Evidence map›Paper›PMID 17680348›Full record

ReviewJournal of structural and functional genomics2007

Structural proteomics of the SARS coronavirus: a model response to emerging infectious diseases.

Mark Bartlam, Yuanyuan Xu, Zihe Rao

Open access · bronzeAbstract readReview
In one paragraph

Review in Journal of structural and functional genomics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.8field-weighted citation impact, top 17% of its field
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

19 citing papers in PubMed, 41 citations in OpenAlex.

  1. Article
  2. Review
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  5. Overview of SARS-CoV-2 genome-encoded proteins.Science China. Life sciences · 2022
    Review
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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

3 authors at 2 institutions in 1 country.

Mark BartlamCollege of Life Sciences, Nankai University, Tianjin, China.
Yuanyuan Xu
Zihe Rao
Nankai University · CNInstitute of Biophysics · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A number of structural genomics/proteomics initiatives are focused on bacterial or viral pathogens. In this article, we will review the progress of structural proteomics initiatives targeting the SARS coronavirus (SARS-CoV), the etiological agent of the 2003 worldwide epidemic that culminated in approximately 8,000 cases and 800 deaths. The SARS-CoV genome encodes 28 proteins in three distinct classes, many of them with unknown function and sharing low similarity to other proteins. The structures of 16 SARS-CoV proteins or functional domains have been determined to date. Remarkably, eight of these 16 proteins or functional domains have novel folds, indicating the uniqueness of the coronavirus proteins. The results of SARS-CoV structural proteomics initiatives will have several profound biological impacts, including elucidation of the structure-function relationships of coronavirus proteins; identification of targets for the design of anti-viral compounds against SARS-CoV and other coronaviruses; and addition of new protein folds to the fold space, with further understanding of the structure-function relationships for several new protein families. We discuss the use of structural proteomics in response to emerging infectious diseases such as SARS-CoV and to increase preparedness against future emerging coronaviruses.

Indexed as

Models, MolecularCommunicable Diseases, EmergingHumansProteomicsSevere Acute Respiratory SyndromeSevere acute respiratory syndrome-related coronavirusViral Nonstructural ProteinsViral Nonstructural Proteins

Identifiers

PMID17680348
PMCPMC7088133
OpenAlexW2002139279

What OpenQuestion holds

Textmetadata
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.