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Combinatorial Protein Design Strategies Using Computational Methods

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Protein Engineering Protocols

Part of the book series: Methods in Molecular Biology™ ((MIMB,volume 352))

Abstract

Computational methods continue to facilitate efforts in protein design. Most of this work has focused on searching sequence space to identify one or a few sequences compatible with a given structure and functionality. Probabilistic computational methods provide information regarding the range of amino acid variability permitted by desired functional and structural constraints. Such methods may be used to guide the construction of both individual sequences and combinatorial libraries of proteins.

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References

  1. Go, N. (1983) Theoretical studies of protein folding. Annu. Rev. Biophys. Bioeng. 12, 183–210.

    Article  PubMed  CAS  Google Scholar 

  2. Shea, J. E. and Brooks, C. L. 3rd. (2001) From folding theories to folding proteins: a review and assessment of simulation studies of protein folding and unfolding. Annu. Rev. Phys. Chem. 52, 499–535.

    Article  PubMed  CAS  Google Scholar 

  3. Brooks, C. L. 3rd. (2002) Protein and peptide folding explored with molecular simulations. Acc. Chem. Res. 35, 447–454.

    Article  PubMed  CAS  Google Scholar 

  4. Kraemer-Pecore, C. M., Wollacott, A. M., and Desjarlais, J. R. (2001) Computational protein design. Curr. Opin. Chem. Biol. 5, 690–695.

    Article  PubMed  CAS  Google Scholar 

  5. Bryson, J. W., Betz, S. F., Lu, H. S., et al. (1995) Protein design: a hierarchic approach. Science 270, 935–941.

    Article  PubMed  CAS  Google Scholar 

  6. Dunbrack, R. (2002) Rotamer libraries. Curr. Opin. Struct. Biol. 12, 431–440.

    Article  PubMed  CAS  Google Scholar 

  7. Shakhnovich, E. I. and Gutin, A. M. (1993) A new approach to the design of stable proteins. Protein Eng. 6, 793–800.

    Article  PubMed  CAS  Google Scholar 

  8. Jones, D. T. (1994) De novo protein design using pairwise potentials and a genetic algorithm. Protein Sci. 3, 567–574.

    Article  PubMed  CAS  Google Scholar 

  9. Hellinga, H. W. and Richards, F. M. (1994) Optimal sequence selection in proteins of known structure by simulated evolution. Proc. Natl. Acad. Sci. USA 91, 5803–5807.

    Article  PubMed  CAS  Google Scholar 

  10. Desjarlais, J. R. and Handel, T. M. (1995) De-novo design of the hydrophobic cores of proteins. Protein Sci. 4, 2006–2018.

    Article  PubMed  CAS  Google Scholar 

  11. Johnson, E. C., Lazar, G. A., Desjarlais, J. R., and Handel, T. M. (1999) Solution structure and dynamics of a designed hydrophobic core variant of ubiquitin. Struct. Fold. Des. 7, 967–976.

    Article  CAS  Google Scholar 

  12. Jiang, X., Farid, H., Pistor, E., and Farid, R. S. (2000) A new approach to the design of uniquely folded thermally stable proteins. Protein Sci. 9, 403–416.

    Article  PubMed  CAS  Google Scholar 

  13. Jiang, X., Bishop, E. J., and Farid, R. S. (1997) A de novo designed protein with properties that characterize natural hyperthermophilic proteins. J. Am. Chem. Soc. 119, 838, 839.

    Article  CAS  Google Scholar 

  14. Bryson, J. W., Desjarlais, J. R., Handel, T. M., and DeGrado, W. F. (1998) From coiled coils to small globular proteins: design of a native-like three-helix bundle. Protein Sci. 7, 1404–1414.

    Article  PubMed  CAS  Google Scholar 

  15. Walsh, S. T. R., Cheng, H., Bryson, J. W., Roder, H., and DeGrado, W. F. (1999) Solution structure and dynamics of a denovo designed three-helix bundle protein. Proc. Natl. Acad. Sci. USA 96, 5486–5491.

    Article  PubMed  CAS  Google Scholar 

  16. Voigt, C. A., Gordon, D. B., and Mayo, S. L. (2000) Trading accuracy for speed: a quantitative comparison of search algorithms in protein sequence design. J. Mol. Biol. 299, 789–803.

    Article  PubMed  CAS  Google Scholar 

  17. Gordon, D. B. and Mayo, S. L. (1998) Radical performance enhancements for combinatorial optimization algorithms based on the dead-end elimination theorem. J. Comput. Chem. 19, 1505–1514.

