Evidence map›Paper›PMID 25581562›Full record

ArticleProteins2015

CASP10-BCL::Fold efficiently samples topologies of large proteins.

Sten Heinze, Daniel K Putnam, Axel W Fischer, Tim Kohlmann, Brian E Weiner, Jens Meiler

Abstract read
In one paragraph

Article in Proteins, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

6 authors.

Sten HeinzeDepartment of Chemistry, Vanderbilt University, Nashville, Tennessee, 37240.
Daniel K Putnam
Axel W Fischer
Tim Kohlmann
Brian E Weiner
Jens Meiler

Funding

Membrane Protein Structure Elucidation from sparse NMR data (KAMP)R01GM080403 · NIGMS · VANDERBILT UNIVERSITY · PI MEILER, JENS · 2007 to 2019
$3.0M
NIGMS NIH HHS R01 GM080403
6 · The paper itself

Abstract

During CASP10 in summer 2012, we tested BCL::Fold for prediction of free modeling (FM) and template-based modeling (TBM) targets. BCL::Fold assembles the tertiary structure of a protein from predicted secondary structure elements (SSEs) omitting more flexible loop regions early on. This approach enables the sampling of conformational space for larger proteins with more complex topologies. In preparation of CASP11, we analyzed the quality of CASP10 models throughout the prediction pipeline to understand BCL::Fold's ability to sample the native topology, identify native-like models by scoring and/or clustering approaches, and our ability to add loop regions and side chains to initial SSE-only models. The standout observation is that BCL::Fold sampled topologies with a GDT_TS score > 33% for 12 of 18 and with a topology score > 0.8 for 11 of 18 test cases de novo. Despite the sampling success of BCL::Fold, significant challenges still exist in clustering and loop generation stages of the pipeline. The clustering approach employed for model selection often failed to identify the most native-like assembly of SSEs for further refinement and submission. It was also observed that for some β-strand proteins model refinement failed as β-strands were not properly aligned to form hydrogen bonds removing otherwise accurate models from the pool. Further, BCL::Fold samples frequently non-natural topologies that require loop regions to pass through the center of the protein.

Indexed as

Protein FoldingAlgorithmsComputational BiologyComputer SimulationModels, MolecularProtein ConformationProteinsSequence Analysis, ProteinProteinsde novo protein structure predictiondouble blind benchmarkknowledge based scoring functionsloop predictionsheet alignment

Identifiers

PMID25581562
PMCPMC5563077

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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.