Locating RNA tertiary structures

RNA molecules tend to form intricate tertiary structures that determine their function and potentially serve as ligand binding sites, opening avenues for RNA-targeted drug therapies. Unlike proteins, only limited amount of known sequenced RNA molecules have annotated tertiary structures, hindering the development of deep learning structure prediction tools (such as AlphaFold) for RNA. To bridge the gap, we aim to develop an ML-based solution to predict locations of tertiary contacts between pairs of residues of an RNA molecule, which would facilitate the discovery of promising regions of sequenced RNA in-silico.