Small Activating RNAs: A Curated Database and an Overview of Rational Design Principles

RNA activation (RNAa), mediated by small activating RNAs (saRNAs), upregulates endogenous gene expression through recruitment of the Argonaute proteins to the promoter, natural antisense transcripts, or other noncoding RNAs. This mechanistically distinct modality addresses an unmet need, as few RNA therapeutics currently function to activate endogenous gene expression. Three saRNA therapeutics are now in clinical trials; however, broader application remains constrained by largely empirical candidate screening and limited design guidelines, particularly in terms of saRNA targets. Unlike siRNAs, for which extensive sequence-activity relationships and computational design strategies exist, saRNA activity remains comparatively difficult to predict. Here, we assembled an updated and annotated database of publicly available saRNA sequences and paired it with an overview of the RNAa principles, the clinical and preclinical landscape of saRNA utility and current saRNA design guidelines. Finally, we outline opportunities for artificial intelligence-assisted rational design, highlighting how machine learning trained on curated saRNA datasets could accelerate discovery of novel saRNA candidates. Consolidation of saRNA records into a unified resource will hopefully enable systematic analysis of sequence features associated with activity and lay a foundation for moving saRNA design from largely empirical screening toward more rational design.