Journal of Biomolecular NMR

, Volume 34, Issue 4, pp 259–269 | Cite as

Identification of Zinc-ligated Cysteine Residues Based on 13Cα and 13Cβ Chemical Shift Data

  • Gregory J. Kornhaber
  • David Snyder
  • Hunter N. B. Moseley
  • Gaetano T. Montelione
Article

Abstract

Although a significant number of proteins include bound metals as part of their structure, the identification of amino acid residues coordinated to non-paramagnetic metals by NMR remains a challenge. Metal ligands can stabilize the native structure and/or play critical catalytic roles in the underlying biochemistry. An atom’s chemical shift is exquisitely sensitive to its electronic environment. Chemical shift data can provide valuable insights into structural features, including metal ligation. In this study, we demonstrate that overlapped 13Cβ chemical shift distributions of Zn-ligated and non-metal-ligated cysteine residues are largely resolved by the inclusion of the corresponding 13Cα chemical shift information, together with secondary structural information. We demonstrate this with a bivariate distribution plot, and statistically with a multivariate analysis of variance (MANOVA) and hierarchical logistic regression analysis. Using 287 13Cα/13Cβ shift pairs from 79 proteins with known three-dimensional structures, including 86 13Cα and13Cβ shifts for 43 Zn-ligated cysteine residues, along with corresponding oxidation state and secondary structure information, we have built a logistic regression model that distinguishes between oxidized cystines, reduced (non-metal ligated) cysteines, and Zn-ligated cysteines. Classifying cysteines/cystines with a statisical model incorporating all three phenomena resulted in a predictor of Zn ligation with a recall, precision and F-measure of 83.7%, and an accuracy of 95.1%. This model was applied in the analysis of Bacillus subtilis IscU, a protein involved in iron–sulfur cluster assembly. The model predicts that all three cysteines of IscU are metal ligands. We confirmed these results by (i) examining the effect of metal chelation on the NMR spectrum of IscU, and (ii) inductively coupled plasma mass spectrometry analysis. To gain further insight into the frequency of occurrence of non-cysteine Zn ligands, we analyzed the Protein Data Bank and found that 78% of the Zn ligands are histidine and cysteine (with nearly identical frequencies), and 18% are acidic residues aspartate and glutamate.

Keywords

chemical shift distribution analysis logistic regression analysis Zn-ligated cysteine 

