Lessons from application of the UNRES force field to predictions of structures of CASP10 targets

The performance of the physics-based protocol, whose main component is the United Residue (UNRES) physics-based coarse-grained force field, developed in our laboratory for the prediction of protein structure from amino acid sequence, is illustrated. Candidate models are selected, based on probabilit...

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Veröffentlicht in:Proceedings of the National Academy of Sciences - PNAS 2013-09, Vol.110 (37), p.14936-14941
Hauptverfasser: He, Yi, Mozolewska, Magdalena A., Krupa, Paweł, Sieradzan, Adam K., Wirecki, Tomasz K., Liwo, Adam, Kachlishvili, Khatuna, Rackovsky, Shalom, Jagieła, Dawid, Ślusarz, Rafał, Czaplewski, Cezary R., Ołdziej, Stanisław, Scheraga, Harold A.
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Sprache:eng
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Zusammenfassung:The performance of the physics-based protocol, whose main component is the United Residue (UNRES) physics-based coarse-grained force field, developed in our laboratory for the prediction of protein structure from amino acid sequence, is illustrated. Candidate models are selected, based on probabilities of the conformational families determined by multiplexed replica-exchange simulations, from the 10th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP10). For target T0663, classified as a new fold, which consists of two [Formula] domains homologous to those of known proteins, UNRES predicted the correct symmetry of packing, in which the domains are rotated with respect to each other by 180° in the experimental structure. By contrast, models obtained by knowledge-based methods, in which each domain is modeled very accurately but not rotated, resulted in incorrect packing. Two UNRES models of this target were featured by the assessors. Correct domain packing was also predicted by UNRES for the homologous target T0644, which has a similar structure to that of T0663, except that the two domains are not rotated. Predictions for two other targets, T0668 and T0684_D2, are among the best ones by global distance test score. These results suggest that our physics-based method has substantial predictive power. In particular, it has the ability to predict domain–domain orientations, which is a significant advance in the state of the art.
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.1313316110