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Evolution of coronavirus frameshifting elements: Competing stem networks explain conservation and variability.
Shuting Yan1, Qiyao Zhu2, Jenna Hohl2
1Department of Chemistry, New York University, New York, NY 10003.
Summary
Coronaviruses use frameshifting RNA elements (FSEs) for replication. This study reveals how FSE sequences evolve, influencing their structure and frameshifting efficiency, offering insights for antiviral drug development.
Area of Science:
- Virology
- Computational Biology
- Structural Biology
Background:
- The frameshifting RNA element (FSE) is crucial for programmed ribosomal frameshifting (-1 PRF) in coronaviruses (CoVs).
- FSEs are potential drug targets due to their role in viral protein production.
- The secondary structure, particularly pseudoknots and stem loops, is believed to be key to FSE function.
Purpose of the Study:
- To investigate the evolutionary structural dynamics of FSEs in Alpha and Beta-CoVs.
- To understand how sequence variations influence FSE topology and frameshifting efficiency.
- To provide insights for developing broad-spectrum antiviral therapies targeting CoV FSEs.
Main Methods:
- Utilized graph theory-based methods within the RNA-As-Graphs (RAG) framework.
- Calculated conformational landscapes of viral FSEs across varying sequence lengths.
- Analyzed sequence-structure correlations and evolutionary patterns in Alpha and Beta-CoVs.
Main Results:
- FSE sequences encode multiple competing stems, favoring diverse topologies like pseudoknots, stem loops, and junctions.
- Recurring mutation patterns explain alternative stem formations and topological shifts.
- FSE topology robustness is linked to stem shifting and base pair coevolution.
- Length-dependent conformational changes correlate with frameshifting efficiency modulation.
Conclusions:
- FSE sequence evolution drives structural diversity and influences frameshifting efficiency in coronaviruses.
- Understanding these sequence-structure-function relationships offers a basis for novel therapeutic strategies.
- The study provides tools for analyzing virus sequence-structure correlations and CoV FSE evolution.
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