Evidence map›Paper›PMID 19731372›Full record

ArticleProteins2009

The other 90% of the protein: assessment beyond the Calphas for CASP8 template-based and high-accuracy models.

Daniel A Keedy, Christopher J Williams, Jeffrey J Headd, W Bryan Arendall, Vincent B Chen, Gary J Kapral, Robert A Gillespie, Jeremy N Block, Adam Zemla, David C Richardson and 1 more

Abstract read
In one paragraph

Article in Proteins, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing 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

52 citing papers in PubMed.

  1. Review
  2. Article
  3. The transformative power of transformers in protein structure prediction.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  4. Article
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  8. DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on CoV-related complexes.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  9. Article
  10. Article
  11. Article
  12. Article
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  15. MolProbity: More and better reference data for improved all-atom structure validation.Protein science : a publication of the Protein Society · 2018
    Article
  16. Article
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  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

11 authors.

Daniel A KeedyDepartment of Biochemistry, Duke University Medical Center, Durham, North Carolina 27710, USA.
Christopher J Williams
Jeffrey J Headd
W Bryan Arendall
Vincent B Chen
Gary J Kapral
Robert A Gillespie
Jeremy N Block
Adam Zemla
David C Richardson
Jane S Richardson

Funding

MolProbity Validation & Corrections: for Crystallography, PDB & BiomedicineR01GM073919 · NIGMS · DUKE UNIVERSITY · PI RICHARDSON, DAVID CLAUDE · 2006 to 2018
$3.7M
New Kind of Quality Management for X-ray &NMR ModelsR01GM073930 · NIGMS · DUKE UNIVERSITY · PI RICHARDSON, DAVID CLAUDE · 2005 to 2013
$2.3M
NIGMS NIH HHS GM073919NIGMS NIH HHS GM073930NIGMS NIH HHS R01 GM073919NIGMS NIH HHS R01 GM073930
6 · The paper itself

Abstract

For template-based modeling in the CASP8 Critical Assessment of Techniques for Protein Structure Prediction, this work develops and applies six new full-model metrics. They are designed to complement and add value to the traditional template-based assessment by the global distance test (GDT) and related scores (based on multiple superpositions of Calpha atoms between target structure and predictions labeled "Model 1"). The new metrics evaluate each predictor group on each target, using all atoms of their best model with above-average GDT. Two metrics evaluate how "protein-like" the predicted model is: the MolProbity score used for validating experimental structures, and a mainchain reality score using all-atom steric clashes, bond length and angle outliers, and backbone dihedrals. Four other new metrics evaluate match of model to target for mainchain and sidechain hydrogen bonds, sidechain end positioning, and sidechain rotamers. Group-average Z-score across the six full-model measures is averaged with group-average GDT Z-score to produce the overall ranking for full-model, high-accuracy performance. Separate assessments are reported for specific aspects of predictor-group performance, such as robustness of approximately correct template or fold identification, and self-scoring ability at identifying the best of their models. Fold identification is distinct from but correlated with group-average GDT Z-score if target difficulty is taken into account, whereas self-scoring is done best by servers and is uncorrelated with GDT performance. Outstanding individual models on specific targets are identified and discussed. Predictor groups excelled at different aspects, highlighting the diversity of current methodologies. However, good full-model scores correlate robustly with high Calpha accuracy.

Indexed as

Computational BiologyHydrogen BondingModels, MolecularProtein ConformationProtein FoldingProteinsSequence Analysis, ProteinSoftwareProteins

Identifiers

PMID19731372
PMCPMC2877634

What OpenQuestion holds

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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.