Background: Multiple viruses including HIV, MERS-CoV (coronavirus responsible for Middle East Respiratory Syndrome, MERS), SARS-CoV (coronavirus responsible for SARS) and SARS-CoV-2 (coronavirus responsible for COVID-19) use a mechanism known as -1 programmed ribosomal frameshifting (-1 PRF) to successfully replicate. SARS-CoV-2 possesses a unique RNA pseudoknotted structure that stimulates -1 PRF. Recent experiments identified small molecules as antiviral agents that can bind to the pseudoknot and disrupt its stimulation of -1 PRF. Targeting -1 PRF in SARS-CoV-2 to impair viral replication can improve patients' prognoses.Crucial to developing these successful therapies is modeling the structure of the SARS-CoV-2 -1 PRF pseudoknot.Our goal is to expand knowledge of possible pseudoknot conformations.
Results: Following a structural alignment approach, we identify similarities in -1 PRF pseudoknots of SARS-CoV-2, SARS-CoV, and MERS-CoV. We introduce Shapify, a novel algorithm that given an RNA sequence incorporates structural reactivity (SHAPE) data and partial structure information to output an RNA secondary structure prediction within a biologically sound hierarchical folding approach. Shapify helps us to better understand non-native SARS-CoV-2 -1 PRF pseudoknot conformations that are relevant to structure function and may correlate with -1 PRF efficiency. We provide in-depth analysis by investigating the structural landscape for the SARS-CoV-2 -1 PRF pseudoknot, including reference and mutated sequences. To better understand the impact of mutations, we provide insight on SARS-CoV-2 -1 PRF pseudoknot sequence mutations and their effect on the resulting structure.
Conclusion: We identify the consensus structure for SARS-CoV, SARS-CoV-2, and MERS-CoV -1 PRF pseudoknots; this similarity in functional RNA structures aids treatment preparation for existing and emergent viruses. Shapify predictions are guided both by SHAPE data and partial structure information. Applied to the SARS-CoV-2 -1 PRF pseudoknot, Shapify unveiled previously unknown pathways from initial stems to pseudoknotted secondary structures. Where SHAPE data is unavailable we provide predictions for noteworthy SARS-CoV-2 -1 PRF mutated pseudoknot sequences. By contextualizing our work with available experimental data, our structure predictions motivate future RNA structure-function research and can aid 3-D modeling of pseudoknots.