SARS-CoV infection crosstalk with human host cell noncoding-RNA machinery: An in-silico approach.

ABSTRACT

Although 70 % of the genome is transcribed to RNA in humans, only ∼2% of these transcripts are translated into proteins. The rest of the transcripts are defined as noncoding RNAs, including Long noncoding RNAs (LncRNAs) and MicroRNAs (miRNAs) that mostly function post-transcriptionally to regulate the gene expression. The outbreak of a novel coronavirus (SARS-CoV) has caused a major public health concern across the globe. The SARS-CoV is the seventh coronavirus that is known to cause human disease. There are currently no promising antiviral drugs with proven efficacy nor are there vaccines for its prevention. As of August 10, 2020, SARS-CoV has been infected more than 13 million cases in more than 213 countries, with an estimated mortality rate of ∼3 %. Thus, it is of utmost important priority to develop novel therapies for COVID-19. It is not fully investigated whether noncoding RNAs regulate signaling pathways that SARS-CoV involved in. Hence, computational analysis of the noncoding RNA interactions and determining importance of key regulatory noncoding RNAs in antiviral defense mechanisms will likely be helpful in developing new drugs to attack SARS-CoV infection. To elucidate this, we utilized bioinformatic approaches to find the interaction network of SARS-CoV/human proteins, miRNAs, and lncRNAs. We found TGF-beta signaling pathway as one of the potential interactive pathways. Furthermore, potential miRNAs/lncRNAs networks that the virus might engage during infection in human host cells have been shown. Altogether, TGF-beta signaling pathway as well as hub miRNAs, and LncRNAs involve during SARS-CoV pathogenesis can be considered as potential therapeutic targets.