FB2026_02 , released June 18, 2026
FB2026_02 , released June 18, 2026
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Citation
Abakarova, M., Freiberger, M.I., Liehrmann, A., Rera, M., Laine, E. (2026). Proteome-wide prediction of the functional impact of missense variants with ProteoCast.  Nat. Commun. 17(1): 3813.
FlyBase ID
FBrf0265216
Publication Type
Research paper
Abstract
Dissecting the functional impact of genetic mutations is essential to advancing our understanding of genotype-phenotype relationships and identifying therapeutic targets. Despite progress in sequencing and genome editing technologies, proteome-wide mutation effect prediction remains challenging. Here we show that evolutionary information alone enables accurate prediction of mutation effects across entire proteomes. ProteoCast is a scalable and interpretable computational method that leverages protein sequence conservation to classify genetic variants and identify functionally important protein sites. We apply ProteoCast to the complete Drosophila melanogaster proteome (22,000 isoforms, 300 million mutations) and validate it against nearly 400,000 natural and experimental variants. It correctly classifies 85% of known lethal mutations as functionally impactful versus 13-18% of population variants. ProteoCast-guided genome editing experiments confirm these predictions. Moreover, ProteoCast successfully identifies functionally important protein modification sites and binding motifs. ProteoCast provides a publicly available resource and deployable pipeline for studying gene function and mutations in any organism.
PubMed ID
PubMed Central ID
PMC13121731 (PMC) (EuropePMC)
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Secondary IDs
    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    Nat. Commun.
    Title
    Nature communications
    ISBN/ISSN
    2041-1723
    Data From Reference