| Literature DB >> 32640417 |
Durjoy Lahiri1, Ritwick Mondal2, Shramana Deb3, Deebya Bandyopadhyay2, Gourav Shome4, Sukanya Sarkar5, Subhas C Biswas5.
Abstract
BACKROUND AND AIMS: After the emergence of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in the last two decades, the world is facing its new challenge in SARS-CoV-2 pandemic with unfathomable global responses. The characteristic clinical symptoms for Coronavirus (COVID-19) affected patients are high fever, dry-cough, dyspnoea, lethal pneumonia whereas some patients also show additional neurological signs such as headache, nausea, vomiting etc. The accumulative evidences suggest that SARS-CoV-2 is not only confined within the respiratory tract but may also invade the central nervous system (CNS) and peripheral nervous system (PNS) inducing some fatal neurological diseases. Here, we analyze the phylogenetic perspective of SARS-CoV-2 with other strains of β-Coronaviridae from a standpoint of neurological spectrum disorders.Entities:
Keywords: ACE2; CNS; COVID-19; Coronavirus; Neurological disorders; PNS; Phylogenetic perspective; SARS-CoV2
Mesh:
Year: 2020 PMID: 32640417 PMCID: PMC7331527 DOI: 10.1016/j.dsx.2020.06.062
Source DB: PubMed Journal: Diabetes Metab Syndr ISSN: 1871-4021
Fig. 1A. Phylogenetic network showing receptor binding domains from various betacoronaviruses. The star denotes nCoV-19 and the question marks means unknown receptor used by the viruses.B,C,D depict structural comparison of the receptor binding domain of SARS- CoV,nCoV-19,MERS-CoV binding to their own receptors respectively. Magenta colour represents core domain and the external subdomains of SARS-CoV,nCoV-19,MERS CoV are represented by orange, blue and green respectively [9].
Fig. 2Based on the manually curated knowledge in UniProtKB and via automatic text mining of the biomedical literature,tissue associations are derived. The confidence of each association is signified by stars, where ★★★★★ is the highest confidence and ★☆☆☆☆ is the lowest. Each tissue–gene association is represented on a text-mining score, which is proportional to 1) the absolute number of comentionings and 2) the ratio of observed to expected comentionings (i.e. the enrichment). These scores are normalized to z-scores by comparing them to a random background. This is represented by stars, each star corresponding to two standard deviations above the mean of the background distribution [TISSUE2.0].