ArticleProteins2019
Evaluation of model refinement in CASP13.
Article in Proteins, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
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- In silico design of a polypeptide as a vaccine candidate against ascariasis.Scientific reports · 2023Article
- Structure-conditioned amino-acid couplings: How contact geometry affects pairwise sequence preferences.Protein science : a publication of the Protein Society · 2022Article
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- Article
- Modeling SARS-CoV-2 proteins in the CASP-commons experiment.Proteins · 2021Article
- Article
- DeepRefiner: high-accuracy protein structure refinement by deep network calibration.Nucleic acids research · 2021Article
- Fast and effective protein model refinement using deep graph neural networks.Nature computational science · 2021Article
- Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models?PLoS computational biology · 2021Article
- Protein Structure Refinement Using Multi-Objective Particle Swarm Optimization with Decomposition Strategy.International journal of molecular sciences · 2021Article
- Improved Sampling Strategies for Protein Model Refinement Based on Molecular Dynamics Simulation.Journal of chemical theory and computation · 2021Article
- Improved protein structure refinement guided by deep learning based accuracy estimation.Nature communications · 2021Article
- Phasertng: directed acyclic graphs for crystallographic phasing.Acta crystallographica. Section D, Structural biology · 2021Article
- Protein storytelling through physics.Science (New York, N.Y.) · 2020Review
- Article
- High-accuracy protein structures by combining machine-learning with physics-based refinement.Proteins · 2020Article
- Improved protein structure prediction using predicted interresidue orientations.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Article
- Evaluation of model refinement in CASP13.Proteins · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Performance in the model refinement category of the 13th round of Critical Assessment of Structure Prediction (CASP13) is assessed, showing that some groups consistently improve most starting models whereas the majority of participants continue to degrade the starting model on average. Using the ranking formula developed for CASP12, it is shown that only 7 of 32 groups perform better than a "naïve predictor" who just submits the starting model. Common features in their approaches include a dependence on physics-based force fields to judge alternative conformations and the use of molecular dynamics to relax models to local minima, usually with some restraints to prevent excessively large movements. In addition to the traditional CASP metrics that focus largely on the quality of the overall fold, alternative metrics are evaluated, including comparisons of the main-chain and side-chain torsion angles, and the utility of the models for solving crystal structures by the molecular replacement method. It is proposed that the introduction of these metrics, as well as consideration of the accuracy of coordinate error estimates, would improve the discrimination between good and very good models.
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