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Graph-theoretical assignment of secondary structure in multidimensional protein NMR spectra: Application to the lac repressor headpiece

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Summary

A novel procedure is presented for the automatic identification of secondary structures in proteins from their corresponding NOE data. The method uses a branch of mathematics known as graph theory to identify prescribed NOE connectivity patterns characteristic of the regular secondary structures. Resonance assignment is achieved by connecting these patterns of secondary structure together, thereby matching the connected spin systems to specific segments of the protein sequence. The method known as SERENDIPITY refers to a set of routines developed in a modular fashion, where each program has one or several well-defined tasks. NOE templates for several secondary structure motifs have been developed and the method has been successfully applied to data obtained from NOESY-type spectra. The present report describes the application of the SERENDIPITY protocol to a 3D NOESY-HMQC spectrum of the 15N-labelled lac repressor headpiece protein. The application demonstrates that, under favourable conditions, fully automated identification of secondary structures and semi-automated assignment are feasible.

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Abbreviations

2D, 3D:

two-, three-dimensional

NOESY:

nuclear Overhauser enhancement spectroscopy

HMQC:

heteronuclear multiple quantum coherence

SSE:

secondary structure element

SERENDIPITY:

SEcondary structuRE ideNtification in multiDImensional ProteIn specTra analYsis

References

  • ArtymiukP.J., GrindleyH.M., MitchellE.M., RiceD.W., UjahE.C. and WillettP. (1991) In Recent Advances In Chemical Information (Ed., CollierH.), Royal Society of Chemistry, Cambridge, pp. 91–106.

    Google Scholar 

  • ArtymiukP.J., GrindleyH.M., PoirretteA.R., RiceD.W., UjahE.C. and WillettP. (1994) J. Chem. Inf. Comput. Sci. 34, 54–62.

    Google Scholar 

  • Artymiuk, P.J., Grindley, H.M., MacKenzie, A.B., Rice, D.W., Ujah, E.C. and Willett, P. (1995) In Molecular Similarity and Reactivity (Ed., Carbo, R.) in press.

  • BarrowH.G. and BurstallR.M. (1976) Inform. Proc. Lett. 4, 83–84.

    Google Scholar 

  • BaxA. and GrzesiekC. (1993) Acc. Chem. Res., 26, 131–138.

    Google Scholar 

  • BaxA. (1994) Curr. Opin. Struct. Biol. 4, 738–744.

    Google Scholar 

  • BilleterM., BraunW. and WüthrichK. (1982) J. Mol. Biol., 155, 321–346.

    Google Scholar 

  • BilleterM., BasusV.J. and KuntzI.D. (1988) J. Magn. Reson. 76, 400–415.

    Google Scholar 

  • BrennanR.G. (1992) Curr. Opin. Struct. Biol. 2, 100–108.

    Google Scholar 

  • BrintA.T. and WillettP. (1988) J. Comput.-Aided Mol. Design, 2, 311–320.

    Google Scholar 

  • BronC. and KerboschJ. (1973) Commun. Assoc. Comput. Machinery, 16, 575–577.

    Google Scholar 

  • ChristofidesN., MingozziA., TothP., and SandiS. (Eds) (1979) Combinatorial Optimization, Wiley-Interscience, London.

    Google Scholar 

  • ChuprinaV.P., RullmannJ.A.C., LamerichsR.M.J.V. VanBoomJ.H., BoelensR. and KapteinR. (1993) J. Mol. Biol., 234, 446–462.

    Google Scholar 

  • CieslarC., CloreG.M. and GronenbornA.M. (1988) J. Magn. Reson. 80, 119–127.

    Google Scholar 

  • CloreG.M. and GronenbornA.M. (1994) Methods Enzymol. 239, 349–363.

    Google Scholar 

  • DeVliegJ., BoelensR., ScheekR.M., KapteinR. and VanGunsterenW.F. (1986) Isr. J. Chem. 27, 181–188.

    Google Scholar 

  • DeVliegJ., BoelensR., ScheekR.M., VanGunsterenW.F., BerendsenH.J.C., KapteinR. and ThomasonJ., (1988) Proteins, 3, 209–218.

    Google Scholar 

  • DeoN. (1975) Graph Theory with Applications to Engineering and Computer Science, Prentice Hall, Englewood Cliffs, NJ.

    Google Scholar 

  • EadsC.D. and KuntzI.D. (1989) J. Magn. Reson, 82, 467–482.

    Google Scholar 

  • GrindleyH.M., ArtymiukP.J., RiceD.W. and WillettP. (1993) J. Mol. Biol., 229, 707–721.

    Google Scholar 

  • GroßK.-H. and KalbitzerR. (1988) J. Magn. Reson, 76, 87–99.

    Google Scholar 

  • HararyF. (1972) Graph Theory, Addison-Wesley, Reading, MA.

    Google Scholar 

  • HarrisonS.C. (1991) Nature, 353, 715–719.

    Google Scholar 

  • IkuraM., KayL.E. and BaxA. (1990) Biochemistry, 29, 4659–4667.

