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. 1996 Feb;5(2):254–261. doi: 10.1002/pro.5560050209

Folding proteins with a simple energy function and extensive conformational searching.

K Yue 1, K A Dill 1
PMCID: PMC2143350  PMID: 8745403

Abstract

We describe a computer algorithm for predicting the three-dimensional structures of proteins using only their amino acid sequences. The method differs from others in two ways: (1) it uses very few energy parameters, representing hydrophobic and polar interactions, and (2) it uses a new "constraint-based exhaustive" searching method, which appears to be among the fastest and most complete search methods yet available for realistic protein models. It finds a relatively small number of low-energy conformations, among which are native-like conformations, for crambin (1CRN), avian pancreatic polypeptide (1PPT), melittin (2MLT), and apamin. Thus, the lowest-energy states of very simple energy functions may predict the native structures of globular proteins.

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Selected References

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  1. Covell D. G. Folding protein alpha-carbon chains into compact forms by Monte Carlo methods. Proteins. 1992 Nov;14(3):409–420. doi: 10.1002/prot.340140310. [DOI] [PubMed] [Google Scholar]
  2. Dill K. A., Bromberg S., Yue K., Fiebig K. M., Yee D. P., Thomas P. D., Chan H. S. Principles of protein folding--a perspective from simple exact models. Protein Sci. 1995 Apr;4(4):561–602. doi: 10.1002/pro.5560040401. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Dill K. A. Dominant forces in protein folding. Biochemistry. 1990 Aug 7;29(31):7133–7155. doi: 10.1021/bi00483a001. [DOI] [PubMed] [Google Scholar]
  4. Hinds D. A., Levitt M. Exploring conformational space with a simple lattice model for protein structure. J Mol Biol. 1994 Nov 4;243(4):668–682. doi: 10.1016/0022-2836(94)90040-x. [DOI] [PubMed] [Google Scholar]
  5. Kolinski A., Skolnick J. Monte Carlo simulations of protein folding. I. Lattice model and interaction scheme. Proteins. 1994 Apr;18(4):338–352. doi: 10.1002/prot.340180405. [DOI] [PubMed] [Google Scholar]
  6. Kuntz I. D., Crippen G. M., Kollman P. A., Kimelman D. Calculation of protein tertiary structure. J Mol Biol. 1976 Oct 5;106(4):983–994. doi: 10.1016/0022-2836(76)90347-8. [DOI] [PubMed] [Google Scholar]
  7. Lee B., Richards F. M. The interpretation of protein structures: estimation of static accessibility. J Mol Biol. 1971 Feb 14;55(3):379–400. doi: 10.1016/0022-2836(71)90324-x. [DOI] [PubMed] [Google Scholar]
  8. Levitt M., Warshel A. Computer simulation of protein folding. Nature. 1975 Feb 27;253(5494):694–698. doi: 10.1038/253694a0. [DOI] [PubMed] [Google Scholar]
  9. McDonald I. K., Thornton J. M. Satisfying hydrogen bonding potential in proteins. J Mol Biol. 1994 May 20;238(5):777–793. doi: 10.1006/jmbi.1994.1334. [DOI] [PubMed] [Google Scholar]
  10. Monge A., Friesner R. A., Honig B. An algorithm to generate low-resolution protein tertiary structures from knowledge of secondary structure. Proc Natl Acad Sci U S A. 1994 May 24;91(11):5027–5029. doi: 10.1073/pnas.91.11.5027. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Novotný J., Rashin A. A., Bruccoleri R. E. Criteria that discriminate between native proteins and incorrectly folded models. Proteins. 1988;4(1):19–30. doi: 10.1002/prot.340040105. [DOI] [PubMed] [Google Scholar]
  12. Sharp K. A., Nicholls A., Fine R. F., Honig B. Reconciling the magnitude of the microscopic and macroscopic hydrophobic effects. Science. 1991 Apr 5;252(5002):106–109. doi: 10.1126/science.2011744. [DOI] [PubMed] [Google Scholar]
  13. Sippl M. J., Hendlich M., Lackner P. Assembly of polypeptide and protein backbone conformations from low energy ensembles of short fragments: development of strategies and construction of models for myoglobin, lysozyme, and thymosin beta 4. Protein Sci. 1992 May;1(5):625–640. doi: 10.1002/pro.5560010509. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Skolnick J., Kolinski A. Simulations of the folding of a globular protein. Science. 1990 Nov 23;250(4984):1121–1125. doi: 10.1126/science.250.4984.1121. [DOI] [PubMed] [Google Scholar]
  15. Srinivasan R., Rose G. D. LINUS: a hierarchic procedure to predict the fold of a protein. Proteins. 1995 Jun;22(2):81–99. doi: 10.1002/prot.340220202. [DOI] [PubMed] [Google Scholar]
  16. Wallqvist A., Ullner M. A simplified amino acid potential for use in structure predictions of proteins. Proteins. 1994 Mar;18(3):267–280. doi: 10.1002/prot.340180308. [DOI] [PubMed] [Google Scholar]
  17. Wilson C., Doniach S. A computer model to dynamically simulate protein folding: studies with crambin. Proteins. 1989;6(2):193–209. doi: 10.1002/prot.340060208. [DOI] [PubMed] [Google Scholar]
  18. Yue K., Dill K. A. Forces of tertiary structural organization in globular proteins. Proc Natl Acad Sci U S A. 1995 Jan 3;92(1):146–150. doi: 10.1073/pnas.92.1.146. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Yue K., Fiebig K. M., Thomas P. D., Chan H. S., Shakhnovich E. I., Dill K. A. A test of lattice protein folding algorithms. Proc Natl Acad Sci U S A. 1995 Jan 3;92(1):325–329. doi: 10.1073/pnas.92.1.325. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Yue K, Dill KA. Sequence-structure relationships in proteins and copolymers. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics. 1993 Sep;48(3):2267–2278. doi: 10.1103/physreve.48.2267. [DOI] [PubMed] [Google Scholar]

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