Evidence map›Paper›PMID 26344195›Full record

ArticleProteins2016

Protein structure prediction using residue- and fragment-environment potentials in CASP11.

Hyungrae Kim, Daisuke Kihara

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 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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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

11 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. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Ensemble-based evaluation for protein structure models.Bioinformatics (Oxford, England) · 2016
    Article
  11. 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.

Hyungrae KimDepartment of Biological Sciences, Purdue University, West Lafayette, Indiana, 47906.
Daisuke KiharaDepartment of Biological Sciences, Purdue University, West Lafayette, Indiana, 47906. dkihara@purdue.edu.

Funding

Identification of protein-metabolite interactome.R01GM097528 · NIGMS · PURDUE UNIVERSITY · PI KIHARA, DAISUKE · 2011 to 2014
$1.1M
NIGMS NIH HHS R01 GM097528
6 · The paper itself

Abstract

An accurate scoring function that can select near-native structure models from a pool of alternative models is key for successful protein structure prediction. For the critical assessment of techniques for protein structure prediction (CASP) 11, we have built a protocol of protein structure prediction that has novel coarse-grained scoring functions for selecting decoys as the heart of its pipeline. The score named PRESCO (Protein Residue Environment SCOre) developed recently by our group evaluates the native-likeness of local structural environment of residues in a structure decoy considering positions and the depth of side-chains of spatially neighboring residues. We also introduced a helix interaction potential as an additional scoring function for selecting decoys. The best models selected by PRESCO and the helix interaction potential underwent structure refinement, which includes side-chain modeling and relaxation with a short molecular dynamics simulation. Our protocol was successful, achieving the top rank in the free modeling category with a significant margin of the accumulated Z-score to the subsequent groups when the top 1 models were considered. Proteins 2016; 84(Suppl 1):105-117. © 2015 Wiley Periodicals, Inc.

Indexed as

Models, StatisticalMolecular Dynamics SimulationSoftwareAdenoviridaeAlgorithmsComputational BiologyDatabases, ProteinHumansInternetProtein FoldingProtein Interaction Domains and MotifsProteinsProtein Structure, SecondaryResearch DesignProteinsCASP11decoy selectionhelix interactionknowledge-based potentialprotein structure predictionresidue environmentsscoring functions

Identifiers

PMID26344195
PMCPMC4781684

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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.