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SUMMARY Structural prediction by artificial intelligence can be powerful new instruments to discover novel protein–protein interactions, but the community still grapples with the implementation, opportunities and limitations. Here, we discuss and re‐analyse our in silico screen for novel pathogen‐secreted inhibitors of immune hydrolases to illustrate the power and limitations of structural predictions. We discuss strategies of curating sequences, including controls, and reusing sequence alignments and highlight important limitations caused by different platforms, sequence depth and computing times. We hope these experiences will support similar interactomic screens by the research community. [ABSTRACT FROM AUTHOR]

RNA-binding proteins (RBPs) play a crucial role in regulating RNA function and fate. However, the full complement of RBPs has only recently begun to be uncovered through proteome-wide approaches such as RNA interactome capture (RIC). RIC has been applied to various cell lines and organisms, including plants, greatly expanding the repertoire of RBPs. However, several technical challenges have limited the efficacy of RIC when applied to plant tissues. Here, we report an improved version of RIC that overcomes the difficulties imposed by leaf tissue. Using this improved RIC method in Arabidopsis leaves, we identified 717 RBPs, generating a deep RNA-binding proteome for leaf tissues. While 75% of these RBPs can be linked to RNA biology, the remaining 25% were previously not known to interact with RNA. Interestingly, we observed that a large number of proteins related to photosynthesis associate with RNA in vivo, including proteins from the four major photosynthetic supercomplexes. As has previously been reported for mammals, a large proportion of leaf RBPs lack known RNA-binding domains, suggesting unconventional modes of RNA binding. We anticipate that this improved RIC method will provide critical insights into RNA metabolism in plants, including how cellular RBPs respond to environmental, physiological and pathological cues. [ABSTRACT FROM AUTHOR]