Evidence map›Paper›PMID 32595278›Full record

ArticleInfectious diseases2020

NeoCoV Is Closer to MERS-CoV than SARS-CoV.

Mohamed M Hassan, Mohamed A Hussain, Sumaya Kambal, Ahmed A Elshikh, Osama R Gendeel, Siddig A Ahmed, Rami A Altayeb, Abdelhafiz Ma Muhajir, Sofia B Mohamed

Abstract read
In one paragraph

Article in Infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Potential Therapeutic Target and Vaccines for SARS-CoV-2.Pathogens (Basel, Switzerland) · 2023
    Article
  3. Article
  4. Review
  5. 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

9 authors.

Mohamed M HassanBioinformatics and Biostatistics Department, National University Biomedical Research Institute, National University, Khartoum, Sudan.ORCID https://orcid.org/0000-0003-1544-7932
Mohamed A HussainDepartment of Pharmaceutical Microbiology, International University of Africa, Khartoum, Sudan.
Sumaya KambalBioinformatics and Biostatistics Department, National University Biomedical Research Institute, National University, Khartoum, Sudan.
Ahmed A ElshikhDepartment of Microbiology, Faculty of Pure and Applied Sciences, International University of Africa, Khartoum, Sudan.
Osama R GendeelFaculty of Science and Technology, Omdurman Islamic University, Omdurman, Sudan.
Siddig A AhmedFaculty of Science and Technology, Omdurman Islamic University, Omdurman, Sudan.
Rami A AltayebFaculty of Science and Technology, Omdurman Islamic University, Omdurman, Sudan.
Abdelhafiz Ma MuhajirFaculty of Science and Technology, Omdurman Islamic University, Omdurman, Sudan.
Sofia B MohamedBioinformatics and Biostatistics Department, National University Biomedical Research Institute, National University, Khartoum, Sudan.ORCID https://orcid.org/0000-0001-6718-3540

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, Coronavirus has been given considerable attention from the biomedical community based on the emergence and isolation of a deadly coronavirus infecting human. To understand the behavior of the newly emerging MERS-CoV requires knowledge at different levels (epidemiologic, antigenic, and pathogenic), and this knowledge can be generated from the most related viruses. In this study, we aimed to compare between 3 species of Coronavirus, namely Middle East Respiratory Syndrome (MERS-CoV), Severe Acute Respiratory Syndrome (SARS-CoV), and NeoCoV regarding whole genomes and 6 similar proteins (E, M, N, S, ORF1a, and ORF1ab) using different bioinformatics tools to provide a better understanding of the relationship between the 3 viruses at the nucleotide and amino acids levels. All sequences have been retrieved from National Center for Biotechnology Information (NCBI). Regards to target genomes' phylogenetic analysis showed that MERS and SARS-CoVs were closer to each other compared with NeoCoV, and the last has the longest relative time. We found that all phylogenetic methods in addition to all parameters (physical and chemical properties of amino acids such as the number of amino acid, molecular weight, atomic composition, theoretical pI, and structural formula) indicated that NeoCoV proteins were the most related to MERS-CoV one. All phylogenetic trees (by both maximum-likelihood and neighbor-joining methods) indicated that NeoCoV proteins have less evolutionary changes except for ORF1a by just maximum-likelihood method. Our results indicated high similarity between viral structural proteins which are responsible for viral infectivity; therefore, we expect that NeoCoV sooner may appear in human-related infection.

Indexed as

6 proteinsbioinformatics analysiscoronavirusesevolutionary studyMERS-CoVNeoCoVSARS-CoV

Identifiers

PMID32595278
PMCPMC7298434

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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.