The regulation of cell signalling is governed by protein conformational changes that enable distinct binding partners to engage key regulators under different signalling conditions. The anti-inflammatory protein A20 exemplifies this principle: it modulates multiple signalling pathways through its dual roles as a deubiquitinase and ubiquitin ligase. However, the presence of extensive intrinsically disordered and flexible regions within A20 has hindered structural investigations into its conformational dynamics. The advent of the AlphaFold artificial intelligence system—which predicts three-dimensional protein structures from amino acid sequences with near-experimental accuracy—has transformed structural biology. In particular, the recent AlphaFold-Multimer v2.3 extension, capable of modelling protein complexes, provides an unprecedented opportunity to systematically explore conformational changes and interaction specificity. Leveraging this advance, we developed an AlphaFold-Multimer–based pipeline to score and evaluate A20’s putative protein–protein interfaces, enabling prediction of potential conformational switches arising from mutually exclusive interactions. By analysing over 90 candidate interaction partners, we identified previously uncharacterised binding interfaces and signal-dependent conformational switches that may underlie A20’s role as a central hub in inflammatory signalling networks. This framework is broadly applicable and offers a generalizable strategy for dissecting the structural logic of signalling regulation across diverse proteins.