Shapify: Paths to SARS-CoV-2 frameshifting pseudoknot

Author:

Trinity LukeORCID,Wark Ian,Lansing Lance,Jabbari HosnaORCID,Stege UlrikeORCID

Abstract

Multiple coronaviruses including MERS-CoV causing Middle East Respiratory Syndrome, SARS-CoV causing SARS, and SARS-CoV-2 causing COVID-19, use a mechanism known as −1 programmed ribosomal frameshifting (−1 PRF) to replicate. SARS-CoV-2 possesses a unique RNA pseudoknotted structure that stimulates −1 PRF. Targeting −1 PRF in SARS-CoV-2 to impair viral replication can improve patients’ prognoses. Crucial to developing these therapies is understanding the structure of the SARS-CoV-2 −1 PRF pseudoknot. Our goal is to expand knowledge of −1 PRF structural conformations. Following a structural alignment approach, we identify similarities in −1 PRF pseudoknots of SARS-CoV-2, SARS-CoV, and MERS-CoV. We provide in-depth analysis of the SARS-CoV-2 and MERS-CoV −1 PRF pseudoknots, including reference and noteworthy mutated sequences. To better understand the impact of mutations, we provide insight on −1 PRF pseudoknot sequence mutations and their effect on resulting structures. 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 enhances our understanding of SARS-CoV-2 −1 PRF pseudoknot conformations by providing energetically favourable predictions that are relevant to structure-function and may correlate with −1 PRF efficiency. Applied to the SARS-CoV-2 −1 PRF pseudoknot, Shapify unveils previously unknown paths from initial stems to pseudoknotted structures. 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.

Funder

University of Victoria

Natural Sciences and Engineering Research Council of Canada

Microsoft Research

Publisher

Public Library of Science (PLoS)

Subject

Computational Theory and Mathematics,Cellular and Molecular Neuroscience,Genetics,Molecular Biology,Ecology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics

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