Defining RNA motif–aminoglycoside interactions via two-dimensional combinatorial screening and structure–activity relationships through sequencing

RNA is an extremely important target for the development of chemical probes of function or small molecule therapeutics. Aminoglycosides are the most well studied class of small molecules to target RNA. However, the RNA motifs outside of the bacterial rRNA A-site that are likely to be bound by these compounds in biological systems is largely unknown. If such information were known, it could allow for aminoglycosides to be exploited to target other RNAs and, in addition, could provide invaluable insights into potential bystander targets of these clinically used drugs. We utilized two-dimensional combinatorial screening (2DCS), a library-versus-library screening approach, to select the motifs displayed in a 3 × 3 nucleotide internal loop library and in a 6-nucleotide hairpin library that bind with high affinity and selectivity to six aminoglycoside derivatives. The selected RNA motifs were then analyzed using structure–activity relationships through sequencing (StARTS), a statistical approach that defines the privileged RNA motif space that binds a small molecule. StARTS allowed for the facile annotation of the selected RNA motif–aminoglycoside interactions in terms of affinity and selectivity. The interactions selected by 2DCS generally have nanomolar affinities, which is higher affinity than the binding of aminoglycosides to a mimic of their therapeutic target, the bacterial rRNA A-site.

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