    Article  CAS  Google Scholar 

  18. Gordon, D. B. and Mayo, S. L. (1999) Branch-and terminate: a combinatorial optimization algorithm for protein design. Struct. Fold. Des. 7, 1089–1098.

    Article  CAS  Google Scholar 

  19. Pierce, N. A., Spriet, J. A., Desmet, J., and Mayo, S. L. (2000) Conformational splitting: a more powerful criterion for dead-end elimination. J. Comput. Chem. 21, 999–1009.

    Article  CAS  Google Scholar 

  20. Looger, L. L. and Hellinga, H. W. (2001) Generalized dead-end elimination algorithms make large-scale protein side-chain structure prediction tractable: implications for protein design and structural genomics. J. Mol. Biol. 307, 429–445.

    Article  PubMed  CAS  Google Scholar 

  21. Dahiyat, B. I. and Mayo, S. L. (1997) De novo protein design: fully automated sequence selection. Science 278, 82–87.

    Article  PubMed  CAS  Google Scholar 

  22. Marshall, S. A. and Mayo, S. L. (2001) Achieving stability and conformational specificity in designed proteins via binary patterning. J. Mol. Biol. 305, 619–631.

    Article  PubMed  CAS  Google Scholar 

  23. Malakauskas, S. M. and Mayo, S. L. (1998) Design, structure, and stability of a hyperthermophilic protein variant. Nat. Struct. Biol. 5, 470–475.

    Article  PubMed  CAS  Google Scholar 

  24. Strop, P. and Mayo, S. L. (1999) Rubredoxin variant folds without iron. J. Am. Chem. Soc. 121, 2341–2345.

    Article  CAS  Google Scholar 

  25. Shimaoka, M., Shifman, J. M., Jing, H., Takagi, L., Mayo, S. L., and Springer, T. A. (2000) Computational design of an integrin i domain stabilized in the open high affinity conformation. Nat. Struct. Biol. 7, 674–678.

    Article  PubMed  CAS  Google Scholar 

  26. Benson, D. E., Wisz, M. S., Liu, W., and Hellinga, H. W. (1998) Construction of a novel redox protein by rational design: conversion of a disulfide bridge into a mononuclear iron-sulfur center. Biochemistry 37, 7070–7076.

    Article  PubMed  CAS  Google Scholar 

  27. DeGrado, W. F., Summa, C. M., Pavone, V., Nastri, F., and Lombardi, A. (1999) De novo design and structural characterization of proteins and metalloproteins. Annu. Rev. Biochem. 68, 779–819.

    Article  PubMed  CAS  Google Scholar 

  28. Bolon, D. N. and Mayo, S. L. (2001) Enzyme-like proteins by computational design. Proc. Natl. Acad. Sci. USA 98, 14,274–14,279.

    Article  PubMed  CAS  Google Scholar 

  29. Street, A. G. and Mayo, S. L. (1999) Computational protein design. Struct. Fold. Des. 7, R105–R109.

    Article  CAS  Google Scholar 

  30. Saven, J. G. (2001) Designing protein energy landscapes. Chem. Rev. 101, 3113–3130.

    Article  PubMed  CAS  Google Scholar 

  31. Gromiha, M. M., Uedaira, H., An, J., Selvaraj, S., Prabakaran, P., and Sarai, A. (2002) Protherm, thermodynamic database for proteins and mutants: developments in version 3.0. Nucleic Acids Res. 30, 301, 302.

    Article  PubMed  CAS  Google Scholar 

  32. Calhoun, J. R., Kono, H., Lahr, S., Wang, W., DeGrado, W. F., and Saven, J. G. (2003) Computational design and characterization of a monomeric helical dinuclear metalloprotein. J. Mol. Biol. 334, 1101–1115.

    Article  PubMed  CAS  Google Scholar 

  33. Slovic, A. M., Kono, H., Lear, J. D., Saven, J. G., and DeGrado, W. F. (2004) Computational design of water-soluble analogues of the potassium channel kcsa. Proc. Natl. Acad. Sci. USA 101, 1828–1833.

    Article  PubMed  CAS  Google Scholar 

  34. Zou, J. and Saven, J. G. (2003) Using self-consistent fields to bias monte carlo methods with applications to designing and sampling protein sequences. J. Chem. Phys. 118, 3843–3854.

    Article  CAS  Google Scholar 

  35. Park, S., Kono, H., Wang, W., Boder, E. T., and Saven, J. G. (2005) Progress in the development and application of computational methods for probabilistic protein design. Comp. Chem. Eng. 24, 407–421.

