Protein Modeling

  • G. Náray-Szabó
  • A. Perczel
  • A. Láng
  • D. K. Menyhárd
Living reference work entry

Abstract

Proteins play a crucial role in biological processes; therefore, understanding their structure and function is very important. In this chapter, we give an overview on computer models of proteins. First, we treat both major experimental structure determination methods, X-ray diffraction and NMR spectroscopy. In subsequent sections, computer modeling techniques as well as their application to the construction of explicit models are discussed. An overview on molecular mechanics and structure prediction is followed by an overview of molecular graphics methods of structure representation. Protein electrostatics and the concept of the solvent-accessible surface are treated in detail. We devote a special section to dynamics, where time scales of molecular motions, structures, and interactions are discussed. Protein in relation to its surroundings is especially important, so protein hydration, ligand binding, and protein-protein interactions receive special attention. The case study of podocin provides an example for the successful application of molecular dynamics to a complex issue. At last, computer modeling of enzyme mechanisms is discussed. It is demonstrated that protein representation by computers arrived to a very high degree of sophistication and reliability; therefore, even lots of experimental studies make use of such models. A list with a large number of up-to-date bibliographic references helps the reader to get informed on further details.

Keywords

Nuclear Magnetic Resonance Nuclear Magnetic Resonance Spectroscopy Solvent Accessible Surface Area Nuclear Overhauser Effect Residual Dipolar Coupling 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

We are indebted to our colleagues Dr. Z. Gáspári, Dr. V. Harmat, and Ms. P. Rovó for important remarks on the manuscript and for providing most of the figures.

Bibliography

  1. Baker, N. A., & McCammon, J. A. (2009). Electrostatic interactions. In J. Gu & P. E. Bourne (Eds.), Structural bioinformatics (2nd ed., p. 575). Chichester: Wiley-Blackwell.Google Scholar
  2. Barabás, O., Pongrácz, V., Kovári, J., Wilmanns, M., & Vértessy, B. G. (2004). Structural insights into the catalytic mechanism of phosphate ester hydrolysis by dUTPase. Journal of Biological Chemistry, 279, 42907.CrossRefGoogle Scholar
  3. Berente, I., Beke, T., & Náray-Szabó, G. (2007). Quantum mechanical studies on the existence of a trigonal bipyramidal phosphorane intermediate in enzymatic phosphate ester hydrolysis. Theoretical Chemistry Accounts, 118, 129.CrossRefGoogle Scholar
  4. Bernardi, F., Bottoni, A., De Vivo, M., Garavelli, M., Keserű, G. M., & Náray-Szabó, G. (2002). A hypothetical mechanism for HIV-1 integrase catalytic action: DFT modelling of a bio-mimetic environment. Chemical Physics Letters, 362, 1.CrossRefGoogle Scholar
  5. Bourgeois, D., & Royant, A. (2005). Advances in kinetic protein crystallography. Current Opinion in Structural Biology, 15, 538.CrossRefGoogle Scholar
  6. Brandén, C., & Tooze, J. (1999). Introduction to protein structure. New York: Garland.Google Scholar
  7. Brás, N. F., Cerqueira, N. M. F. S. A., Sousa, S. F., Fernandes, P. A., & Ramos, M. J. (2014). Protein ligand docking in drug discovery. In G. Náray-Szabó (Ed.), Protein modelling (p. 249). Cham-Heidelberg/New York/Dordrecht/London: Springer.Google Scholar
  8. Bujnicki, J. M. (Ed.). (2009). Prediction of protein structures, functions, and interactions. Chichester: Wiley-Blackwell.Google Scholar
  9. Case, D. A., Cheatham, T. E., III, Darden, T., Gohlke, H., Luo, R., Merz, K. M., Jr., Onufriev, A., Simmerling, C., Wang, B., & Woods, R. (2005). The Amber biomolecular simulation programs. Journal of Combinatorial Chemistry, 26, 1668.Google Scholar
  10. Cavalli, A., Salvatella, X., Dombson, C. M., & Vendruscolo, M. (2007). Protein structure determination from chemical shifts. Proceedings of the National Academy of Sciences of the United States of America, 104, 9615.CrossRefGoogle Scholar
  11. Cavanagh, J., Fairbrother, W. J., Palmer, A. G., III, Rance, M., & Skelton, N. J. (2007). Protein NMR spectroscopy, principles and practice. Amsterdam: Elsevier.Google Scholar
  12. Chaplin, M. (2015). Protein hydration. London South Bank University, http://www1.lsbu.ac.uk/water/protein_hydration.html. Downloaded 18 Mar 2015.
