Convergent evolution, the independent emergence of similar traits, is increasingly recognized as a pervasive force shaping molecular and metabolic diversity. A striking manifestation of convergence at the molecular level is represented by non-homologous isofunctional enzymes (NISE), distinct proteins with no detectable common ancestry that catalyze identical biochemical reactions. Despite their conceptual and practical relevance, NISE are often treated as exceptional cases, and no large-scale, systematically curated resource has been available to explore their distribution and properties across all domains of life. Here we present a curated dataset of homologous and non-homologous isofunctional enzymes (HISE and NISE) derived from UniProtKB release 2025₀1, encompassing both reviewed (Swiss-Prot) and unreviewed (TrEMBL) entries. Using Enzyme Commission (EC) numbers to define catalytic equivalence and SUPERFAMILY (SCOP structure superfamily) annotations to infer evolutionary relationships, we implemented a transparent and reproducible pipeline to classify enzymes into homologous and non-homologous functional groups. The dataset comprises over 200, 000 Swiss-Prot and 27 million TrEMBL enzymes with complete EC and SUPERFAMILY annotations, organized by domain of life, enzyme class, and structural domain composition. Multiple output files, including presence/absence matrices, clustered enzyme groups, phyloprofiles, and full annotation tables, are provided to facilitate downstream evolutionary, functional, and comparative analyses. This resource offers a global view of molecular convergence and divergence in enzymatic functions, highlighting the widespread nature of NISE across taxa and enzyme classes. It provides a foundation for studying metabolic evolution, functional redundancy, drug target discovery, and the evolutionary constraints shaping biochemical solutions.
Oliveira et al. (Tue,) studied this question.