Perspectives in protein-fold recognition

Current Opinion in Structural Biology

Volumn 7, Issue 2, 1997, Pages 200-205

  Torda, Andrew E ^a  

^a AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID SEQUENCE; ENERGY; METHODOLOGY; PRIORITY JOURNAL; PROTEIN FOLDING; PROTEIN STRUCTURE; REVIEW; STATISTICAL ANALYSIS;

EID: 0030967586     PISSN: 0959440X     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0959-440X(97)80026-7     Document Type: Article

References (46)

1. Jones DT, Thornton JM: Potential energy functions for threading. Curr Opin Struct Biol 1996, 6:210-216.
2. Sippl MJ, Flöckner H: Threading thrills and threats. Structure 1996, 4:15-19.
3. Böhm G: New approaches in molecular structure prediction. Biophys Chem 1996, 59:1-32.
4. Jernigan RL, Bahar I: Structure-derived potentials and protein simulations. Curr Opin Struct Biol 1996, 6:195-209.
5. Sippl MJ: Knowledge-based potentials for proteins. Curr Opin Struct Biol 1995, 5:229-235.
6. Jones DT, Taylor WR, Thornton JM: A new approach to protein fold recognition. Nature 1992, 358:86-89.
7. Pedersen JT, Moult J: Ab initio structure prediction for small polypeptides and protein fragments using genetic algorithms. Proteins 1995, 23:454-460.
8. Unger R, Moult J: Genetic algorithms for protein folding simulations. J Mol Biol 1993, 231:75-81.
9. Srinivasan R, Rose GD: LINUS: a hierarchic procedure to predict the fold of a protein. Proteins 1995, 22:81-99.
10. Gunn JR: Minimizing reduced-model proteins using a generalized hierarchical table-lookup potential function. J Phys Chem 1996, 100:3264-3272.
11. Pachter R, Fairchild SB, Lupo JA, Adams WW: Biomolecular structure prediction at a low resolution using a neural network and the double-iterated Kalman filter technique. Biopolymers 1996, 39:377-386.
12. Reese MG, Lund O, Bohr J, Bohr H, Hansen JE, Brunak S: Distance distributions in proteins: a six-parameter representation. Protein Eng 1996, 9:733-740.
13. Tanaka S, Scheraga HA: Medium- and long-range interaction parameters between amino acids for predicting three-dimensional structures of proteins. Macromolecules 1976, 9:945-950.
14. Sippl MJ: Calculation of conformational ensembles from potentials of mean force. J Mol Biol 1990, 213:859-883.
15. Kocher J-PA, Rooman MJ, Wodak S: Factors influencing the ability of knowledge-based potentials to identify native sequence-structure matches. J Mol Biol 1994, 235:1598-1613.
16. Nishikawa K, Matsuo Y: Development of pseudoenergy potentials for assessing protein 3D-1D compatibility and detecting weak homologies. Protein Eng 1993, 6:811-820.
17. Matsuo Y, Nishikawa K: Protein structural similarities predicted by a sequence-structure compatibility method. Protein Sci 1994, 3:2055-2063.
18. Sippl MJ: Boltzmann's principle, knowledge-based mean fields and protein folding. An approach to the computational determination of protein structures. J Comput Aided Mol Des 1993, 7:473-501.
19. Miyazawa S, Jernigan RL: Residue-residue potentials with a favorable contact pair term and an unfavorable high packing density term, for simulation and threading. J Mol Biol 1996, 256:623-644.
20. Matsuo Y, Nakamura H, Nishikawa K: Detection of protein 3D-1D compatibility characterized by the evaluation of side-chain packing and electrostatic interactions. J Biochem 1995, 118:137-148.
21. Park B, Levitt M: Energy functions that discriminate X-ray and near-native folds from well-constructed decoys. J Mol Biol 1996, 258:367-392. In this paper, rather than just generate force fields suitable for threading, the authors offer a series of terms that, when summed, allow fold recognition from a very large number of native-like structures.
22. Thomas PD, Dill KA: Statistical potentials extracted from protein structures: how accurate are they? J Mol Biol 1996, 257:457-469. This paper uses a simple lattice model to highlight weaknesses in the calculation of potentials of mean force from native structures. The authors suggest that fold recognition would be almost as powerful using a much simpler hydrophobic/polar model for interactions.
23. Huang ES, Subbiah S, Tsai J, Levitt M: Using a hydrophobic contact potential to evaluate native and near-native folds generated by molecular dynamics simulations. J Mol Biol 1996, 257:716-725.
24. Crippen GM, Snow ME: A 1.8 Å resolution potential function for protein folding. Biopolymers 1990, 29:1479-1489.
