Computational protein design with explicit consideration of surface hydrophobic patches

Proteins: Structure, Function and Bioinformatics

Volumn 80, Issue 3, 2012, Pages 825-838

  Jacak, Ron ^a   Leaver Fay, Andrew ^a   Kuhlman, Brian ^a  

^a UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

Author keywords

Computational protein design; Protein solubility; Protein stability; Rosetta

Indexed keywords

AMINO ACID;

AMINO ACID SEQUENCE; ARTICLE; COMPUTER PROGRAM; HYDROPHOBICITY; PRIORITY JOURNAL; PROTEIN FUNCTION; PROTEIN PROTEIN INTERACTION; PROTEIN STABILITY; PROTEIN STRUCTURE; SURFACE PROPERTY;

DATABASES, PROTEIN; HYDROPHOBIC AND HYDROPHILIC INTERACTIONS; MODELS, MOLECULAR; PROTEIN STABILITY; PROTEIN UNFOLDING; PROTEINS; SOLUBILITY; THERMODYNAMICS;

EID: 84856769805     PISSN: 08873585     EISSN: 10970134     Source Type: Journal    
DOI: 10.1002/prot.23241     Document Type: Article

References (42)

1. Schreiber G, Buckle AM, Fersht AR. Stability and function: two constraints in the evolution of barstar and other proteins. Structure 1994; 2: 945-951.
2. Poso D, Sessions RB, Lorch M, Clarke AR. Progressive stabilization of intermediate and transition states in protein folding reactions by introducing surface hydrophobic residues. J Biol Chem 2000; 275: 35723-35726.
3. Schindler T, Perl D, Graumann P, Sieber V, Marahiel MA, Schmid FX. Surface-exposed phenylalanines in the RNP1/RNP2 motif stabilize the cold-shock protein CspB from Bacillus subtilis. Proteins 1998; 30: 401-406.
4. Dantas G, Corrent C, Reichow SL, Havranek JJ, Eletr ZM, Isern NG, Kuhlman B, Varani G, Merritt EA, Baker D. High-resolution structural and thermodynamic analysis of extreme stabilization of human procarboxypeptidase by computational protein design. J Mol Biol 2007; 366: 1209-1221.
5. Lawrence MS, Phillips KJ, Liu DR. Supercharging proteins can impart unusual resilience. J Am Chem Soc 2007; 129: 10110-10112.
6. Jones S, Thornton JM. Principles of protein-protein interactions. Proc Natl Acad Sci USA 1996; 93: 13-20.
7. Janin J, Miller S, Chothia C. Surface, subunit interfaces and interior of oligomeric proteins. J Mol Biol 1988; 204: 155-164.
8. Chiti F, Stefani M, Taddei N, Ramponi G, Dobson CM. Rationalization of the effects of mutations on peptide and protein aggregation rates. Nature 2003; 424: 805-808.
9. Jaramillo A, Wernisch L, Hery S, Wodak SJ. Folding free energy function selects native-like protein sequences in the core but not on the surface. Proc Natl Acad Sci USA 2002; 99: 13554-13559.
10. Pokala N, Handel TM. Energy functions for protein design: adjustment with protein-protein complex affinities, models for the unfolded state, and negative design of solubility and specificity. J Mol Biol 2005; 347: 203-227.
11. Dahiyat BI, Gordon DB, Mayo SL. Automated design of the surface positions of protein helices. Protein Sci 1997; 6: 1333-1337.
12. Dahiyat BI, Sarisky CA, Mayo SL. De novo protein design: towards fully automated sequence selection. J Mol Biol 1997; 273: 789-796.
13. Dahiyat BI, Mayo SL. Probing the role of packing specificity in protein design. Proc Natl Acad Sci USA 1997; 94: 10172-10177.
14. Sun S, Brem R, Chan HS, Dill KA. Designing amino acid sequences to fold with good hydrophobic cores. Protein Eng 1995; 8: 1205-1213.
15. Wernisch L, Hery S, Wodak SJ. Automatic protein design with all atom force-fields by exact and heuristic optimization. J Mol Biol 2000; 301: 713-736.
16. Havranek JJ, Harbury PB. Automated design of specificity in molecular recognition. Nat Struct Biol 2003; 10: 45-52.
17. Alvizo O, Mayo SL. Evaluating and optimizing computational protein design force fields using fixed composition-based negative design. Proc Natl Acad Sci USA 2008; 105: 12242-12247.