  13. Chayen, N. E. (Ed.). (2007). Protein crystallization strategies for structural genomics (Biotechnology series). La Jolla: International University Line.Google Scholar
  14. Connolly, M. L. (1996). Molecular surfaces: A review. http://www.netsci.org/Science/Compchem/feature14.html. Retrieved on 7 Mar 2011.
  15. Dambrot, S. M. (2012). Small is beautiful: Viewing hydrogen atoms with neutron protein crystallography, http://phys.org/news/2012-09-small-beautiful-viewing-hydrogen-atoms.html. Downloaded: 17 Mar 2015.
  16. Drenth, J. (2007). Principles of protein x-ray crystallography (3rd ed.). New York: Springer.Google Scholar
  17. Ehrlich, L. P., & Wade, R. C. (2001). Protein-protein docking. Reviews in Computational Chemistry, 17, 61.CrossRefGoogle Scholar
  18. Elsasser, B., Valiev, M., & Weare, J. H. (2009). A dianionic phosphorane intermediate and transition states in an associative A(N) + D-N mechanism for the ribonucleaseA hydrolysis reaction. Journal of the American Chemical Society, 131, 3869.CrossRefGoogle Scholar
  19. Emsley, P., & Cowtan, K. (2004). Coot: Model-building tools for molecular graphics. Acta Crystallographica, D60, 2126.Google Scholar
  20. Ferenczy, G. G., & Náray-Szabó, G. (2014). Strictly localised molecular orbitals in QM/MM methods. In G. Náray-Szabó (Ed.), Protein modelling (p. 71). Cham-Heidelberg/New York/Dordrecht/London: Springer.Google Scholar
  21. Fischer, D., Lin, S., Wolfson, H. L., & Nussinov, R. (1995). A geometry-based suite of molecular docking processes. Journal of Molecular Biology, 248, 459.Google Scholar
  22. Fiser, A., & Sali, A. (2003). Modeller: Generation and refinement of homology-based protein structure models. Methods in Enzymology, 374, 461.CrossRefGoogle Scholar
  23. Fitter, J., Gutberlet, T., & Katsaras, J. (Eds.). (2006). Neutron scattering in biology, techniques and applications. Berlin: Springer.Google Scholar
  24. Florián, J., & Warshel, A. (1998). Phosphate ester hydrolysis in aqueous solution: Associative versus dissociative mechanisms. Journal of Physical Chemistry B, 102, 719.CrossRefGoogle Scholar
  25. Fodor, K., Harmat, V., Kardos, J., Antal, J., Hetényi, C., Perczel, A., Szenthe, B., Gáspári, Z., Katona, G., & Gráf, L. (2005). Conformational adaptation of a canonical protease inhibitor upon its binding to the target protease increases specificity. FEBS Journal, 272, 167.Google Scholar
  26. Gao, J., & Truhlar, D. G. (2002). Quantum mechanical methods for enzyme kinetics. Annual Review of Physical Chemistry, 53, 467–505.CrossRefGoogle Scholar
  27. Gilson, M. K., & Honig, B. (1987). Calculation of electrostatic potentials in an enzyme active site. Nature, 330, 84.CrossRefGoogle Scholar
  28. Ginzinger, S. W., Gerick, F., Coles, M., & Heun, V. (2007). CheckShift: Automatic correction of inconsistent chemical shift referencing. Journal of Biomolecular NMR, 39, 223.CrossRefGoogle Scholar
  29. Giorgetti, A., & Carloni, P. (2014). Molecular mechanics/coarse-grained models. In G. Náray-Szabó (Ed.), Protein modelling (p. 165). Cham-Heidelberg/New York/Dordrecht/London: Springer.Google Scholar
  30. Goh, C. S., Milburn, D., & Gerstein, M. (2004). Conformational changes associated with protein-protein interactions. Current Opinion in Structural Biology, 14, 104.CrossRefGoogle Scholar
  31. Gray, J. J., Moughan, S. E., Wang, C., Schueler-Furman, O., Kuhlman, B., Rohl, C. A., & Baker, D. (2003). Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations. Journal of Molecular Biology, 331, 281.CrossRefGoogle Scholar
