RESUMO
Coronavirus (CoV) genomes consist of positive-sense single-stranded RNA and are among the largest viral RNAs known to date (â¼30 kb). As a result, CoVs deploy sophisticated mechanisms to replicate these extraordinarily large genomes as well as to transcribe subgenomic messenger RNAs. Since 2003, with the emergence of three highly pathogenic CoVs (SARS-CoV, MERS-CoV, and SARS-CoV-2), significant progress has been made in the molecular characterization of the viral proteins and key mechanisms involved in CoV RNA genome replication. For example, to allow for the maintenance and integrity of their large RNA genomes, CoVs have acquired RNA proofreading 3'-5' exoribonuclease activity (in nonstructural protein nsp14). In order to replicate the large genome, the viral-RNA-dependent RNA polymerase (RdRp; in nsp12) is supplemented by a processivity factor (made of the viral complex nsp7/nsp8), making it the fastest known RdRp. Lastly, a viral structural protein, the nucleocapsid (N) protein, which is primarily involved in genome encapsidation, is required for efficient viral replication and transcription. Therefore, CoVs are a paradox among positive-strand RNA viruses in the sense that they use both a processivity factor and have proofreading activity reminiscent of DNA organisms in addition to structural proteins that mediate efficient RNA synthesis, commonly used by negative-strand RNA viruses. In this review, we present a historical perspective of these unsuspected discoveries and detail the current knowledge on the core replicative machinery deployed by CoVs.
Assuntos
Genoma Viral , Vírus de RNA de Cadeia Positiva , SARS-CoV-2 , COVID-19/virologia , Genoma Viral/genética , Humanos , Mutação , Vírus de RNA de Cadeia Positiva/genética , RNA Viral/genética , RNA Viral/metabolismo , RNA Polimerase Dependente de RNA/metabolismo , SARS-CoV-2/genética , Proteínas não Estruturais Virais/metabolismo , Replicação Viral/genéticaRESUMO
Understanding the replication machinery of viruses contributes to suggest and try effective antiviral strategies. Exhaustive knowledge about the proteins structure, their function, or their interaction is one of the preconditions for successfully modeling it. In this context, modeling methods based on a formal representation with a high semantic expressiveness would be relevant to extract proteins and their nucleotide or amino acid sequences as an element from the replication process. Consequently, our approach relies on the use of semantic technologies to design the SARS-CoV-2 replication machinery. This provides the ability to infer new knowledge related to each step of the virus replication. More specifically, we developed an ontology-based approach enriched with reasoning process of a complete replication machinery process for SARS-CoV-2. We present in this paper a partial overview of our ontology OntoRepliCov to describe one step of this process, namely, the continuous translation or protein synthesis, through classes, properties, axioms, and SWRL (Semantic Web Rule Language) rules.
