Evidence map›Paper›PMID 20163737›Full record

ArticleBMC bioinformatics2010

Potentials 'R' Us web-server for protein energy estimations with coarse-grained knowledge-based potentials.

Yaping Feng, Andrzej Kloczkowski, Robert L Jernigan

Abstract read
In one paragraph

Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Computational Ways to Enhance Protein Inhibitor Design.Frontiers in molecular biosciences · 2020
    Article
  5. Article
  6. 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
  7. 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
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. 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

3 authors.

Yaping FengDepartment of Biochemistry, Biophysics, and Molecular Biology, Iowa State University, Ames, IA 50011-0320, USA.
Andrzej Kloczkowski
Robert L Jernigan

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 1R01GM072014-5NIGMS NIH HHS 1R01GM073095-3NIGMS NIH HHS 1R01GM081680-2NIGMS NIH HHS R01 GM072014
6 · The paper itself

Abstract

backgroundKnowledge-based potentials have been widely used in the last 20 years for fold recognition, protein structure prediction from amino acid sequence, ligand binding, protein design, and many other purposes. However generally these are not readily accessible online.

resultsOur new knowledge-based potential server makes available many of these potentials for easy use to automatically compute the energies of protein structures or models supplied. Our web server for protein energy estimation uses four-body potentials, short-range potentials, and 23 different two-body potentials. Users can select potentials according to their needs and preferences. Files containing the coordinates of protein atoms in the PDB format can be uploaded as input. The results will be returned to the user's email address.

conclusionsOur Potentials 'R' Us server is an easily accessible, freely available tool with a web interface that collects all existing and future protein coarse-grained potentials and computes energies of multiple structural models.

Indexed as

Artificial IntelligenceInternetModels, ChemicalModels, MolecularAmino Acid SequenceComputer SimulationEnergy TransferMolecular Sequence DataProgramming LanguagesProtein ConformationProteinsSequence Analysis, ProteinSoftwareProteins

Identifiers

PMID20163737
PMCPMC3098114

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.