Misassigned Mg2+ ions are pervasive in RNA structural databases, obscuring mechanistic interpretation, undermining comparative analyses, and compromising machine-learning training sets. Here, we present CatWiz, a Coot-integrated, stereochemistry-guided toolkit that facilitates the localization, diagnosis, correction, and annotation of Mg2+ binding sites. CatWiz comprises three modules: MGdiagnosis, which validates and regularizes existing assignments; MGdetect, which identifies unmodeled ion binding sites; and MGclamp, which classifies recurrent Mg2+ clamp motifs. CatWiz also includes a complete binding site annotation system. The stereochemical principles implemented in CatWiz were derived from an earlier analysis of the 1. 55 Å resolution Escherichia coli ribosome and from surveys of the Cambridge Structural Database (CSD). These principles provide a robust experimental foundation for characterizing Mg2+ binding sites. Applications to ribosomes, hammerhead ribozymes, group I introns, and quaternary RNA assemblies demonstrate that CatWiz rapidly locates overlooked ions, corrects misassignments, and improves stereochemical fidelity in hours rather than days. Beyond refinement, CatWiz generates curated data that can seed diverse machine learning and artificial intelligence (AI) models. This transparent, cost-effective framework establishes reproducible standards for RNA-ion assignments and will drive progress in the design of RNA 3D architectures through the identification of unique Mg2+-dependent backbone folds. CatWiz, that is based on universal stereochemical principles, applies also to Mg2+ binding sites in proteins and related biomolecular systems.
Naleem et al. (Thu,) studied this question.