HERCULES: an integrative deep-learning framework for predicting RNA-binding propensity and mutation effects at single-residue resolution

Abstract RNA-binding proteins (RBPs) regulate essential aspects of RNA metabolism, yet accurately identifying RNA-binding domains (RBDs) and quantifying the impact of sequence variation on RNA-binding ability remain challenging. Here, we present HERCULES (Hybrid framEwoRk for RNA-binding domain loCalization and mUtation anaLysis using physicochemical and languagE modelS), a unified sequence-based framework for simultaneous RBD localization, global RNA-binding propensity prediction and mutation effect assessment. HERCULES integrates a fine-tuned protein language model with an explicit residue-level physicochemical module, combining global contextual representations with local mutation-sensitive descriptors. On an independent test set, the HERCULES global score discriminates RBPs from non-RBPs with an AUROC of 0.86. At residue resolution, HERCULES outperforms state-of-the-art sequence-based predictors in identifying canonical, non-canonical and putative RBDs across Pfam-annotated proteins. Using a curated dataset of experimentally validated RNA-binding–disrupting mutations, HERCULES correctly classifies 87% of deleterious variants, including single–amino acid substitutions. Evaluation on experimentally resolved protein–RNA complexes further demonstrates robust residue-level performance and improved generalization when contact annotations are augmented with AlphaFold3-predicted complexes. By unifying domain localization and mutation sensitivity within a single sequence-only framework, HERCULES provides a mechanistically interpretable approach for studying RNA–protein interactions. HERCULES is freely available at https://tools.tartaglialab.com/hercules and as an open-source Python package at https://github.com/tartaglialabIIT/hercules.git. Competing Interest Statement The authors have declared no competing interest. Data availability All datasets generated and analyzed in this study are provided as Supplementary Tables. HERCULES is freely available as an open-source Python package at https://github.com/tartaglialabIIT/hercules and through a public web server at https://tools.tartaglialab.com/hercules.