Among all living things, RNA plays a variety of crucial roles such as catalysis, protein production, and gene regulation. Resolving the structures of these RNAs is critically important to understanding their functions and potential for therapeutic targeting. Pseudoknots, a type of secondary structure which creates unique 3-dimensional folds, can play fundamental roles in the viral life cycle, and as such, can be potential targets for small molecule antivirals. An RNA secondary structure prediction algorithm, ThreshKnot, can be used to identify pseudoknotted structures. The ThreshKnot heuristic was run on sliding windows of the SARS-CoV-2 genome to identify a number of potential pseudoknots. These structures were then further refined using ShapeKnots, an algorithm which predicts RNA secondary structures using SHAPE reactivity data. Finally, the base pairing probability of the sequences containing each predicted pseudoknot were plotted and compared with SHAPE reactivity data from multiple independent experiments, and this helped determine the regions which are predicted to be structured with the greatest agreement to experimental evidence. The regions of the SARS genome predicted to contain pseudoknots are promising targets for further structural determination as part of the growing effort to characterize viral RNA structures to inform the development of antivirals against them.

Predicting pseudoknots in SARS-CoV-2 with ThreshKnot, ShapeKnots, and reactivity data

ACS Spring 2022

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