Interrogation and validation of the interactome of neuronal Munc18-interacting Mint proteins with AlphaFold2

Abstract

Munc18-interacting proteins (Mints) are multi-domain adaptors that regulate neuronal membrane trafficking, signalling and neurotransmission. Mint1 and Mint2 are highly expressed in the brain and play overlapping roles in the regulation of synaptic vesicle fusion required for neurotransmitter release by interacting with the essential synaptic protein Munc18-1. The mechanism by which Mint1 mediates the interaction of Munc18-1 with Syntaxin1a (Sx1a) to control formation of the fusogenic SNARE complex and facilitate neurotransmission remains unclear. Here, we have studied both the specific interactions of the neuronal Mint proteins with Munc18-1 as well as their wider interactome. Using biochemical and biophysical binding approaches we identify a short acidic [alpha];-helical motif (AHM) within Mint1 and Mint2 that is necessary and sufficient for specific binding to Munc18-1. In silico modelling of this interaction with AlphaFold2 and extensive validation by structure-based mutagenesis in vitro, showed that the AHM in Mint forms an [alpha];-helical structure, binds a conserved surface on Munc18-1 domain3b. Although Munc18-1 can interact with Mint and Sx1a proteins simultaneously we find they have mutually reduced affinities, suggesting an allosteric coupling between the two proteins. Finally, using AlphaFold2 we probed the wider network of interactions governed by the Mint scaffolds, and provide a structural model for their assembly with a variety of known and novel regulatory and cargo proteins including ARF3/ARF4 small GTPases, neurexins, and the AP3 clathrin adaptor complex. Overall, our data provides insights into the diversity of interactions mediated by the Mint family and suggests that Mints may help to control a key trigger point in SNARE complex assembly and vesicle fusion.

PPIscreenML: Structure-based screening for protein-protein interactions using AlphaFold

“…The natural extension of using AF2 and related methods to carry out structure-based screening for protein-protein interactions, naturally, is using these methods to define whole interactomes. Already certain studies have applied these tools either within targeted protein families [42,43] for groups of proteins thought to belong together in large complexes [41,44,45]. Importantly, careful consideration of the statistical measures needed for productively scaling assessments to whole proteomes must complement these studies; for example, this will allow for defining thresholds that ideally balance precision and recall ( Table 1 ), and also ensure that the expected results justify these larger-scale analyses.…”

“…The natural extension of using AF2 and related methods to carry out structure-based screening for protein-protein interactions, naturally, is using these methods to define whole interactomes. Already certain studies have applied these tools either within targeted protein families [42,43] for groups of proteins thought to belong together in large complexes [41,44,45].…”

Selecting genes for analysis using historically contingent progress: from RNA changes to protein-protein interactions

“…Therefore, to constrain the predictions further, we used the ranking scores, which are a combination of interface-predicted template modeling (ipTM) and predicted template modeling scores (pTM): 0.8*ipTM + 0.2*pTM for AlphaFold 2.3 [24] and 0.8*ipTM + 0.2*pTM + 0.5*disorder for AlphaFold 3 [21]. We only considered interactions with a ranking score greater than 0.6, which is relatively high given than ipTM scores as low as ~0.3 can yield true positives [25]. Together, these criteria identified 35 interactions (Fig.…”