查看文章

Identification of RNA–small molecule binding sites plays an essential role in RNA-targeted drug discovery and development. These small molecules are expected to be leading compounds to guide the development of new types of RNA-targeted therapeutics compared with regular therapeutics targeting proteins. RNAs can provide many potential drug targets with diverse structures and functions. However, up to now, only a few methods have been proposed. Predicting RNA–small molecule binding sites still remains a big challenge. New computational model is required to better extract the features and predict RNA–small molecule binding sites more accurately. In this paper, a deep learning model, RLBind, was proposed to predict RNA–small molecule binding sites from sequence-dependent and structure-dependent properties by combining global RNA sequence channel and local neighbor nucleotides …