T. & Borchers, C. H. DXMSMS match program for automated analysis of LC-MS/MS data obtained using isotopically coded CID-cleavable cross-linking reagents. Curr. Protoc. Bioinformatics 48, 8.18.1–19 (2014).

    Google Scholar 

  53. 53.

    Chambers, M. C. et al. A cross-platform toolkit for mass spectrometry and proteomics. Nat. Biotechnol. 30, 918–920 (2012).

    CAS  Article  Google Scholar 

  54. 54.

    Fischer, L. & Rappsilber, J. Quirks of error estimation in cross-linking/mass spectrometry. Anal. Chem. 89, 3829–3833 (2017).

    CAS  Article  Google Scholar 

Download references


This work was supported by the Wellcome Trust through a Senior Research Fellowship to J.R. (103139), a Centre Core Grant (203149) and an Instrument Grant (108504).

Author information




J.R. and Z.A.C. designed the research. Z.A.C. performed the experiments; J.R. and Z.A.C. analyzed the data and wrote and edited the manuscript.

Corresponding author

Correspondence to Juri Rappsilber.

Ethics declarations

Competing interests

The 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.

Related links

Key references using this protocol

O’Reilly, F. J. & Rappsilber, J. Nat. Struct. Mol. Biol. (2018): https://doi.org/10.1038/s41594-018-0147-0

Fischer, L., Chen, Z. A. & Rappsilber, J. J. Proteomics 88, 120–128 (2013): https://www.sciencedirect.com/science/article/pii/S1874391913001449?via%3Dihub

Chen, Z. A., Fischer, L., Cox, J. & Rappsilber, J. Mol. Cell. Proteomics 15, 2769–2778 (2016): http://www.mcponline.org/content/15/8/2769.long

Software availability

Skyline is available at https://skyline.ms/wiki/home/software/Skyline/page.view?name=tutorial_ms1_filtering and XiSearch at https://github.com/Rappsilber-Laboratory/XiSearch.

Integrated supplementary information

Supplementary Figure 1 Example results of cross-linking titration experiments for proteins and protein complexes.

(a) The SDS-PAGE image shows the cross-linking titration results for the Pol II complex. The protein/cross-linker molar ratio of 1:1800 (marked with red frame) is optimal for CLMS analysis, since at this ratio, bands of free subunits disappears and a defined band with MW corresponding to monomeric Pol II complex forms, in addition, there is very little oligomeric complex forms. (b) The protein/cross-linker mass ratio of 1:2 is select for CLMS analysis for protein MECP2, the broader band of cross-linked MECP2 confirms the cross-linking reaction, and the different appearance of the band in comparison with the cross-linked protein using a higher ratio of cross-linker indicates that cross-linking reaction is not saturated at the selected condition. (c).The wild type (WT) and the mutant (Mu) versions of protein Tsr1 yield different products when cross-linked. The protein/cross-linker mass ratio of 1:1 is selected for QCLMS analysis, as at this ratio, both the WT and the mutant protein obtain reasonable amount of monomeric cross-linking products.

Supplementary Figure 2 Schematic demonstration of how to generate pseudo identification entries in the .ssl file.

(a) The extracted ion chromatogram (XIC) of the BS3- (light) and the BS3-d4- (heavy) version of a cross-linked peptide (the MS1 spectrum is shown below). The overlapped elution window of the light and the heavy versions of the cross-linked peptide allowed for applying the retention time of the identified MS2 event of the light version as the retention time of the pseudo identification event for the heavy version which not been actually identified. (b) An example on how to generate a pseudo identification entry of a BS3-d4 cross-linked peptide in an .ssl file, based on the MS2 information of the identified BS3 cross-linked version of this cross-linked peptide.

Supplementary Figure 3 Curved HPLC gradient applied for SCX-based enrichment of cross-linked peptides.

The curved gradient is shown on the left and the equation of the curved gradient is shown on the right.

Supplementary Figure 4

Demonstration of how to define modifications in Skyline.

Supplementary Figure 5

Transition settings that need to be defined when quantifying cross-linked peptides.

Supplementary Figure 6

Demonstration of how to build a library in Skyline.

Supplementary Figure 7 Examples of correctly and incorrectly isolated signals.

(a) An example of a correctly isolated chromatographic signal of a peptide. The elution peak is correctly isolated; the isotope distribution of the isolated signals is in good agreement (with the “idotp” close to 1) with the expected pattern calculated based on the sequence of the target peptide; the measured signals of isotope peaks are in good matches with the calculated m/z of isotope peaks of the target peptide. (b) One error on peptide signal picking is incorrectly isolated elution peak of the target peptide. (c) Skyline might pick wrong signals for a target peptide, the error can be indicated by poor agreement on isotope distribution between the expected and the measured pattern, showing as low “idotp”. (d) The mistakenly selected signal may share the same charge as the target peptide which might resulted in an “idotp” value close to one. Such signal picking error would only be revealed when compare isotope peaks of the isolated signal in the MS1 spectra with the m/z of expected isotope peaks of the target peptide.

Supplementary Figure 8 Mis-quantitation of a singlet cross-linked peptide as a consequence of overlapping signals of the light and the heavy versions.

The MS1 spectra show the signals of an example cross-linked peptide in both the forward-labeled (conformer 1+BS3/conformer II+BS3-d4) and the reverse-labeled (conformer I+BS3-d4/conformer II+BS3) analysis. The isotope peaks used for quantitation are highlighted (blue for the light version and pink for the heavy version of the peptide). The extended isotope envelope of the example peptides leads to an overlap between the signals of the light and the heavy versions. Therefore in the forward-labeled dataset, this conformer I-unique cross-linked peptide is mis-quantified as a “doublet” by the automated data process.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Chen, Z.A., Rappsilber, J. Quantitative cross-linking/mass spectrometry to elucidate structural changes in proteins and their complexes. Nat Protoc 14, 171–201 (2019). https://doi.org/10.1038/s41596-018-0089-3

Download citation

Further reading


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.


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