25. Ulrich P, Scott W, Van Gunsteren WF, Torda AE: Protein structure prediction force fields: parametrisation with quasi-Newtonian dynamics. Proteins 1997, in press.
26. Koretke KK, Luthey-Schulten Z, Wolynes PG: Self-consistently optimized statistical mechanical energy functions for sequence structure alignment. Protein Sci 1996, 5:1043-1059. First, the authors parametrize a force field by optimizing its ability to distinguish native from nonnative folds for a sequence. Second, the authors give a method to optimize gap penalties along with the rest of the force field.
27. ••], the authors present a force field generation method that optimizes fold-recognition capability. They show that even though a force field performs well at finding a native structure amongst alternatives generated by threading, it does not perform well with misfolded structures generated by other means. The authors then improve their own force field to handle these other decoy structures.
28. Crippen GM: Easily searched protein folding potentials. J Mol Biol 1996, 260:467-475. This paper gives a method for extracting the correct potentials of mean force from observations of native structures. The authors then show how to improve the suitability of the force field for searching algorithms by imposing some correlation between pseudoenergy and distance from the correct answer.
29. Finkelstein AV, Reva BA: Search for the most stable folds of protein chains. I. Application of a self-consistent molecular field theory to a problem of protein three-dimensional structure prediction. Protein Eng 1996, 9:387-397.
30. Reva BA, Finkelstein AV: Search for the most stable folds of protein chains: II. Computation of stable architectures of β-proteins using a self-consistent molecular field theory. Protein Eng 1996, 9:399-411.
31. Defay TR, Cohen FE: Multiple sequence information for threading algorithms. J Mol Biol 1996, 262:314-323.
32. Lemer CM-R, Rooman MJ, Wodak SJ: Protein structure prediction by threading methods: evaluation of current techniques. Proteins 1995, 23:337-355.
33. Lathrop RH: The protein threading problem with sequence amino acid interaction preferences is NP-complete. Protein Eng 1994, 7:1059-1068.
34. Ouzonis C, Sander C, Scharf M, Schneider R: Prediction of protein structure by evaluation of sequence-structure fitness. J Mol Biol 1993, 232:805-825.
35. Madej T, Gilbrat J-F, Bryant SH: Threading a database of protein cores. Proteins 1995, 23:356-369.
36. Westhead DR, Collura VP, Eldridge MD, Firth MA, Li J, Murray CW: Protein fold recognition by threading: comparison of algorithms and analysis of results. Protein Eng 1995, 8:1197-1204.
37. Lathrop RH, Smith TF: Global optimum protein threading with gapped alignment and empirical pair score functions. J Mol Biol 1996, 255:641-665. The authors give the first practical method for handling sequence-structure alignments using residue-specific scoring functions and without using approximations.
38. Crippen GM, Maiorov VN: How many protein folding motifs are there? J Mol Biol 1995, 252:144-151.
39. Hamprecht FA, Scott W, Van Gunsteren WF: Generation of pseudo-native protein structures for threading. Proteins 1997, in press.
40. Madej T, Boguski MS, Bryant SH: Threading analysis suggests that the obese gene product may be a helical cytokine. FEBS Lett 1995, 373:13-18.
41. Miller RT, Jones DT, Thornton JM: Protein fold recognition by sequence threading: tools and assessment techniques. FASEB J 1996, 10:171-178.
42. Jones DT: Two applications of statistical potentials: protein fold recognition and de novo protein design. Abstract for Molecular Interactions, 15th International Meeting of Molecular Graphics Society, 1996 April 16-19, York.
43. Bryant SH, Lawrence CE: An empirical energy function for threading protein sequence through the folding motif. Proteins 1993, 16:92-112.
44. Jones DT, Miller RT, Thornton JM: Successful protein fold recognition by optimal sequence threading validated by rigorous blind testing. Proteins 1995, 23:387-397.
45. Sippl MJ: Helmholtz free energy of peptide hydrogen bonds in proteins. J Mol Biol 1996, 260:644-648. See annotation [46••].
46. ••] are of outstanding interest because of the controversy they arouse and the boldness of the authors' assertion that protein data bank structures constitute an ensemble that allows free-energy estimations.