Cross-phyla protein annotation by structural prediction and alignment

<p><strong>Background:</strong> Protein annotation is a major goal in molecular biology, yet experimentally determined knowledge is&nbsp;typically limited to a few model organisms. In non-model species, the sequence-based prediction of&nbsp;gene orthology can be used to infer protein identity, however this approach loses predictive power&nbsp;at longer evolutionary distances. Here we propose a workflow for protein annotation using structural&nbsp;similarity, exploiting the fact that similar protein structures often reflect homology and are more&nbsp;conserved than protein sequences.</p> <p><strong>Results:</strong>&nbsp;&nbsp;We propose a workflow of openly available tools for the functional annotation of proteins via&nbsp;structural similarity (MorF: <strong>Mor</strong>pholog<strong>F</strong>inder) and use it to annotate the complete&nbsp;proteome of a sponge. Sponges are highly relevant for inferring the early history of animals, yet&nbsp;their proteomes remain sparsely annotated. MorF accurately predicts the functions of proteins with&nbsp;known homology in &gt;90%&nbsp;cases, and annotates an additional 50%&nbsp;of the proteome beyond&nbsp;standard sequence-based methods. We uncover new functions for sponge cell types, including extensive&nbsp;FGF, TGF and Ephrin signalling in sponge epithelia, and redox metabolism and control in&nbsp;myopeptidocytes. Notably, we also annotate genes specific to the enigmatic sponge mesocytes,&nbsp;proposing they function to digest cell walls.</p> <p><strong>Conclusions:</strong> Our work demonstrates that structural similarity is a powerful approach that complements and extends sequence similarity searches to identify homologous proteins over long evolutionary distances. We anticipate this to be a powerful approach that boosts discovery in numerous -omics datasets, especially for non-model organisms.</p>