Evidence map›Paper›PMID 32244041›Full record

ArticleMicrobial pathogenesis2020

Shell disorder analysis predicts greater resilience of the SARS-CoV-2 (COVID-19) outside the body and in body fluids.

Gerard Kian-Meng Goh, A Keith Dunker, James A Foster, Vladimir N Uversky

Open access · greenAbstract read
In one paragraph

Article in Microbial pathogenesis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 7% 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

43 citing papers in PubMed, 1 synthesis or guideline pooled it, 91 citations in OpenAlex.

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  14. SARS-CoV-2-Specific Immune Response and the Pathogenesis of COVID-19.International journal of molecular sciences · 2022
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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 at 3 institutions in 2 countries.

Gerard Kian-Meng GohGoh's BioComputing, Singapore. Electronic address: gohsbiocomputing@yahoo.com.
A Keith DunkerCenter for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.
James A FosterDepartment of Biological Sciences, University of Idaho, Moscow, ID, USA; Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID, USA.
Vladimir N UverskyDepartment of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA; Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow region, Russia.
Indiana University School of MedicineUniversity of Idaho · USUniversity of South Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coronavirus (CoV) family consists of viruses that infects a variety of animals including humans with various levels of respiratory and fecal-oral transmission levels depending on the behavior of the viruses' natural hosts and optimal viral fitness. A model to classify and predict the levels of respective respiratory and fecal-oral transmission potentials of the various viruses was built before the outbreak of MERS-CoV using AI and empirically-based molecular tools to predict the disorder level of proteins. Using the percentages of intrinsic disorder (PID) of the nucleocapsid (N) and membrane (M) proteins of CoV, the model easily clustered the viruses into three groups with the SARS-CoV (M PID = 8%, N PID = 50%) falling into Category B, in which viruses have intermediate levels of both respiratory and fecal-oral transmission potentials. Later, MERS-CoV (M PID = 9%, N PID = 44%) was found to be in Category C, which consists of viruses with lower respiratory transmission potential but with higher fecal-oral transmission capabilities. Based on the peculiarities of disorder distribution, the SARS-CoV-2 (M PID = 6%, N PID = 48%) has to be placed in Category B. Our data show however, that the SARS-CoV-2 is very strange with one of the hardest protective outer shell, (M PID = 6%) among coronaviruses. This means that it might be expected to be highly resilient in saliva or other body fluids and outside the body. An infected body is likelier to shed greater numbers of viral particles since the latter is more resistant to antimicrobial enzymes in body fluids. These particles are also likelier to remain active longer. These factors could account for the greater contagiousness of the SARS-CoV-2 and have implications for efforts to prevent its spread.

Indexed as

BetacoronavirusBody FluidsCoronavirus InfectionsCOVID-19FecesHumansMiddle East Respiratory Syndrome CoronavirusPandemicsPneumonia, ViralSalivaSARS-CoV-2Severe Acute Respiratory SyndromeSevere acute respiratory syndrome-related coronavirusCoronavirusCoVCOVIDIntrinsically disordered proteinMembraneMERSNucleocapsidSARSSpread

Identifiers

PMID32244041
PMCPMC7118597
OpenAlexW3013294882

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.