Evidence map›Paper›PMID 27671894›Full record

ArticleProteins2016

Development of a motif-based topology-independent structure comparison method to identify evolutionarily related folds.

Joseph M Dybas, Andras Fiser

Abstract readComparative Study
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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Joseph M DybasDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, New York, 10461.
Andras FiserDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, New York, 10461.

Funding

Molecular basis of receptor-ligand recognition in the Immunological SynapseR01GM118709 · NIGMS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI FISER, ANDRAS · 2016 to 2019
$2.3M
Membrane protein structure modeling with experimental restraintsR01GM096041 · NIGMS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI FISER, ANDRAS · 2011 to 2014
$1.3M
NIGMS NIH HHS R01 GM096041NIGMS NIH HHS R01 GM118709
6 · The paper itself

Abstract

Structure conservation, functional similarities, and homologous relationships that exist across diverse protein topologies suggest that some regions of the protein fold universe are continuous. However, the current structure classification systems are based on hierarchical organizations, which cannot accommodate structural relationships that span fold definitions. Here, we describe a novel, super-secondary-structure motif-based, topology-independent structure comparison method (SmotifCOMP) that is able to quantitatively identify structural relationships between disparate topologies. The basis of SmotifCOMP is a systematically defined super-secondary-structure motif library whose representative geometries are shown to be saturated in the Protein Data Bank and exhibit a unique distribution within the known folds. SmotifCOMP offers a robust and quantitative technique to compare domains that adopt different topologies since the method does not rely on a global superposition. SmotifCOMP is used to perform an exhaustive comparison of the known folds and the identified relationships are used to produce a nonhierarchical representation of the fold space that reflects the notion of a continuous and connected fold universe. The current work offers insight into previously hypothesized evolutionary relationships between disparate folds and provides a resource for exploring novel ones. Proteins 2016; 84:1859-1874. © 2016 Wiley Periodicals, Inc.

Indexed as

AlgorithmsEvolution, MolecularProtein FoldingAmino Acid MotifsDatabases, ProteinModels, MolecularProtein DomainsProteinsProtein Structure, SecondaryStructural Homology, ProteinProteinsfold evolutionSmotifstructure classificationstructure comparisonsuper-secondary structure motif

Identifiers

PMID27671894
PMCPMC5118133

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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.