Evidence map›Paper›PMID 19398323›Full record

ReviewCurrent opinion in structural biology2009

Exploiting structural classifications for function prediction: towards a domain grammar for protein function.

Benoît H Dessailly, Oliver C Redfern, Alison Cuff, Christine A Orengo

Abstract readReview
In one paragraph

Review in Current opinion in structural biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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. Clustering protein functional families at large scale with hierarchical approaches.Protein science : a publication of the Protein Society · 2024
    Article
  2. Quantitative In Silico Evaluation of Allergenic Proteins fromCurrent issues in molecular biology · 2022
    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

4 authors.

Benoît H DessaillyDepartment of Structural and Molecular Biology, University College London, London WC1E 6BT, United Kingdom.
Oliver C Redfern
Alison Cuff
Christine A Orengo

Funding

The Midwest Center for Structural GenomicsU54GM074942 · NIGMS · UNIVERSITY OF CHICAGO · PI JOACHIMIAK, ANDRZEJ · 2005 to 2009
$51.0M
Biotechnology and Biological Sciences Research Council BB/F010451/1NIGMS NIH HHS U54 GM074942
6 · The paper itself

Abstract

The ability to assign function to proteins has become a major bottleneck for comprehensively understanding cellular mechanisms at the molecular level. Here we discuss the extent to which structural domain classifications can help in deciphering the complex relationship between the functions of proteins and their sequences and structures. Structural classifications are particularly helpful in understanding the mosaic manner in which new proteins and functions emerge through evolution. This is partly because they provide reliable and concrete domain definitions and enable the detection of very remote structural similarities and homologies. It is also because structural data can illuminate more clearly the mechanisms by which a broader functional repertoire can emerge during evolution.

Indexed as

AnimalsHumansModels, MolecularProtein FoldingProteinsProtein Structure, TertiaryProteins

Identifiers

PMID19398323
PMCPMC2920418

What OpenQuestion holds

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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.