High-accuracy refinement using Rosetta in CASP13.
Park H , Lee GR , Kim DE , Anishchanka I , Cong Q , Baker D
Because proteins generally fold to their lowest free energy states, energy-guided refinement in principle should be able to systematically improve the quality of protein structure models generated using homologous structure or co-evolution derived information. However, because of the high dimensionality of the search space, there are far more ways to degrade the quality of a near native model than to improve it, and hence refinement methods are very sensitive to energy function errors. In CASP13, we sought to carry out a thorough search for low energy states in the neighborhood of a starting model using restraints to avoid straying too far. The approach was reasonably successful in improving both regions largely incorrect in the starting models as well core regions that started out closer to the correct structure. Models with GDT-HA over 70 were obtained for five targets and for one of those, an accuracy of 0.5 å backbone RMSD was achieved. An important current challenge is to improve performance in refining oligomers and/or larger proteins, for which the search problem remains extremely difficult. This article is protected by copyright. All rights reserved.
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