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Understanding the mechanistic basis of non-coding RNA through molecular dynamics simulations

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https://doi.org/10.1016/j.jsb.2019.03.004
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Abstract

Noncoding RNA (ncRNA) has a key role in regulating gene expression, mediating fundamental processes and diseases via a variety of yet unknown mechanisms. Here, we review recent applications of conventional and enhanced Molecular Dynamics (MD) simulations methods to address the mechanistic function of large biomolecular systems that are tightly involved in the ncRNA function and that are of key importance in life sciences. This compendium focuses of three biomolecular systems, namely the CRISPR-Cas9 genome editing machinery, group II intron ribozyme and the ribonucleoprotein complex of the spliceosome, which edit and process ncRNA. We show how the application of a novel accelerated MD simulations method has been key in disclosing the conformational transitions underlying RNA binding in the CRISPR-Cas9 complex, suggesting a mechanism for RNA recruitment and clarifying the conformational changes required for attaining genome editing. As well, we discuss the use of mixed quantum-classical MD simulations in deciphering the catalytic mechanism of RNA splicing as operated by group II intron ribozyme, one of the largest ncRNA structures crystallized so far. Finally, we debate the future challenges and opportunities in the field, discussing the recent application of MD simulations for unraveling the functional biophysics of the spliceosome, a multi-mega Dalton complex of proteins and small nuclear RNAs that performs RNA splicing in humans. This showcase of applications highlights the current talent of MD simulations to dissect atomic-level details of complex biomolecular systems instrumental for the design of finely engineered genome editing machines. As well, this review aims at inspiring future investigations of several other ncRNA regulatory systems, such as micro and small interfering RNAs, which achieve their function and specificity using RNA-based recognition and targeting strategies.

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