Molecular diversity in engineered protein libraries

Current Opinion in Chemical Biology

Volumn 11, Issue 3, 2007, Pages 335-341

  Barakat, Nora H ^a   Love, John J ^a  

^a SAN DIEGO STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AMYLOID BETA PROTEIN[1-42]; BACTERIAL PROTEIN; GREEN FLUORESCENT PROTEIN;

ALGORITHM; AMINO ACID SEQUENCE; FLUORESCENCE; GENETIC CODE; PROTEIN DOMAIN; PROTEIN ENGINEERING; REVIEW;

ALGORITHMS; AMYLOID; GREEN FLUORESCENT PROTEINS; PROTEIN ENGINEERING; SOLUBILITY;

EID: 34250745335     PISSN: 13675931     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cbpa.2007.05.014     Document Type: Review

References (55)

1. Jackson S.E., Craggs T.D., and Huang J.-R. Understanding the folding of GFP using biophysical techniques. Expert Rev Proteomics 3 (2006) 545-559
2. Evanko D. Training GFP to fold. Nat Methods 3 (2006) 76
3. Miyawaki A., Nagai T., and Mizuno H. Engineering fluorescent proteins. Adv Biochem Eng Biotechnol 95 (2005) 1-15
4. Wachter R.M. The family of GFP-like proteins: structure, function, photophysics and biosensor applications. Introduction and perspective. Photochem Photobiol 82 (2006) 339-344
5. Scruggs A.W., Flores C.L., Wachter R., and Woodbury N.W. Development and characterization of green fluorescent protein mutants with altered lifetimes. Biochemistry 44 (2005) 13377-13384
6. Zhang L., Patel H.N., Lappe J.W., and Wachter R.M. Reaction progress of chromophore biogenesis in green fluorescent protein. J Am Chem Soc 128 (2006) 4766-4772
7. Magliery T.J., and Regan L. Reassembled GFP: detecting protein-protein interactions and protein expression patterns. Methods Biochem Anal 47 (2006) 391-405
8. Wilson C.G., Magliery T.J., and Regan L. Detecting protein-protein interactions with GFP-fragment reassembly. Nat Methods 1 (2004) 255-262
9. Waldo G.S. Genetic screens and directed evolution for protein solubility. Curr Opin Chem Biol 7 (2003) 33-38
10. Heim R., Cubitt A.B., and Tsien R.Y. Improved green fluorescence. Nature 373 (1995) 663-664
11. Cubitt A.B., Heim R., Adams S.R., Boyd A.E., Gross L.A., and Tsien R.Y. Understanding, improving and using green fluorescent proteins. Trends Biochem Sci 20 (1995) 448-455
12. Waldo G.S., Standish B.M., Berendzen J., and Terwilliger T.C. Rapid protein-folding assay using green fluorescent protein. Nat Biotechnol 17 (1999) 691-695
13. Cabantous S., Terwilliger T.C., and Waldo G.S. Protein tagging and detection with engineered self-assembling fragments of green fluorescent protein. Nat Biotechnol 23 (2005) 102-107
14. Cabantous S., and Waldo G.S. In vivo and in vitro protein solubility assays using split GFP. Nat Methods 3 (2006) 845-854
15. Cabantous S., Pedelacq J.D., Mark B.L., Naranjo C., Terwilliger T.C., and Waldo G.S. Recent advances in GFP folding reporter and split-GFP solubility reporter technologies. Application to improving the folding and solubility of recalcitrant proteins from Mycobacterium tuberculosis. J Struct Funct Genomics 6 (2005) 113-119
16. Pedelacq J.D., Cabantous S., Tran T., Terwilliger T.C., and Waldo G.S. Engineering and characterization of a superfolder green fluorescent protein. Nat Biotechnol 24 (2006) 79-88. This is a comprehensive description of the use of directed evolution to generate a highly stable GFP variant. A detailed analysis of the crystal structure, and rationale for the increased stability, is provided.
17. Crameri A., Whitehorn E.A., Tate E., and Stemmer W.P. Improved green fluorescent protein by molecular evolution using DNA shuffling. Nat Biotechnol 14 (1996) 315-319
18. Patterson G.H., Knobel S.M., Sharif W.D., Kain S.R., and Piston D.W. Use of the green fluorescent protein and its mutants in quantitative fluorescence microscopy. Biophys J 73 (1997) 2782-2790