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References

  1. Acton, T.B., Gunsalus, K.C., Xiao, R., Ma, L.C., Aramini, J., Baran, M.C., Chiang, Y.W., Climent, T., Cooper, B., Denissova, N.G., Douglas, S.M., Everett, J.K., Ho, C.K., Macapagal, D., Rajan, P.K., Shastry, R., Shih, L.Y., Swapna, G.V.T., Wilson, M., Wu, M., Gerstein, M., Inouye, M., Hunt, J.F., Montelione, G.T. 2005Meth. Enzymol.394210243CrossRefGoogle Scholar
  2. Agar, J.N., Krebs, C., Frazzon, J., Huynh, B.H., Dean, D.R., Johnson, M.K. 2000Biochemistry3978567862CrossRefGoogle Scholar
  3. Bateman, A., Coin, L., Durbin, R., Finn, R.D., Hollich, V., Griffiths-Jones, S., Khanna, A., Marshall, M., Moxon, S., Sonnhammer, E.L.L., Studholme, D.J., Yeats, C., Eddy, S.R. 2004Nucleic Acids Res.32138141CrossRefGoogle Scholar
  4. Becker, A., Schlichting, I., Kabsch, W., Groche, D., Schultz, S., Wagner, A.F. 1998Nat. Struct. Biol.510531058CrossRefGoogle Scholar
  5. Berg, J.M., Shi, Y. 1996Science27110811085ADSGoogle Scholar
  6. Clamp, M., Andrews, D., Barker, D., Bevan, P., Cameron, G., Chen, Y., Clark, L., Cox, T., Cuff, J., Curwen, V., Down, T., Durbin, R., Eyras, E., Gilbert, J., Hammond, M., Hubbard, T., Kasprzyk, A., Keefe, D., Lehvaslaiho, H., Iyer, V., Melsopp, C., Mongin, E., Pettett, R., Potter, S., Rust, A., Schmidt, E., Searle, S., Slater, G., Smith, J., Spooner, W., Stabenau, A., Stalker, J., Stupka, E., Ureta-Vidal, A., Vastrik, I., Birney, E. 2003Nucleic Acids Res.313842CrossRefGoogle Scholar
  7. Clarke, N.D., Berg, J.M. 1998Science28220182022CrossRefADSGoogle Scholar
  8. Coplen, T.B., Bohlke, J.K., De Bievre, P., Ding, T., Holden, N.E., Hopple, J.A., Krouse, H.R., Lamberty, A., Peiser, H.S., Revesz, K., Rieder, S.E., Rosman, K.J.R., Roth, E., Taylor, P.D.P., Vocke, R.D., Xiao, Y.K. 2002Pure Appl. Chem.7419872017Google Scholar
  9. Dauter, Z., Wilson, K.S., Sieker, L.C., Moulis, J.M., Meyer, J. 1996Proc. Natl. Acad. Sci. USA9388368840CrossRefADSGoogle Scholar
  10. Drohat, A.C., Kwon, K., Krosky, D.J., Stivers, J.T. 2002Nat. Struct. Biol.9659664CrossRefGoogle Scholar
  11. Everitt, B.S., Dunn, G. 2001Applied Multivariate Data Analysis.ArnoldLondonGoogle Scholar
  12. Fujii, T., Hata, Y., Oozeki, M., Moriyama, H., Wakagi, T., Tanaka, N., Oshima, T. 1997Biochemistry3615051513CrossRefGoogle Scholar
  13. Glusker, J.P., Katz, A.K., Bock, C.W. 1999Rigaku16816Google Scholar
  14. Hernick, M., Fierke, C.A. 2005Arch. Biochem. Biophys.4337184CrossRefGoogle Scholar
  15. Jansson, M., Li, Y.C., Jendeberg, L., Anderson, S., Montelione, B.T., Nilsson, B. 1996J. Biomol. NMR7131141CrossRefGoogle Scholar
  16. Kabsch, W., Sander, C. 1983Biopolymers2225772637CrossRefGoogle Scholar
  17. Klug, A. and Rhodes, D. (1987) Zinc fingers: a novel protein fold for nucleic acid recognition. Cold Spring Harb. Symp. Quant. Biol 52, 473–482Google Scholar
  18. Koradi, R., Billeter, M., Wuthrich, K. 1996J. Mol. Graph.142932Google Scholar
  19. Krishna, S.S., Majumdar, I., Grishin, N.V. 2003Nucleic Acids Res.31532550CrossRefGoogle Scholar
  20. Kwon, K., Cao, C., Stivers, J.T. 2003J. Biol. Chem.2781944219446CrossRefGoogle Scholar
  21. Lipscomb, W.N., Strater, N. 1996Chem. Rev.9623752433CrossRefGoogle Scholar
  22. Liu, J., Oganesyan, N., Shin, D.H., Jancarik, J., Yokota, H., Kim, R., Kim, S.H. 2005Proteins59875881CrossRefGoogle Scholar
  23. Lu, D., Searles, M.A., Klug, A. 2003Nature42696100CrossRefADSGoogle Scholar
  24. Miller, R.G. 1997Beyond ANOVA: Basics of Applied StatisticsChapman & HallBoca Raton, FLMATHGoogle Scholar
  25. Moseley, H.N., Sahota, G., Montelione, G.T. 2004J. Biomol. NMR28341355CrossRefGoogle Scholar
  26. Murzin, A.G., Brenner, S.E., Hubbard, T., Chothia, C. 1995J. Mol. Biol.247536540CrossRefGoogle Scholar
  27. Neuhaus, D., Wagner, G., Vasak, M., Kagi, J.H., Wuthrich, K. 1984Eur. J. Biochem.143659667CrossRefGoogle Scholar
  28. Pelton, J.G., Torchia, D.A., Meadow, N.D., Roseman, S. 1993Protein Sci.2543558CrossRefGoogle Scholar
  29. Ramelot, T.A., Cort, J.R., Goldsmith-Fischman, S., Kornhaber, G.J., Xiao, R., Shastry, R., Acton, T.B., Honig, B., Montelione, G.T., Kennedy, M.A. 2004J. Mol. Biol.344567583CrossRefGoogle Scholar
  30. Rea, P.A. 2003Nat. Biotechnol.2111491151CrossRefGoogle Scholar
  31. Sharma, D., Rajarathnam, K. 2000J. Biomol. NMR18165171CrossRefGoogle Scholar
  32. Taylor, J.R. 1997An introduction to Error Analysis: The Study of Uncertainties in Physical MeasurementsUniversity Science BooksSausalito, CAGoogle Scholar
  33. Vasak, M., Worgotter, E., Wagner, G., Kagi, J.H., Wuthrich, K. 1987J. Mol. Biol.196711719CrossRefGoogle Scholar
  34. Venter, J.C., Adams, M.D., Myers, E.W., Li, P.W., Mural, R.J., Sutton, G.G., Smith, H.O., Yandell, M., Evans, C.A., Holt, R.A., Gocayne, J.D., Amanatides, P., Ballew, R.M., Huson, D.H., Wortman, J.R., Zhang, Q., Kodira, C.D., Zheng, X.Q.H., Chen, L., Skupski, M.,  et al. 2001Science29113041351CrossRefADSGoogle Scholar
  35. Zhang, H.Y., Neal, S., Wishart, D.S. 2003J. Biomol. NMR25173195CrossRefGoogle Scholar
  36. Zheng, L., Cash, V.L., Flint, D.H., Dean, D.R. 1998J. Biol. Chem.2731326413272CrossRefGoogle Scholar
  37. Zhou, Z.S., Peariso, K., Penner-Hahn, J.E., Matthews, R.G. 1999Biochemistry381591515926CrossRefGoogle Scholar

Copyright information

© Springer 2006

Authors and Affiliations

  • Gregory J. Kornhaber
    • 1
    • 2
    • 3
  • David Snyder
    • 1
    • 3
  • Hunter N. B. Moseley
    • 1
    • 3
  • Gaetano T. Montelione
    • 1
    • 2
    • 3
  1. 1.Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and BiochemistryRutgers UniversityPiscatawayUSA
  2. 2.Department of Biochemistry and Molecular BiologyRobert Wood Johnson Medical SchoolPiscatawayUSA
  3. 3.Northeast Structural Genomics ConsortiumPiscatawayUSA

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