    Article  Google Scholar 

  36. Keefe, A. D. and Szostak, J. W. (2001) Functional proteins from a random-sequence library. Nature 410, 715–718.

    Article  PubMed  CAS  Google Scholar 

  37. Rojas, N. R. L., Kamtekar, S., Simons, C. T., et al. (1997) De novo heme proteins from designed combinatorial libraries. Protein Sci. 6, 2512–2524.

    PubMed  CAS  Google Scholar 

  38. Roy, S., Ratnaswamy, G., Boice, J. A., Fairman, R., McLendon, G., and Hecht, M. H. (1997) A protein designed by binary patterning of polar and nonpolar amino acids displays native-like properties. J. Am. Chem. Soc. 119, 5302–5306.

    Article  CAS  Google Scholar 

  39. Roy, S., Helmer, K. J., and Hecht, M. H. (1997) Detecting native-like properties in combinatorial libraries of de novo proteins. Fold. Des. 2, 89–92.

    Article  PubMed  CAS  Google Scholar 

  40. Finucane, M. D., Tuna, M., Lees, J. H., and Woolfson, D. N. (1999) Core-directed protein design. I. An experimental method for selecting stable proteins from combinatorial libraries. Biochemistry 38, 11,604, 11,612.

    Article  PubMed  CAS  Google Scholar 

  41. Xu, G. F., Wang, W. X., Groves, J. T., and Hecht, M. H. (2001) Self-assembled monolayers from a designed combinatorial library of de novo beta-sheet proteins. Proc. Natl. Acad. Sci. USA 98, 3652–3657.

    Article  PubMed  CAS  Google Scholar 

  42. Case, M. A. and McLendon, G. L. (2000) A virtual library approach to investigate protein folding and internal packing. J. Am. Chem. Soc. 122, 8089, 8090.

    Article  CAS  Google Scholar 

  43. Arndt, K. M., Pelletier, J. N., Müller, K. M., Alber, T., Michnick, S. W., and Plückthun, A. (2000) A heterodimeric coiled-coil peptide pair selected in vivo from a designed library-versus-library ensemble. J. Mol. Biol. 295, 627–639.

    Article  PubMed  CAS  Google Scholar 

  44. Zhao, H. M. and Arnold, F. H. (1997) Combinatorial protein design: strategies for screening protein libraries. Curr. Opin. Struct. Biol. 7, 480–485.

    Article  PubMed  CAS  Google Scholar 

  45. Giver, L. and Arnold, F. H. (1998) Combinatorial protein design by in vitro recombination. Curr. Opin. Chem. Biol. 2, 335–338.

    Article  PubMed  CAS  Google Scholar 

  46. Hoess, R. H. (2001) Protein design and phage display. Chem. Rev. 101, 3205–3218.

    Article  PubMed  CAS  Google Scholar 

  47. Moffet, D. A. and Hecht, M. H. (2001) De novo proteins from combinatorial libraries. Chem. Rev. 101, 3191–3203.

    Article  PubMed  CAS  Google Scholar 

  48. Holm, L. and Sander, C. (1998) Touring protein fold space with dali/fssp. Nucleic Acids Res. 26, 316–319.

    Article  PubMed  CAS  Google Scholar 

  49. Luthy, R., Bowie, J. U., and Eisenberg, D. (1992) Assessment of protein models with 3-dimensional profiles. Nature 356, 83–85.

    Article  PubMed  CAS  Google Scholar 

  50. Durbin, R., Eddy, S., Krogh, A., and Mitchison, G. (1998) Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. Cambridge University Press, Cambridge, UK.

    Book  Google Scholar 

  51. Raha, K., Wollacott, A. M., Italia, M. J., and Desjarlais, J. R. (2000) Prediction of amino acid sequence from structure. Protein Sci. 9, 1106–1119.

    Article  PubMed  CAS  Google Scholar 

  52. Kuhlman, B. and Baker, D. (2000) Native protein sequences are close to optimal for their structures. Proc. Natl. Acad. Sci. USA 97, 10,383–10,388.

    Article  PubMed  CAS  Google Scholar 

  53. Koehl, P. L. M. (1999) De novo protein design. I. In search of stability and specificity. J. Mol. Biol. 239, 1161–1181.

    Article  Google Scholar 

  54. Koehl, P. L. M. (1999) De novo protein design. II. Plasticity in sequence space. J. Mol. Biol. 293, 1183–1193.

    Article  PubMed  CAS  Google Scholar 

  55. Kraemer-Pecore, C. M., Lecomte, J. T., and Desjarlais, J. R. (2003) A de novo redesign of the ww domain. Protein Sci. 12, 2194–2205.

