FANTASIA leverages language models to decode the functional dark proteome across the animal tree of life - Gemma I. Martínez-Redondo; Francisco M. Perez-Canales; Belén Carbonetto; José M. Fernández; Israel Barrios-Núñez; Marçal Vázquez-Valls; Ildefonso Cases; Ana M. Rojas; Rosa Fernández (Communications Biology)
Abstract Protein functional annotation is crucial in biology, but many protein-coding genes remain uncharacterized, especially in non-model organisms. FANTASIA (Functional ANnoTAtion based on embedding space SImilArity) integrates protein language models for large-scale functional annotation. Applied to ~1000 animal proteomes, FANTASIA predicts functions to virtually all proteins, including up to 50% that remained unannotated by traditional homology-based methods. This enables the discovery of novel gene functions, enhancing our understanding of molecular evolution and organismal biology. FANTASIA holds particular promise for functional discovery in non-model taxa, offering advantages over homology-based tools in sensitivity and generalizability. FANTASIA is available on GitHub at https://github.com/CBBIO/FANTASIA .