  32. GROMOS. (2011). Dynamic modelling of molecular systems. https://www1.ethz.ch/igc/GROMOS/. Retrieved on 10 Mar 2011.
  33. Gsponer, J., Hopearuoho, H., Whittaker, S. B. M., Spence, G. R., Moore, G. R., Paci, E., Radford, S. E., & Vendruscolo, M. (2006). Determination of an ensemble of structures representing the intermediate state of the bacterial immunity protein Im7. Proceedings of the National Academy of Sciences of the United States of America, 103, 99.CrossRefGoogle Scholar
  34. Guvencs, O., & MacKerrell, A. D., Jr. (2009). Computational evaluation of protein-small molecule binding. Current Opinion in Structural Biology, 19, 56.CrossRefGoogle Scholar
  35. Güntert, P. (2011). Automated protein structure determination from NMR data. In A. J. Dingley & S. M. Pascal (Eds.), Advances in biomedical spectroscopy, vol. 3: Biomolecular NMR spectroscopy (p. 341). Amsterdam: Ios Press. doi:10.3233/978-1-60750-695-9-338.Google Scholar
  36. Halgren, T. A. (1996). Merck molecular force field. I-V. Journal of Combinatorial Chemistry, 17, 490.Google Scholar
  37. Harmat, V., & Náray-Szabó, G. (2009). Theoretical aspects of molecular recognition. Croatica Chemica Acta, 82, 277.Google Scholar
  38. Horsefield, R., & Neutze, R. (2006). Crystallization of lysozyme by the hanging drop method, http://www.csb.gu.se/rob/PDFs/Crystallisation_Course_2006_Part-I.pdf. Retrieved on 10 Mar 2011.
  39. Hovmöller, S., Zhou, T., & Ohlson, T. (2002). Conformations of amino acids in proteins. Acta Crystallographica, D58, 768.Google Scholar
  40. Hu, Z., & Jiang, J. (2009). Assessment of biomolecular force fields for molecular dynamics simulations in a protein crystal. Journal of Computational Chemistry. doi:10.1002/jcc.21330.Google Scholar
  41. Hu, H., & Yang, W. (2008). Free energies of chemical reactions in solution and in enzymes with ab initio quantum mechanics/molecular mechanics methods. Annual Review of Physical Chemistry, 59, 573.CrossRefGoogle Scholar
  42. Hub, J. S., Grubmüller, H., & de Groot, B. L. (2009). Dynamics and energetics of permeation through aquaporins. What do we learn from molecular dynamics simulations? In E. Beitz (Ed.), Handbook of experimental pharmacology, vol. 190, aquaporins (p. 57). Berlin: Springer.Google Scholar
  43. Jarymowycz, V. A., & Stome, M. J. (2006). Fast time scale dynamics of protein backbones: NMR relaxation methods, applications, and functional consequences. Chemical Reviews, 106, 1624.CrossRefGoogle Scholar
  44. Jiao, D., Golubkov, P. A., Darden, T. A., & Ren, P. (2008). Calculation of protein–ligand binding free energy by using a polarizable potential. Proceedings of the National Academy of Sciences of the United States of America, 105, 6290.CrossRefGoogle Scholar
  45. Katchalski-Katzir, E., Shariv, I., Eisenstein, M., Friesem, A. A., Aflalo, C., & Vakser, I. A. (1992). Molecular surface recognition: Determination of geometric fit between proteins and their ligands by correlation techniques. Proceedings of the National Academy of Sciences of the United States of America, 89, 2195.CrossRefGoogle Scholar
  46. Khoruzhii, O., Butin, O., Illarionov, A., Leontyev, I., Olevanov, M., Ozrin, V., Pereyaslavets, L., & Fain, B. (2014). Polarizable force fields for proteins. In G. Náray-Szabó (Ed.), Protein modelling (p. 91). Cham-Heidelberg/New York/Dordrecht/London: Springer.Google Scholar
