Speeding drug discovery targeting RNAs: an iterative “RNA selection-compounds screening cycle“ for exploring RNA-small molecule pairs

2021 
Abstract RNA is an emerging target of next-generation drug development. Recently, new small molecules targeting RNAs were discovered by several pharmaceutical companies. Methods have been reported to identify small molecules targeting a specific RNA sequence and structural motif, however, because of diverse sequence and structural motifs potentially present in the druggable functional RNAs, large sets of structure-activity relationships (SARs) information of small molecule – RNA interactions will be required for the acceleration and efficient startup of the discovery programs toward unprecedented RNA targets. Here we describe our iterative RNA selection and compounds screening to accumulate rich information about small molecules – RNA interaction. The RNAs that selectively bind to the initial molecular target, compound 1 from our in-house chemical library (JT-library), was isolated using in vitro selection technique from a hairpin-structured RNA library mimicking precursor-microRNA (pre-miRNA). Then, we engineered pre-let-7f-2 to create its mutant that can bind to compound 1 by embedding the in vitro selected RNA motif for compound 1 in the hairpin loop region. The obtained mutant pre-let-7f-2-loop-mt was used as a target for screening 316 analogs of compound 1. A surface plasmon resonance (SPR) -based screening was performed against pre-let-7f-2-loop-mt-immobilized sensor surface and we obtained four compounds that can bind to the RNA. Among these four compounds, three compounds showed higher affinity to pre-let-7f-2-loop-mt than the parental compound 1, which suggests the feasibility of our strategy for gathering the SAR information on small molecule – RNA interactions. We demonstrated only one cycle of RNA selection and compound screening in the present study, but can continue this cycle with the selected molecule to gain new RNAs and even new RNA motifs and gather much SAR information with improved accuracy.
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