Abstract

EVOLUTIONARY STUDY OF COVID-19 USING BIOINFORMATICS APPROACH

Mohan Kumar*

ABSTRACT

The Coronaviruses are belongs to a genus of the Coronaviridae family, the word “corona” represents distinctive morphology of virions and are medium sized about 30 kb long and having positive sense, single stranded RNA (ssRNA) that cause illness in humans and animals. First human coronavirus (HCoV) was isolated from persons having common cold in mid 1960s (Foula Vassilara et al., 2018). First human coronaviruses were detected are HCoV-229E and HCoV-OC43, associated with the symptoms of common cold and respiratory infections and were found more pathogenic in children, elderly and persons having less immunity due to some associated diseases.[1] Form the study it has been conformed that human coronaviruses dividing rapidly results in variations in their genomic pattern, having different cellular receptor.[2] In past 17 years, different types of HCoVs identified are HCoV-229E, HCoV-NL63, HCoV-OC43, HCoV-HKU1, Severe acute respiratory syndrome coronavirus (SARS-HCoV) and Middle East respiratory syndrome coronavirus (MERS-CoV), were caused life- threatening respiratory problems among human populations.[5] From a case study it has been conformed that the pathogenicity of coronaviruses varies with the change in climate, more in winter and spring than in summer.[4] Recently a new and highly mutated form of coronaviruses emerged as a global life threatening, known as 2019 novel coronavirus written as Covid-19, according to World Health Organisation report as of 2:20pm CEST, 11 June 2020, there have been 7,273,958 confirmed cases of COVID-19, including 413,372 deaths.[3] In this study we have explored the rate of genomic variation of covid-19 with respect to time, place, migration, transmission, age and individual immunity that will help to understand the pathogenicity and eventually will help to study further in molecular level in order to develop more potent drugs and vaccines against Covid-19.

Keywords: Covid-19, HCoV-229E, HCoV-NL63, HCoV-OC43, HCoV-HKU1, SARS-CoV, MERS-HCoV.