RNA structural determination is a complex problem because of the inherent flexibility, multiple biologically relevant structures, and rapid degradation of RNA. Current techniques are able to determine secondary structures and small RNA tertiary structure but are often time consuming and tedious. Pattern recognition utilizes differential binding of a receptor to a known analyte to form patterns, which then can be used to evaluate unknown analytes. A receptor array utilizing differential binding of small molecules to RNA would allow for creation of patterns based on function and/or protein binding partners of known RNA. Unknown RNA structures could then be rapidly screened using the previously determined patterns, allowing for classification of complex RNA with minimal structure perturbations. To this end, a library of highly defined secondary structure sequences was determined using computational modeling as a training set to predict the patterns of RNA-small molecule binding unique to each structure. Also, an aminoglycoside receptor library was generated using simple synthetic approaches to form a receptor library array. The aminoglycoside library will be evaluated against the computationally determined RNA structural motifs to determine differential binding of RNA to a small molecule library utilizing a solution phase fluorescence assay. Preliminary data is consistent with the ability of the small molecule library to differentiate a hairpin and bulge structure within TAR RNA. Continuing work will focus on generating a library of known secondary and tertiary RNA structures, evaluating the differential binding of the small molecule library, and classification of unknown RNA structures.

Pattern recognition for the classification of long non-coding RNA

251st National Meeting (2016)

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