19. Wurth C., Guimard N.K., and Hecht M.H. Mutations that reduce aggregation of the Alzheimer's Abeta42 peptide: an unbiased search for the sequence determinants of Aβ amyloidogenesis. J Mol Biol 319 (2002) 1279-1290
20. Wurth C., Kim W., and Hecht M.H. Combinatorial approaches to probe the sequence determinants of protein aggregation and amyloidogenicity. Protein Pept Lett 13 (2006) 279-286
21. Wang W., and Hecht M.H. Rationally designed mutations convert de novo amyloid-like fibrils into monomeric beta-sheet proteins. Proc Natl Acad Sci USA 99 (2002) 2760-2765
22. Kim W., and Hecht M.H. Sequence determinants of enhanced amyloidogenicity of Alzheimer Aβ42 peptide relative to Aβ40. J Biol Chem 280 (2005) 35069-35076
23. Petkova A.T., Ishii Y., Balbach J.J., Antzutkin O.N., Leapman R.D., Delaglio F., and Tycko R. A structural model for Alzheimer's beta-amyloid fibrils based on experimental constraints from solid state NMR. Proc Natl Acad Sci USA 99 (2002) 16742-16747
24. Bradley L.H., Thumfort P.P., and Hecht M.H. De novo proteins from binary-patterned combinatorial libraries. Methods Mol Biol 340 (2006) 53-69. This review provides a detailed description of the application and use of binary patterning to focus molecular diversity and create combinatorial libraries of well-folded de novo proteins.
25. Bradley L.H., Wei Y., Thumfort P., Wurth C., and Hecht M.H. Protein design by binary patterning of polar and nonpolar amino acids. Methods Mol Biol 352 (2007) 155-166
26. Kim W., and Hecht M.H. Generic hydrophobic residues are sufficient to promote aggregation of the Alzheimer's Aβ42 peptide. Proc Natl Acad Sci USA 103 (2006) 15824-15829
27. Nelson R., Sawaya M.R., Balbirnie M., Madsen A.O., Riekel C., Grothe R., and Eisenberg D. Structure of the cross-beta spine of amyloid-like fibrils. Nature 435 (2005) 773-778
28. Kim W., Kim Y., Min J., Kim D.J., Chang Y.T., and Hecht M.H. A high-throughput screen for compounds that inhibit aggregation of the Alzheimer's peptide. ACS Chem Biol 1 (2006) 461-469
29. Dahiyat B.I., and Mayo S.L. De novo protein design: fully automated sequence selection. Science 278 (1997) 82-87
30. Voigt C.A., Mayo S.L., Arnold F.H., and Wang Z.G. Computationally focusing the directed evolution of proteins. J Cell Biochem Suppl 37 (2001) 58-63
31. Meyer M.M., Silberg J.J., Voigt C.A., Endelman J.B., Mayo S.L., Wang Z.G., and Arnold F.H. Library analysis of SCHEMA-guided protein recombination. Protein Sci 12 (2003) 1686-1693
32. Voigt C.A., Martinez C., Wang Z.G., Mayo S.L., and Arnold F.H. Protein building blocks preserved by recombination. Nat Struct Biol 9 (2002) 553-558
33. Patrick W.M., and Firth A.E. Strategies and computational tools for improving randomized protein libraries. Biomol Eng 22 (2005) 105-112
34. Denault M., and Pelletier J.N. Protein library design and screening: working out the probabilities. Methods Mol Biol 352 (2007) 127-154
35. Hayes R.J., Bentzien J., Ary M.L., Hwang M.Y., Jacinto J.M., Vielmetter J., Kundu A., and Dahiyat B.I. Combining computational and experimental screening for rapid optimization of protein properties. Proc Natl Acad Sci USA 99 (2002) 15926-15931. This work represents an excellent example of the use of protein design algorithms to focus sequence space to that which is most probable to produce a mutant protein variant with the desired properties.
36. Mena M.A., Treynor T.P., Mayo S.L., and Daugherty P.S. Blue fluorescent proteins with enhanced brightness and photostability from a structurally targeted library. Nat Biotechnol 24 (2006) 1569-1571
