Advances in Rosetta structure prediction for difficult molecular-replacement problems
- University of Washington, UW Box 357350, Seattle, WA 98195 (United States)
Modeling advances using Rosetta structure prediction to aid in solving difficult molecular-replacement problems are discussed. Recent work has shown the effectiveness of structure-prediction methods in solving difficult molecular-replacement problems. The Rosetta protein structure modeling suite can aid in the solution of difficult molecular-replacement problems using templates from 15 to 25% sequence identity; Rosetta refinement guided by noisy density has consistently led to solved structures where other methods fail. In this paper, an overview of the use of Rosetta for these difficult molecular-replacement problems is provided and new modeling developments that further improve model quality are described. Several variations to the method are introduced that significantly reduce the time needed to generate a model and the sampling required to improve the starting template. The improvements are benchmarked on a set of nine difficult cases and it is shown that this improved method obtains consistently better models in less running time. Finally, strategies for best using Rosetta to solve difficult molecular-replacement problems are presented and future directions for the role of structure-prediction methods in crystallography are discussed.
- OSTI ID:
- 22347832
- Journal Information:
- Acta Crystallographica. Section D: Biological Crystallography, Vol. 69, Issue Pt 11; Other Information: PMCID: PMC3817693; PMID: 24189231; PUBLISHER-ID: ba5213; OAI: oai:pubmedcentral.nih.gov:3817693; Copyright (c) DiMaio 2013; This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.; Country of input: International Atomic Energy Agency (IAEA); ISSN 0907-4449
- Country of Publication:
- Denmark
- Language:
- English
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