Comparative analysis of protein synthesis rate in COVID-19 with other human coronaviruses

The genetic code contains information that impacts the efficiency and rate of translation. Translation elongation plays a crucial role in determining the composition of the proteome, errors within a protein contributes towards disease processes. It is important to analyze the novel coronavirus (2019-nCoV) at the codon level to find similarities and variations in hosts to compare with other human coronavirus (CoVs). This requires a comparative and comprehensive study of various human and zoonotic nature CoVs relating to codon usage bias, relative synonymous codon usage (RSCU), proportions of slow codons, and slow di-codons, the effective number of codons (ENC), mutation bias, codon adaptation index (CAI), and codon frequencies. In this work, seven different CoVs were analyzed to determine the protein synthesis rate and the adaptation of these viruses to the host cell. The result reveals that the proportions of slow codons and slow di-codons in human host of 2019-nCoV and SARS-CoV found to be similar and very less compared to the other five coronavirus types, which suggest that the 2019-nCoV and SARS-CoV have faster protein synthesis rate. Zoonotic CoVs have high RSCU and codon adaptation index than human CoVs which implies the high translation rate in zoonotic viruses. All CoVs have more AT% than GC% in genetic codon compositions. The average ENC values of seven CoVs ranged between 38.36 and 49.55, which implies the CoVs are highly conserved and are easily adapted to host cells. The mutation rate of 2019-nCoV is comparatively less than MERS-CoV and NL63 that shows an evidence for genetic diversity. Host-specific codon composition analysis portrays the relation between viral host sequences and the capability of novel virus replication in host cells. Moreover, the analysis provides useful measures for evaluating a virus-host adaptation, transmission potential of novel viruses, and thus contributes to the strategies of anti-viral drug design.