We report here on the nuclear magnetic resonance (NMR) 19 F screening of 14 RNA targets with different secondary and tertiary structure to systematically assess druggability of RNAs. Our RNA targets include representative bacterial riboswitches that naturally bind with nanomolar affinity and high specificity to cellular metabolites of low molecular weight. Based on counter‐screens against five DNAs and five proteins, we can show that RNA can be specifically targeted. To demonstrate the quality of the initial fragment library that has been designed for easy follow‐up chemistry, we further show how to increase binding affinity from an initial fragment hit by chemistry that links the identified fragment to the intercalator acridine. Thus, we achieve low micromolar binding affinity without losing binding specificity between two different terminator structures.

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Riboswitches are gene regulatory elements located in untranslated mRNA regions. They bind inducer molecules with high affinity and specificity. Cyclic-di-nucleotide-sensing riboswitches are major regulators of genes for the environment, membranes and motility (GEMM) of bacteria. Up to now, structural probing assays or crystal structures have provided insight into the interaction between cyclic-di-nucleotides and their corresponding riboswitches. ITC analysis, NMR analysis and computational modeling allowed us to gain a detailed understanding of the gene regulation mechanisms for the Cd1 (Clostridium difficile) and for the pilM (Geobacter metallireducens) riboswitches and their respective di-nucleotides c-di-GMP and c-GAMP. Binding capability showed a 25 nucleotide (nt) long window for pilM and a 61 nt window for Cd1. Within this window, binding affinities ranged from 35 μM to 0.25 μM spanning two orders of magnitude for Cd1 and pilM showing a strong dependence on competing riboswitch folds. Experimental results were incorporated into a Markov simulation to further our understanding of the transcriptional folding pathways of riboswitches. Our model showed the ability to predict riboswitch gene regulation and its dependence on transcription speed, pausing and ligand concentration.