Deep learning for protein interactions The use of deep learning has revolutionized the field of protein modeling. Humphreys et al . combined this approach with proteome-wide, coevolution-guided protein interaction identification to conduct a large-scale screen of protein-protein interactions in yeast (see the Perspective by Pereira and Schwede). The authors generated predicted interactions and accurate structures for complexes spanning key biological processes in Saccharomyces cerevisiae . The complexes include larger protein assemblies such as trimers, tetramers, and pentamers and provide insights into biological function. —VV

Increasing evidence suggests that some small open reading frame-encoded polypeptides (SEPs) function in prokaryotic and eukaryotic cellular stress responses.

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