Scaling Functional Annotation Across Proteomes, Pangenomes and Metagenomes with Sma3s v3

High-throughput sequencing has generated protein datasets whose scale increasingly exceeds the practical limits of conventional functional annotation workflows. We present Sma3s v3, a scalable reimplementation of the Sma3s three-step annotation strategy, which combines transfer from highly similar homologs, orthology-based inference, and functional enrichment among homologous proteins. Sma3s v3 replaces BLAST-based searches with MMseqs2 and introduces parallel processing, reusable SQLite caches, taxonomic filtering, and traceable outputs that retain the evidence underlying each assignment. We evaluated the method on a Vibrio cholerae pangenome comprising 50,415 gene clusters from 11,295 quality-filtered genomes and on a metagenomic catalogue containing 843,935 proteins. After excluding non-informative assignments, Sma3s v3 annotated 30,662 pangenome clusters (60.8%), comparable to InterProScan (60.2%) and exceeding eggNOG-mapper (41.4%), while providing 5,747 annotations not recovered by either comparator. Gene Ontology comparisons showed broad semantic agreement between methods, with Sma3s v3 frequently contributing more non-redundant information in Molecular Function and Biological Process. Within the pangenome, annotation coverage reached 97.1% for core clusters and approximately 59% for accessory and unique clusters. Exact protein matches to non-Vibrio genera identified 1,838 candidate horizontally transferred clusters enriched in genetic mobility, antimicrobial resistance, and metal tolerance functions. In the metagenomic catalogue, Sma3s v3 annotated 728,014 proteins (86.3%), compared with 616,895 (73.1%) using InterProScan 2026, and recovered approximately 20,000 unique functional terms. These results establish Sma3s v3 as a scalable and interpretable tool for functional annotation and re-annotation of proteomes, pangenomes, and metagenomic protein catalogues.