Evidence map›Paper›PMID 27081793›Full record

ArticleProteins2016

Assessment of refinement of template-based models in CASP11.

Vivek Modi, Roland L Dunbrack

Abstract read
In one paragraph

Article in Proteins, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

  1. Article
  2. Article
  3. Building Structural Models of a Whole Mycoplasma Cell.Journal of molecular biology · 2022
    Article
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  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Methods for the Refinement of Protein Structure 3D Models.International journal of molecular sciences · 2019
    Review
  12. Experimental accuracy in protein structure refinement via molecular dynamics simulations.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  13. Article
  14. Protein structure prediction.International journal of modern physics. B · 2018
    Article
  15. Modeling protein folding in vivo.Biology direct · 2018
    Article
  16. Article
  17. Protein homology model refinement by large-scale energy optimization.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Vivek ModiFox Chase Cancer Center, Philadelphia, Pennsylvania, 19111.
Roland L DunbrackFox Chase Cancer Center, Philadelphia, Pennsylvania, 19111. roland.dunbrack@fccc.edu.

Funding

WORD PROCESSING CENTER--COREP30CA006927 · NCI · RESEARCH INST OF FOX CHASE CAN CTR · PI Margaret von Mehren · 1985 to 2026
$138.8M
Bayesian Statistics and Algorithms for Homology ModelingR01GM084453 · NIGMS · RESEARCH INST OF FOX CHASE CAN CTR · PI DUNBRACK, ROLAND L · 2008 to 2016
$2.6M
Modeling of Protein Complexes and Missense MutationsR01GM073784 · NIGMS · RESEARCH INST OF FOX CHASE CAN CTR · PI DUNBRACK, ROLAND L · 2006 to 2009
$1.2M
NCI NIH HHS P30 CA006927NIGMS NIH HHS R01 GM073784NIGMS NIH HHS R01 GM084453
6 · The paper itself

Abstract

CASP11 (the 11th Meeting on the Critical Assessment of Protein Structure Prediction) ran a blind experiment in the refinement of protein structure predictions, the fourth such experiment since CASP8. As with the previous experiments, the predictors were provided with one starting structure from the server models of each of a selected set of template-based modeling targets and asked to refine the coordinates of the starting structure toward native. We assessed the refined structures with the Z-scores of the standard CASP measures, which compare the model-target similarities of the models from all the predictors. Furthermore, we assessed the refined structures with "relative measures," which compare the improvement in accuracy of each model with respect to the starting structure. The latter provides an assessment of the extent to which each predictor group is able to improve the starting structures toward native. We utilized heat maps to display improvements in the Calpha-Calpha distance matrix for each model. The heat maps labeled with each element of secondary structure helped us to identify regions of refinement toward native in each model. Most positively scoring models show modest improvements in multiple regions of the structure, while in some models we were able to identify significant repositioning of N/C-terminal segments and internal elements of secondary structure. The best groups were able to improve more than 70% of the targets from the starting models, and by an average of 3-5% in the standard CASP measures. Proteins 2016; 84(Suppl 1):260-281. © 2016 Wiley Periodicals, Inc.

Indexed as

BenchmarkingModels, MolecularModels, StatisticalSoftwareAlgorithmsAmino Acid MotifsComputational BiologyComputer SimulationDatabases, ProteinHumansInternetProtein Conformation, alpha-HelicalProtein Conformation, beta-StrandProtein FoldingProtein Interaction Domains and MotifsProteinsProteinsCASPcomparative modelingrefinement

Identifiers

PMID27081793
PMCPMC5030126

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.