Fecko, J. | bioRxiv Science

bioRxiv2025

A fold switch regulates conformation of an alphavirus virus RNA-dependent RNA polymerase

Alphaviruses are mosquito-vectored, positive-strand RNA viruses causing rheumatic and neurological diseases. Like all RNA viruses, they encode an RNA-dependent RNA polymerase (RdRp, nsP4). Purification of an nsP4 derivative capable of processive RNA synthesis from a heteropolymeric template has been unsuccessful. Prior studies indicated Onyong-nyong virus (ONNV) nsP4 is soluble and requires additional non-structural proteins for activity. We performed biochemical and biophysical characterization of ONNV nsP4, including analytical ultracentrifugation and small-angle X-ray scattering (SAXS), revealing an extended conformation inconsistent with AlphaFold predictions of a compact structure. Fold switching was required for the extended conformation. Hydrogen-deuterium exchange mass spectrometry confirmed the fold-switched, extended state. Phylogenetic analysis showed conservation of residues contributing to both extended and compact states, implying functional roles for each. The extended form exhibited weak RNA binding and no polymerase activity on primed templates. The SAXS envelope of a precursor containing 50 amino acids from the nsP3 C-terminus (CT50-P34) matched the compact state. We propose precursor forms adopt the compact conformation. At the replication site, proteolytic cleavage would convert the precursor to an active polymerase. Polymerase dissociation upon completion of synthesis would induce fold switching to the inactive, extended state, precluding cytoplasmic activity that would activate intracellular immune responses.

biophysics↗

bioRxiv2025

Novel Computational Pipeline to Identify Target Sites for Broad Spectrum Antiviral Drugs

Emerging viruses pose an ongoing threat to human health. While certain viral families are common sources of outbreaks, predicting the specific virus within a family that will cause the next outbreak or pandemic is not possible, creating an urgent need for broad spectrum antiviral drugs that are effective against an array of related viral pathogens. However, broad spectrum drug development is hindered by the lack of detailed knowledge of compound binding sites that are structurally and functionally conserved between viral family members and are essential for virus replication. To overcome this limitation, we developed an in silico approach that combines AI-driven protein structure prediction, computational fragment soaking, multiple sequence alignment, and protein stability calculations to identify highly conserved target sites that are both solvent-accessible and conserved. We applied this approach to the Togaviridae family, which includes emerging pandemic disease threats such as chikungunya and Venezuelan equine encephalitis virus for which there are currently no approved antiviral therapies. Our analysis identified multiple solvent accessible and structurally conserved pockets in the alphavirus non-structural protein 2 (nsP2) protease domain, which is essential for processing of the viral replicase proteins. Mutagenesis of key solvent accessible and conserved residues identified novel pockets that are essential for protease activity and the replication of multiple alphaviruses, validating these pockets as potential antiviral target sites for nsP2 inhibitors. These findings highlight the potential of artificial intelligence-informed modeling for revealing functionally conserved, accessible pockets as a means of identifying potential target binding sites for broadly active direct acting antivirals. Significance StatementHere we present a novel integrative computational approach to identify novel target sites for broadly acting antiviral drugs. We used this technique to identify multiple functionally and structurally conserved protein surface pockets within the alphavirus nsP2 protease and methyl-transferase-like domain. Mutagenesis of these pockets identified that they are essential for protease activity and replication of a genetically diverse group of alphaviruses, validating these sites as potential targets for broadly active small molecule alphavirus inhibitors. This integrative AI-driven approach thus provides an important tool in developing antivirals essential for pandemic preparedness.

microbiology↗