Driving factors in amiloride recognition of HIV RNA targets

Abstract

Noncoding RNAs are increasingly promising drug targets yet ligand design is hindered by a paucity of methods that reveal driving factors in selective small molecule : RNA interactions, particularly given the difficulties of high-resolution structural characterization. HIV RNAs are excellent model systems for method development given their targeting history, known structure–function relationships, and the unmet need for more effective treatments. Herein we report a strategy combining synthetic diversification, profiling against multiple RNA targets, and predictive cheminformatic analysis to identify driving factors for selectivity and affinity of small molecules for distinct HIV RNA targets. Using this strategy, we discovered improved ligands for multiple targets and the first ligands for ESSV, an exonic splicing silencer critical to replication. Computational analysis revealed guiding principles for future designs and a predictive cheminformatics model of small molecule : RNA binding. These methods are expected to facilitate progress toward selective targeting of disease-causing RNAs.