18. Koehl P, Levitt M. De novo protein design. I. In search of stability and specificity. J Mol Biol 1999; 293: 1161-1181.
19. Kuhlman B, Baker D. Native protein sequences are close to optimal for their structures. Proc Natl Acad Sci USA 2000; 97: 10383-10388.
20. Kuhlman B, Dantas G, Ireton GC, Varani G, Stoddard BL, Baker D. Design of a novel globular protein fold with atomic-level accuracy. Science 2003; 302: 1364-1368.
21. Rohl CA, Strauss CE, Misura KM, Baker D. Protein structure prediction using Rosetta. Methods Enzymol 2004; 383: 66-93.
22. Lazaridis T, Karplus M. Effective energy function for proteins in solution. Proteins 1999; 35: 133-152.
23. Simons KT, Ruczinski I, Kooperberg C, Fox BA, Bystroff C, Baker D. Improved recognition of native-like protein structures using a combination of sequence-dependent and sequence-independent features of proteins. Proteins 1999; 34: 82-95.
24. Kortemme T, Morozov AV, Baker D. An orientation-dependent hydrogen bonding potential improves prediction of specificity and structure for proteins and protein-protein complexes. J Mol Biol 2003; 326: 1239-1259.
25. Dunbrack RL, Jr, Cohen FE. Bayesian statistical analysis of protein side-chain rotamer preferences. Protein Sci 1997; 6: 1661-1681.
26. Krissinel E, Henrick K. Inference of macromolecular assemblies from crystalline state. J Mol Biol 2007; 372: 774-797.
27. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE. The Protein Data Bank. Nucleic Acids Res 2000; 28: 235-242.
28. Li W, Godzik A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 2006; 22: 1658-1659.
29. Leaver-Fay A, Butterfoss GL, Snoeyink J, Kuhlman B. Maintaining solvent accessible surface area under rotamer substitution for protein design. J Comput Chem 2007; 28: 1336-1341.
30. Le Grand S, Merz K. Rapid approximation to molecular surface area via the use of Boolean logic and look-up tables. J Comput Chem 1993; 14: 349-352.
31. Lijnzaad P, Berendsen HJ, Argos P. A method for detecting hydrophobic patches on protein surfaces. Proteins 1996; 26: 192-203.
32. Galler B, Fisher MJ. An improved equivalence algorithm. Commun ACM 1964; 7: 301-303.
33. Chothia C. The nature of the accessible and buried surfaces in proteins. J Mol Biol 1976; 105: 1-12.
34. Wang G, Dunbrack RL, Jr. PISCES: a protein sequence culling server. Bioinformatics 2003; 19: 1589-1591.
35. Kellogg EH, Leaver-Fay A, Baker D. Role of conformational sampling in computing mutation-induced changes in protein structure and stability. Proteins 2010; 79: 830-838.
36. Yin S, Ding F, Dokholyan NV. Modeling backbone flexibility improves protein stability estimation. Structure 2007; 15: 1567-1576.
37. Guerois R, Nielsen JE, Serrano L. Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations. J Mol Biol 2002; 320: 369-387.
38. Creamer TP, Srinivasan R, Rose GD. Modeling unfolded states of peptides and proteins. Biochemistry 1995; 34: 16245-16250.
39. Correia BE, Ban YE, Friend DJ, Ellingson K, Xu H, Boni E, Bradley-Hewitt T, Bruhn-Johannsen JF, Stamatatos L, Strong RK, Schief WR. Computational protein design using flexible backbone remodeling and resurfacing: case studies in structure-based antigen design. J Mol Biol 2011; 405: 284-297.
40. Hu X, Wang H, Ke H, Kuhlman B. Computer-based redesign of a beta sandwich protein suggests that extensive negative design is not required for de novo beta sheet design. Structure 2008; 16: 1799-1805.
41. Dantas G, Kuhlman B, Callender D, Wong M, Baker D. A large scale test of computational protein design: folding and stability of nine completely redesigned globular proteins. J Mol Biol 2003; 332: 449-460.
42. Chennamsetty N, Voynov V, Kayser V, Helk B, Trout BL. Design of therapeutic proteins with enhanced stability. Proc Natl Acad Sci USA 2009; 106: 11937-11942.