37. Treynor T.P., Vizcarra C.L., Nedelcu D., and Mayo S.L. Computationally designed libraries of fluorescent proteins evaluated by preservation and diversity of function. Proc Natl Acad Sci USA 104 (2007) 48-53. In this work (in conjunction with [36]), seven different protein design algorithms are evaluated for the ability to impart a new function into a protein without destroying the protein altogether. The results of the comparison are evaluated against variants generated by error-prone PCR.
38. Shaner N.C., Steinbach P.A., and Tsien R.Y. A guide to choosing fluorescent proteins. Nat Methods 2 (2005) 905-909
39. Choi E.J., and Mayo S.L. Generation and analysis of proline mutants in protein G. Protein Eng Des Sel 19 (2006) 285-289
40. Tsai H-HG, Tsai C.-J., Ma B., and Nussinov R. In silico protein design by combinatorial assembly of protein building blocks. Protein Sci 13 (2004) 2753-2765
41. Ross S.A., Sarisky C.A., Su A., and Mayo S.L. Designed protein G core variants fold to native-like structures: sequence selection by ORBIT tolerates variation in backbone specification. Protein Sci 10 (2001) 450-454
42. Malakauskas S.M., and Mayo S.L. Design, structure and stability of a hyperthermophilic protein variant. Nat Struct Biol 5 (1998) 470-475
43. Dahiyat B.I., and Mayo S.L. Probing the role of packing specificity in protein design. Proc Natl Acad Sci USA 94 (1997) 10172-10177
44. Distefano M.D., Zhong A., and Cochran A.G. Quantifying β-sheet stability by phage display. J Mol Biol 322 (2002) 179-188
45. Alexander P.A., Rozak D.A., Orban J., and Bryan P.N. Directed evolution of highly homologous proteins with different folds by phage display: implications for the protein folding code. Biochemistry 44 (2005) 14045-14054
46. Kotz J.D., Bond C.J., and Cochran A.G. Phage-display as a tool for quantifying protein stability determinants. Eur J Biochem 271 (2004) 1623-1629
47. Bai Y., and Feng H. Selection of stably folded proteins by phage-display with proteolysis. Eur J Biochem 271 (2004) 1609-1614
48. Feng H., and Bai Y. Repacking of hydrophobic residues in a stable mutant of apocytochrome b562 selected by phage-display and proteolysis. Proteins 56 (2004) 426-429
49. Scalley-Kim M., Minard P., and Baker D. Low free energy cost of very long loop insertions in proteins. Protein Sci 12 (2003) 197-206
50. Minard P., Scalley-Kim M., Watters A., and Baker D. A "loop entropy reduction" phage-display selection for folded amino acid sequences. Protein Sci 10 (2001) 129-134
51. Chu R., Takei J., Knowlton J.R., Andrykovitch M., Pei W., Kajava A.V., Steinbach P.J., Ji X., and Bai Y. Redesign of a four-helix bundle protein by phage display coupled with proteolysis and structural characterization by NMR and X-ray crystallography. J Mol Biol 323 (2002) 253-262
52. Wunderlich M., Martin A., Staab C.A., and Schmid F.X. Evolutionary protein stabilization in comparison with computational design. J Mol Biol 351 (2005) 1160-1168. In this work (as well as that described in [53]), phage display and in vitro proteolysis are used to generate and screen for mutant Gβ1 variants that have increased stability. The results are compared to a previous design of Gβ1 that used computational design algorithms to increase protein stability.
53. Wunderlich M., and Schmid F.X. In vitro evolution of a hyperstable Gβ1 variant. J Mol Biol 363 (2006) 545-557
54. Barakat N.H., Carmody L.J., and Love J.J. Exploiting elements of transcriptional machinery to enhance protein stability. J Mol Biol 366 (2007) 103-116. This work describes a novel application of transcriptional elements to create an in vivo screen for protein stability. The results obtained from the screen are compared and contrasted to those obtained from the application of protein design algorithms.
55. Olson C.A., and Roberts R.W. Design, expression, and stability of a diverse protein library based on the human fibronectin type III domain. Protein Sci 16 (2007) 476-484