SARS-CoV-2 Ribosomal Frameshifting Pseudoknot: Detection of Inter-viral Structural Similarity

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Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the COVID-19 pandemic. After over 160 million cases and 3.3 million deaths worldwide as of May 2021, it is still unclear when this crisis will end. Thus, there is an urgent need for treatments that improve the prognosis of seriously affected patients. Multiple viruses including HIV, MERS-CoV (coronavirus responsible for Middle East Respiratory Syndrome, MERS), SARS-CoV (coronavirus responsible for SARS) and SARS-CoV-2 use a mechanism known as -1 programmed ribosomal frameshifting (-1 PRF) to successfully replicate. SARS-CoV and SARS-CoV-2 possess 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 can be an excellent strategy to impair viral replication and improve patients' prognoses. Crucial to developing these successful therapies is modeling the structure of the SARS-CoV-2 -1 PRF pseudoknot. Following a structural alignment approach, we identify similarities in -1 PRF pseudoknots of SARS-CoV-2, SARS-CoV, and MERS-CoV. In addition, we provide a better understanding of the SARS-CoV-2 -1 PRF pseudoknot by investigating the structural landscape using a hierarchical folding approach. We provide in-depth analysis on alternative structure prediction methods based on SARS-CoV-2 structural reactivity (SHAPE) data to contextualize and motivate future RNA structure-function research. Since understanding the impact of mutations is vital to long-term success of treatments based on predicted RNA functional structures, we provide insight on SARS-CoV-2 -1 PRF pseudoknot sequence mutations and their effect on the resulting structure.

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APA

Trinity, L., Lansing, L., Jabbari, H., & Stege, U. (2021). SARS-CoV-2 Ribosomal Frameshifting Pseudoknot: Detection of Inter-viral Structural Similarity. In Proceedings - 2021 IEEE 9th International Conference on Healthcare Informatics, ISCHI 2021 (pp. 451–460). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICHI52183.2021.00080

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