  47. Kiss, R., Kovács, D., Tompa, P., & Perczel, A. (2008). Local structural preferences of calpastatin, the intrinsically unstructured protein inhibitor of calpain. Biochemistry, 47, 6936.CrossRefGoogle Scholar
  48. Klähn, M., Rosta, E., & Warshel, A. (2006). On the mechanism of hydrolysis of phosphate monoesters dianions in solutions and proteins. Journal of the American Chemical Society, 128, 15310.CrossRefGoogle Scholar
  49. Krieger, E., Nabuurs, S. B., & Vriend, G. (2003). Homology modeling. Methods of Biochemical Analysis, 44, 509.Google Scholar
  50. Lahiri, S. D., Zhang, G., Dunaway-Mariano, D., & Allen, K. N. (2003). The pentacovalent phosphorus intermediate of a phosphoryl transfer reaction. Science, 299, 2067.CrossRefGoogle Scholar
  51. Lange, O. F., Lakomek, N. A., Fares, C., Schroder, G. F., Walter, K. F. A., Becker, S., Meiler, J., Grubmuller, H., Griesinger, C., & de Groot, B. L. (2008). Recognition dynamics up to microseconds revealed from an RDC-derived ubiquitin ensemble in solution. Science, 320, 1471.CrossRefGoogle Scholar
  52. Lasilla, J. K., Zalatan, J. G., & Herschlag, G. (2011). Biological phosphoryl transfer reactions: Understanding mechanism and catalysis. Annual Review of Biochemistry, 80, 669–702. doi:10.1146/annurev-biochem-060409-092741.CrossRefGoogle Scholar
  53. Lesk, A. M., Bernstein, H. J., & Bernstein, F. C. (2008). Molecular graphics in structural biology. In M. Peitsch & T. Schwede (Eds.), Computational structural biology, methods and applications (p. 729). Singapore: World Scientific Publishing.CrossRefGoogle Scholar
  54. Lin, M. S., Fawzi, N. L., & Head-Gordon, T. (2007). Hydrophobic potential of mean force as a solvation function for protein structure prediction. Structure, 15, 727.CrossRefGoogle Scholar
  55. Lindorff-Larsen, K., Best, R. B., Depristo, M. A., Dobson, C. M., & Vendruscolo, M. (2005). Simultaneous determination of protein structure and dynamics. Nature, 433, 128.CrossRefGoogle Scholar
  56. Luft, J. R., Collins, R. J., Fehrman, N. A., Lauricella, A. M., Veatch, C. K., & DeTitta, G. T. (2003). A deliberate approach to screening for initial crystallization conditions of biological macromolecules. Journal of Structural Biology, 142, 170.CrossRefGoogle Scholar
  57. MacKerell, A. D., Jr. (2004). Empirical force fields for biological macromolecules: Overview and issues. Journal of Computational Chemistry, 25, 1584.CrossRefGoogle Scholar
  58. Makarov, V., Pettitt, B. M., & Feig, M. (2002). Solvation and hydration of proteins and nucleic acids: A theoretical view of simulation and experiment. Accounts of Chemical Research, 35, 376.CrossRefGoogle Scholar
  59. Mancera, R. L. (2007). Molecular modeling of hydration in drug design. Current Opinion in Drug Discovery & Development, 10, 275.Google Scholar
  60. Mehta, N., & Datta, S. N. (2008). Theoretical investigation of redox species in condensed phase. Journal of Chemical Sciences, 119, 501.CrossRefGoogle Scholar
  61. Menyhárd, D. K., & Náray-Szabó, G. (1999). Electrostatic effect on electron transfer at the active site of heme peroxidases: A comparative molecular orbital study on cytochrome C peroxidase and ascorbate peroxidase. Journal of Physical Chemistry B, 103, 227.CrossRefGoogle Scholar
  62. Merlino, A., Krauss, I. R., Albino, A., Pica, A., Vergara, A., Masullo, M., De Vendittis, E., & Sica, F. (2011). Improving protein crystal quality by the without-oil microbatch method: Crystallization and preliminary X-ray diffraction analysis of glutathione synthetase from Pseudoalteromonashaloplanktis. International Journal of Molecular Sciences, 12, 6312.CrossRefGoogle Scholar
