Structure-aware machine learning identifies microRNAs operating as Toll-like receptor 7/8 ligands
Martin Raden, Thomas Wallach, Milad Miladi, Yuanyuan Zhai, Christina Krüger, Zoé J. Mossmann, Paul Dembny, Rolf Backofen, Seija Lehnardt
Abstract
experiments on murine microglia, incorporating sequence and intra-molecular structure, as well as inter-molecular homo-dimerization potential of candidate RNAs. The method was applied to analyse all known human miRNAs regarding their potential to induce TLR7/8 signalling and microglia activation. We validated the predicted functional activity of subsets of high- and low-scoring miRNAs experimentally, of which a selection has been linked to Alzheimer's disease. High agreement between predictions and experiments confirms the robustness and power of BrainDead. The results provide new insight into the mechanisms of how miRNAs act as TLR ligands. Eventually, BrainDead implements a generic machine learning methodology for learning and predicting the functions of short RNAs in any context.