    Google Scholar 

  • KabschW. and SanderC. (1983) Biopolymers, 22, 2577–2637.

    Google Scholar 

  • KapteinR., ZuiderwegE.R.P., ScheekR.M., BoelensR. and VanGunsterenW.F. (1985) J. Mol. Biol. 182, 179–182.

    Google Scholar 

  • KleywegtG.J., VuisterG.W., PadillaA., KnegtelR.M.A., BoelensR. and KapteinR. (1993) J. Magn. Reson. Ser. B, 102, 166–176.

    Google Scholar 

  • KraulisP.J. (1989) J. Magn. Reson., 84, 627–633.

    Google Scholar 

  • KraulisP.J. (1991) J. Appl. Crystallogr. 24, 946–950.

    Google Scholar 

  • LaskowskiR.A., MacArthurM.W., MossD.S. and ThorntonJ.M. (1993) J. Appl. Crystallogr., 26, 283–290.

    Google Scholar 

  • LauH. (1989) Algorithms on Graphs, TAB Books Inc., Blue Ridge Summit, PA.

    Google Scholar 

  • LiuX., BalasubramanianK. and MunkM.E. (1990) J. Magn. Reson., 87, 457–474.

    Google Scholar 

  • MarionD., DriscollL.E., KayP.T., WingfieldA., BaxA., GronenbornA.M. and CloreG.M. (1989) Biochemistry 28, 6150–6156.

    Google Scholar 

  • McGregorJ.J. (1982) Software — Pract. Exp., 12, 23–34.

    Google Scholar 

  • MeadowsR.P., OlejniczakE.T. and FesikS.W. (1994) J. Biomol. NMR, 4, 79–96.

    Google Scholar 

  • NelsonS.J., SchneiderD.M. and WandA.J. (1991) Biophys. J., 59, 1113–1122.

    Google Scholar 

  • OschkinatH., GriesingerC., KraulisP.J., SørensenO.W., ErnstR.R., GronenbornA.M. and CloreG.M. (1988) Nature 332, 374–376.

    Google Scholar 

  • OschkinatH., HolakT.A. and CieslarC. (1991) Biopolymers, 31, 699–712.

    Google Scholar 

  • PfändlerP. and BodenhausenG. (1988) J. Magn. Reson., 79, 99–123.

    Google Scholar 

  • RichardsonJ.S. (1981) Adv. Protein Chem., 34, 167–339.

    Google Scholar 

  • RicharzR. and WüthrichK. (1978) Biopolymers, 17, 2133–2141.

    Google Scholar 

  • RouvrayD.H. (Ed.) (1991) Computational Chemical Graph Theory, Nova, New York, NY.

    Google Scholar 

  • SchulzG.E. and SchirmerR.H. (1979) Principles of Protein Structure, Springer, Berlin.

    Google Scholar 

  • Ujah, E.C. (1992) Ph.D. Thesis, University of Sheffield, Sheffield.

  • WandA.J. and NelsonS.J. (1991) Biophys. J., 59, 1101–1112.

    Google Scholar 

  • WishartD.S., SykesB.D. and RichardsF.M. (1991) J. Mol. Biol., 222, 311–333.

    Google Scholar 

  • WishartD.S. and SykesB.D. (1994) J. Biomol. NMR, 4, 171–180.

    Google Scholar 

  • WüthrichK., BilleterM. and BraunW. (1984) J. Mol. Biol. 180, 715–740.

    Google Scholar 

  • WüthrichK. (1986) NMR of Proteins and Nucleic Acids, Wiley, New York, NY.

    Google Scholar 

  • XuJ., GrayB., and SanctuaryB.C. (1993) J. Chem. Inf. Comput. Sci., 33, 475–489.

    Google Scholar 

  • XuJ. and SanctuaryB.C. (1993) J. Chem. Inf. Comput. Sci., 33, 490–500.

    Google Scholar 

  • XuJ., StraussS.K., SanctuaryB.C. and TrimbleL. (1994) J. Magn. Reson. Ser. B, 103, 53–58.

    Google Scholar 

  • ZuiderwegE.R.P., KapteinR. and WüthrichK. (1983a) Proc. Natl. Acad. Sci. USA, 80, 5837–5841.

    Google Scholar 

  • ZuiderwegE.R.P., KapteinR. and WüthrichK. (1983b) Eur. J. Biochem., 137, 279–292.

    Google Scholar 

  • ZuiderwegE.R.P. and FesikS.W. (1989) Biochemistry, 28, 2387–2391.

    Google Scholar 

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Supplementary Material available from the authors: Two tables containing the total number of mappings resulting from the graph search procedure for simulated and experimental NOE data.

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van Geerestein-Ujah, E.C., Slijper, M., Boelens, R. et al. Graph-theoretical assignment of secondary structure in multidimensional protein NMR spectra: Application to the lac repressor headpiece. J Biomol NMR 6, 67–78 (1995). https://doi.org/10.1007/BF00417493

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  • DOI: https://doi.org/10.1007/BF00417493

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