  63. Mildvan, A. S. (1997). Mechanisms of signaling and related enzymes. Proteins: Structure, Function, and Genetics, 29, 401.CrossRefGoogle Scholar
  64. Mintseris, J., Wiehe, K., Pierce, B., Anderson, R., Chen, R., Janin, J., & Weng, Z. (2005). Protein-protein docking benchmark 2.0: An update. Proteins: Structure, Function, and Bioinformatics, 60, 214.CrossRefGoogle Scholar
  65. Mohan, V., Gibbs, A. C., Cummings, M. D., Jaeger, E. P., & DesJarlais, R. L. (2005). Docking: Successes and challenges. Current Pharmaceutical Design, 11, 323.CrossRefGoogle Scholar
  66. Náray-Szabó, G. (Ed.). (2014). Protein modelling. Cham-Heidelberg/New York/Dordrecht/London: Springer.Google Scholar
  67. Náray-Szabó, G., Fuxreiter, M., & Warshel, A. (1997). Electrostatic basis of enzyme catalysis. In G. Náray-Szabó & A. Warshel (Eds.), Computational approaches to biochemical reactivity. Dordrecht: Kluwer.Google Scholar
  68. Náray-Szabó, G., Oláh, J., & Krámos, B. (2013). Quantum mechanical modeling: A tool for the understanding of enzyme reactions. Biomolecules, 3, 662.CrossRefGoogle Scholar
  69. Palmer, A. G., III, Kroenke, C. D., & Loria, J. P. (2001). Nuclear magnetic resonance methods for quantifying microsecond-to-millisecond motions in biological macromolecules. Methods in Enzymology, 339, 204.CrossRefGoogle Scholar
  70. Petsko, G. A., & Ringe, D. (2015). Time-resolved crystallography, Petsko & Ringe Laboratories, Brandeis University, http://www.bio.brandeis.edu/prLab/time.html. Downloaded, 17 Mar 2015.
  71. Porollo, A., & Meller, J. (2007). Prediction-based fingerprints of protein interactions. Proteins: Structure, Function, and Bioinformatics, 66, 630.CrossRefGoogle Scholar
  72. Protein Data Bank. (2015). http://www.rcsb.org/pdb/results/results.do?qrid=BA1B8D74&tabtoshow=Current. Retrieved on 13 Mar 2015.
  73. Redfield, C. (2004). NMR studies of partially folded molten globule states. In A. K. Downing (Ed.), Protein NMR techniques (2nd ed.). Totowa: Humana Press.Google Scholar
  74. Richter, B., Gsponer, J., Várnai, P., Salvatella, X., & Vendruscolo, M. (2007). The MUMO (Minimal Under-Restraining Minimal Over-Restraining) method for the determination of native state ensembles of proteins. Journal of Biomolecular NMR, 37, 117.CrossRefGoogle Scholar
  75. Ritchie, D. W. (2008). Recent progress and future directions in protein-protein docking. Current Protein & Peptide Science, 9, 1.CrossRefGoogle Scholar
  76. Rocchia, W., & Spagnuolo, M. (Eds.). (2015). Computational electrostatics for biological applications. Cham-Heidelberg/New York/Dordrecht/London: Springer.Google Scholar
  77. Rosetta@home. http://boinc.bakerlab.org/rosetta/. Retrieved 10 Mar 2011.
  78. Schmucki, R., Yokoyama, S., & Güntert, P. (2009). Automated assignment of NMR chemical shifts using peak-particle dynamics simulation with the DYNASSIGN algorithm. Journal of Biomolecular NMR, 43, 97.CrossRefGoogle Scholar
  79. Schorn, C., & Taylor, B. J. (2004). NMR-spectroscopy: Data acquisition (2nd ed.). New York: Wiley-VCH.CrossRefGoogle Scholar
  80. Schwieters, C. D., Kuszewski, J. J., & Clore, G. M. (2006). Using Xplor-NIH for NMR molecular structure determination. Progress in Nuclear Magnetic Resonance Spectroscopy, 48, 47.CrossRefGoogle Scholar
  81. SWISS-MODEL. A fully automated protein structure homology-modeling server, http://swissmodel.expasy.org/. Retrieved on 10 Mar 2011.
