Evidence map›Paper›PMID 21560165›Full record

ArticleProteins2011

Multibody coarse-grained potentials for native structure recognition and quality assessment of protein models.

Pawel Gniewek, Sumudu P Leelananda, Andrzej Kolinski, Robert L Jernigan, Andrzej Kloczkowski

Erratum issuedAbstract read
In one paragraph

Article in Proteins, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Protein Docking Model Evaluation by Graph Neural Networks.Frontiers in molecular biosciences · 2021
    Article
  3. Article
  4. Article
  5. Knowledge-based entropies improve the identification of native protein structures.Proceedings of the National Academy of Sciences of the United States of America · 2017
    Article
  6. Molecular determinants of cadherin ideal bond formation: Conformation-dependent unbinding on a multidimensional landscape.Proceedings of the National Academy of Sciences of the United States of America · 2016
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

5 authors.

Pawel GniewekFaculty of Chemistry, University of Warsaw, Warsaw, Poland.
Sumudu P Leelananda
Andrzej Kolinski
Robert L Jernigan
Andrzej Kloczkowski

Funding

Coarse-Grained Models of ProteinsR01GM072014 · NIGMS · IOWA STATE UNIVERSITY · PI JERNIGAN, ROBERT L · 2004 to 2012
$2.3M
Modeling Ribosomal Control, Function and AssemblyR01GM073095 · NIGMS · IOWA STATE UNIVERSITY · PI JERNIGAN, ROBERT L · 2006 to 2009
$1.0M
High-Accuracy Protein Models Derived from Lower Resolution DataR01GM081680 · NIGMS · IOWA STATE UNIVERSITY · PI KLOCZKOWSKI, ANDRZEJ · 2007 to 2009
$763k
NIGMS NIH HHS R01 GM072014NIGMS NIH HHS R01GM072014NIGMS NIH HHS R01 GM073095NIGMS NIH HHS R01 GM081680NIGMS NIH HHS R01GM081680NIGMS NIH HHS R01GM081680-S1
6 · The paper itself

Abstract

Multibody potentials have been of much interest recently because they take into account three dimensional interactions related to residue packing and capture the cooperativity of these interactions in protein structures. Our goal was to combine long range multibody potentials and short range potentials to improve recognition of native structure among misfolded decoys. We optimized the weights for four-body nonsequential, four-body sequential, and short range potentials to obtain optimal model ranking results for threading and have compared these data against results obtained with other potentials (26 different coarse-grained potentials from the Potentials 'R'Us web server have been used). Our optimized multibody potentials outperform all other contact potentials in the recognition of the native structure among decoys, both for models from homology template-based modeling and from template-free modeling in CASP8 decoy sets. We have compared the results obtained for this optimized coarse-grained potentials, where each residue is represented by a single point, with results obtained by using the DFIRE potential, which takes into account atomic level information of proteins. We found that for all proteins larger than 80 amino acids our optimized coarse-grained potentials yield results comparable to those obtained with the atomic DFIRE potential.

Indexed as

Amino AcidsComputational BiologyModels, MolecularProtein ConformationProteinsAmino AcidsProteins

Identifiers

PMID21560165
PMCPMC3093657

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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.