The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Energy Functions that Discriminate X-ray and Near-native Folds from Well-constructed Decoys
Open accessAbstract
This study generates ensembles of decoy or test structures for eight small proteins with a variety of different folds. Between 35,000 and 200,000 decoys were generated for each protein using our four-state off-lattice model together with a novel relaxation method. These give compact self-avoiding conformations each constrained to have native secondary structure. Ensembles of these decoy conformations were used to test the ability of several types of empirical contact, surface area and distance-dependent energy functions to distinguish between correct and incorrect conformations. These tests have shown that none of the functions is able to distinguish consistently either the X-ray conformation or the near-native conformations from others which are incorrect. Certain combinations of two of these energy functions were able, however, consistently to identify X-ray structures from amongst the decoy conformations. These same combinations are better also at identifying near-native conformations, consistently finding them with a hundred-fold higher frequency than chance. The fact that these combination energy functions perform better than generally accepted energy functions suggests their future use in folding simulations and perhaps threading predictions.
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Cites
Needleman, S. B., & Wunsch, C. D. (1970) · Journal of Molecular Biology · doi:10.1016/0022-2836(70)90057-4 · Cited by 11,288
Principles that Govern the Folding of Protein Chains
Anfinsen, C. B. (1973) · Science · doi:10.1126/science.181.4096.223 · Cited by 7,096
A new approach to protein fold recognition
Jones, D. T., Taylort, W. R., & Thornton, J. M. (1992) · Nature · doi:10.1038/358086a0 · Cited by 1,221
Topology fingerprint approach to the inverse protein folding problem
Godzik, A., Kolinski, A., & Skolnick, J. (1992) · Journal of Molecular Biology · doi:10.1016/0022-2836(92)90693-e · Cited by 339
A lattice model for protein structure prediction at low resolution.
Hinds, D. A., & Levitt, M. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.7.2536 · Cited by 217
Self-citation
Cited by
Zhou, H., & Zhou, Y. (2002) · Protein Science · doi:10.1110/ps.0217002 · Cited by 902
Progress in Modeling of Protein Structures and Interactions.
Schueler-Furman, O., Wang, C., Bradley, P., Misura, K., & Baker, D. (2005) · Science · doi:10.1126/science.1112160 · Cited by 294
An improved protein decoy set for testing energy functions for protein structure prediction
Tsai, J., Bonneau, R., Morozov, A. V., Kuhlman, B., Rohl, C. A., & Baker, D. (2003) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10454 · Cited by 158
Contact Potential for Structure Prediction of Proteins and Protein Complexes from Potts Model
Anishchenko, I., Kundrotas, P. J., & Vakser, I. A. (2018) · Biophysical Journal · doi:10.1016/j.bpj.2018.07.035 · Cited by 29
Metadata
- Authors
- Park, B., & Levitt, M.
- Venue
- Journal of Molecular Biology
- Publisher
- Elsevier BV
- Published
- 1996-05
- Volume
- 258
- Issue
- 2
- Pages
- 367-392
- ISSN
- 0022-2836 (ISSN-L)
- OpenAlex
- W2040823078
- Cited by
- 410
- References
- 5
- FWCI
- 7.42
- Type
- journal article
- Language
- en
- Open access
- hybrid
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