High-accuracy refinement using Rosetta in CASP13
By Hahnbeom Park, Gyu Rie Lee, David E. Kim, Ivan Anishchanka, Qian Cong, David Baker. 2019
34 citations recorded by the source corpus.
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 the 13th Critial Assessment of techniques for protein Structure Prediction (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 as 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 root‐mean‐square deviation (RMSD) was achieved. An important current challenge is to improve performance in refining oligomers and larger proteins, for which the search problem remains extremely difficult.
Subfields: Materials Chemistry, Molecular Biology, Spectroscopy, Evaluation & Benchmarks, Computational Biology & Bioinformatics
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Materials Chemistry
- Sergey Ovchinnikov
- David Baker
- Ivan V. Anishchenko
- Hahnbeom Park
- Yang Zhang
- Zhenling Peng
- Jianyi Yang
- Robin Pearce
In Molecular Biology
- Sergey Ovchinnikov
- David Baker
- Yang Zhang
- Ivan V. Anishchenko
- Hahnbeom Park
- Zhenling Peng
- Robin Pearce
- Jianyi Yang
In Spectroscopy
- Sergey Ovchinnikov
- Hahnbeom Park
- David Baker
- Zhenling Peng
- Ivan V. Anishchenko
- Jianyi Yang
- Arne Elofsson
- Gabriele Pozzati
In Evaluation & Benchmarks
In Computational Biology & Bioinformatics
- Sergey Ovchinnikov
- Ivan V. Anishchenko
- David Baker
- Hahnbeom Park
- Yang Zhang
- Jianyi Yang
- Zhenling Peng
- David T. Jones
Citations in the corpus
- Improved protein structure prediction using predicted interresidue orientations (2019, positive): “We also tested the incorporation of the networkderived distance restraints into the more compute-intensive structure refinement protocol we used in CASP13 (10) on the CASP13 FM targets with an estimated starting TM-score >0.”