  82. Szenthe, B., Gáspári, Z., Nagy, A., Perczel, A., & Gráf, L. (2004). Same fold with different mobility: Backbone dynamics of small protease inhibitors from the desert locust, Schistocerca gregaria. Biochemistry, 43, 3376.CrossRefGoogle Scholar
  83. Tory, K., Menyhárd, D. K., Woerner, S., Nevo, F., Gribouval, O., Kerti, A., Stráner, P., Arrondel, P., Cong, E. H., Tulassay, T., Mollet, G., Perczel, A., & Antignac, C. (2014). Mutation-dependent recessive inheritance of NPHS2-associated steroid-resistant nephrotic syndrome. Nature Genetics, 46, 299.CrossRefGoogle Scholar
  84. Vakser, I. A. (2014). Protein-protein docking: From interaction to intercome. Biophysical Journal, 107, 1785.CrossRefGoogle Scholar
  85. Van Der Spoel, D., Lindahl, E., Hess, B., Groenhof, G., Mark, A. E., & Berendsen, H. J. (2005). GROMACS: Fast, flexible, and free. Journal of Computational Chemistry, 26, 1701.CrossRefGoogle Scholar
  86. Van Dijk, A. D. J., & Bonvin, A. M. J. J. (2006). Solvated docking: Introducing water into the modelling of biomolecular complexes. Bioinformatics, 22, 2340.CrossRefGoogle Scholar
  87. Volk, J., Herrmann, T., & Wüthrich, K. (2008). Automated sequence-specific protein NMR assignment using the memetic algorithm MATCH. Journal of Biomolecular NMR, 41, 127.CrossRefGoogle Scholar
  88. Wang, W., Donini, O., Reyes, C. M., & Kollman, P. A. (2001). Biomolecular simulations: Recent developments in force fields, simulations of enzyme catalysis, protein-ligand, protein-protein, and protein-nucleic acid noncovalent interactions. Annual Review of Biophysics and Biomolecular Structure, 30, 211.CrossRefGoogle Scholar
  89. Warshel, A. (2003). Computer simulations of enzyme catalysis: methods, progress, and insights. Annual Review of Biophysics and Biomolecular Structure, 32, 425.CrossRefGoogle Scholar
  90. Wüthrich, K. (2002). NMR studies of structure and function of biological macromolecules, http://nobelprize.org/nobel_prizes/chemistry/laureates/2002/wutrich-lecture.pdf. Retrieved on 10 Mar 2011.
  91. Xu, D., & Guo, H. (2008). Ab initio QM/MM studies of the phosphoryl transfer reaction catalyzed by PEP mutase suggest a dissociative metaphosphate transition state. Journal of Physical Chemistry B, 112, 4102.CrossRefGoogle Scholar
  92. Xu, Y., Xu, D., & Liang, J. (2007). Computational methods for protein structure prediction and modeling (Vol. 1–2). New York: Springer.CrossRefGoogle Scholar
  93. Zsoldos, Z., Reida, D., Simona, A., Sadjada, S. B., & Johnson, A. P. (2007). eHiTS: A new fast, exhaustive flexible ligand docking system. Journal of Molecular Graphics and Modelling, 26, 198.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • G. Náray-Szabó
    • 1
  • A. Perczel
    • 1
  • A. Láng
    • 1
  • D. K. Menyhárd
    • 1
  1. 1.Laboratory of Structural Chemistry and Biology, Institute of ChemistryEötvös Loránd University and MTA-ELTE Protein Modelling Research GroupBudapestHungary

Personalised recommendations