RNA viruses are responsible for all emerging infectious diseases (Ebola, Zika, Dengue, Coronaviruses…). Unfortunately, most of the time, we have few weapons to fight them, due to a certain lack of knowledge of their propagation cycle.
Combining multidisciplinary approaches such as biochemistry, enzymology, structural biology combining to artificial intelligence methods, we aim to dissect fascinating RNA virus replication machineries. These data will lay the groundwork for the discovery of anti-viral molecules. Indeed, viral replicases have already proved their worth with, for example, the development of therapies against HIV and HCV.
Model of RNApol complex’s formation
Reconstitution of the SARS-CoV replicative catalytic core
The successive emergence of three highly pathogenic Coronaviruses (CoVs): the Severe Acute Respiratory Syndrome-CoV (SARS-CoV) in 2003, the Middle East Respiratory Syndrome-CoV (MERS-CoV) in 2012 and now the new CoV (CoVid-19) reinforces the urgent needs of clinical options. Indeed, neither vaccine nor antiviral drugs are available against CoVs. Interestingly, among (+) RNA viruses, coronaviruses stand out as having the largest (~30-kb) single-stranded RNA genome known to date associated paradoxically with low mutations rates. CoVs encode a huge replication/transcription machinery consisting, at least, of 16 viral nonstructural proteins (nsps). Thus, a central question is by which mechanisms, these viruses maintain their astonishingly large RNA genome.
In the case of SARS-CoV, we showed that the viral RNA-dependent RNA polymerase (named nsp12) requires a processivity proteins complex formed by 2 other viral proteins (nsp7 and nsp8). Then, we demonstrated that the SARS-CoV polymerase complex in association with the viral nsp14 protein harboring a 3’-5’ exonuclease activity is able to faithfully replicate its RNA genome. Indeed, this protein complex can selectively excise a misincorporated ribonucleotide at the 3’-end of the nascent RNA. This SARS-CoV proofreading machinery is also able to excise erroneous mutagenic nucleotides inserted by the viral polymerase, such Ribavirin (a FDA-approved broad-spectrum antiviral drug). This feature provides part of the explanation for the ineffectiveness of Ribavirin on CoVs-infected patients.
In silico viral RNA polymerization modelling
Modelling of complex biological systems is a growing field of research and a valuable tool for public health. Examples of applications include modelling the dynamics of virus transmission, predicting circulating strains in vaccine manufacturing or modelling the occurrence of resistance mutations after treatment with antivirals.
We develop an integrative system using artificial intelligence approaches to anticipate the biodiversity of RNA virus polymerases. Our strategy relies on the use of semantic technologies (especially ontology engineering) associated to in silico simulation. Then, an iterative process is engaged where in silico results are confronted with the in vitro experimentations.