RNA secondary and tertiary structure is critically involved in ribozyme and ribosomal rRNA function, as well as viral and cellular regulation. Traditional experimental methods for RNA structure determination such as X-ray crystallography or chemical mapping are incisive; however, these approaches suffer from low-throughput and low-dimensionality, respectively. Computational approaches, leveraging evolutionary signals from correlated positions’ mutations, provide an alternative means to infer RNA structures. However, these methods require assembly, and face challenges due to statistical biases inherent in multiple sequence alignment (MSA). Furthermore, these methods cannot make use of the full spectrum of natural variations seen for a given RNA element.
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https://www.biorxiv.org/content/10.1101/2024.10.03.616574v1