    Article  PubMed  CAS  Google Scholar 

  56. Larson, S. M., England, J. L., Desjarlais, J. R., and Pande, V. S. (2002) Thoroughly sampling sequence space: large-scale protein design of structural ensembles. Protein Sci. 11, 2804–2813.

    Article  PubMed  CAS  Google Scholar 

  57. Hayes, R. J., Bentzien, J., Ary, M. L., Hwang, M. Y., Jacinto, J. M., Vielmetter, J., Kundu, A., and Dahiyat, B. I. (2002) Combining computational and experimental screening for rapid optimization of protein properties. Proc. Natl. Acad. Sci. USA 99, 15,926–15,931.

    Article  PubMed  CAS  Google Scholar 

  58. Zou, J. and Saven, J. G. (2000) Statistical theory of combinatorial libraries of folding proteins: energetic discrimination of a target structure. J. Mol. Biol. 296, 281–294.

    Article  PubMed  CAS  Google Scholar 

  59. Kono, H. and Saven, J. G. (2001) Statistical theory for protein combinatorial libraries. Packing interactions, backbone flexibility, and the sequence variability of a main-chain structure. J. Mol. Biol. 306, 607–628.

    Article  PubMed  CAS  Google Scholar 

  60. Dunbrack, R. and Cohen, F. E. (1997) Bayesian statistical analysis of protein side-chain retainer preferences. Protein Sci. 6, 1661–1681.

    Article  PubMed  CAS  Google Scholar 

  61. McQuarrie, D. A. (1976) Statistical mechanics. Harper and Row, New York.

    Google Scholar 

  62. Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P. (1992) Numerical recipes. 2nd ed., Cambridge University Press, Cambridge, UK.

    Google Scholar 

  63. Weiner, S. J., Kollman, P. A., Case, D. A., et al. (1984) A new force field for molecular mechanical simulation of nucleic acids and proteins. J. Am. Chem. Soc. 106, 765–784.

    Article  CAS  Google Scholar 

  64. Kono, H. and Doi, J. (1996) A new method for side-chain conformation prediction using a hopfield network and reproduced rotamers. J. Comput. Chem. 17, 1667–1683.

    CAS  Google Scholar 

  65. Wernisch, L., Hery, S., and Wodak, S. J. (2000) Automatic protein design with all atom force-fields by exact and heuristic optimization. J. Mol. Biol. 301, 713–736.

    Article  PubMed  CAS  Google Scholar 

  66. Sander, C. and Schneider, R. (1991) Database of homology-derived protein structures and the structural meaning of sequence alignment. Proteins 9, 56–68.

    Article  PubMed  CAS  Google Scholar 

  67. Jensen, L. J., Andersen, K. V., Svendsen, A., and Kretzschmar, T. (1998) Scoring functions for computational algorithms applicable to the design of spiked oligonucleotides. Nucleic Acids Res. 26, 697–702.

    Article  PubMed  CAS  Google Scholar 

  68. Wolf, E. and Kim, P. S. (1999) Combinatorial codons: a computer program to approximate amino acid probabilities with biased nucleotide usage. Protein Sci. 8, 680–688.

    Article  PubMed  CAS  Google Scholar 

  69. Wang, W. and Saven, J. G. (2002) Designing gene libraries from protein profiles for combinatorial protein experiments. Nucleic Acids Res. 30, e120.

    Article  PubMed  Google Scholar 

  70. Eriksson, A. E., Baase, W. A., Zhang, X. J., Heinz, D. W., Blaber, M., Baldwin, E. P., and Matthews, B. W. (1992) Response of a protein structure to cavity-creating mutations and its relation to the hydrophobic effect. Science 255, 178–183.

    Article  PubMed  CAS  Google Scholar 

  71. Axe, D. D., Foster, N. W., and Fersht, A. R. (1996) Active barnase variants with completely random hydrophobic cores. Proc. Natl. Acad. Sci. USA 93, 5590–5594.

    Article  PubMed  CAS  Google Scholar 

  72. Voigt, C. A., Mayo, S. L., Arnold, F. H., and Wang, Z. G. (2001) Computational method to reduce the search space for directed protein evolution. Proc. Natl. Acad. Sci. USA 98, 3778–3783.

    Article  PubMed  CAS  Google Scholar 

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Kono, H., Wang, W., Saven, J.G. (2007). Combinatorial Protein Design Strategies Using Computational Methods. In: Arndt, K.M., Müller, K.M. (eds) Protein Engineering Protocols. Methods in Molecular Biology™, vol 352. Humana Press. https://doi.org/10.1385/1-59745-187-8:3

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  • DOI: https://doi.org/10.1385/1-59745-187-8:3

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-58829-072-4

  • Online ISBN: 978-1-59745-187-1

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