Deep Learning-based structure modelling illuminates structure and function in uncharted regions of β-solenoid fold space

Abstract

Repeat proteins are common in all domains of life and exhibit a wide range of functions. One class of repeat protein contains solenoid folds where the repeating unit consists of β-strands separated by tight turns. β-solenoids have distinguishing structural features such as handedness, twist, oligomerisation state, coil shape and size which give rise to their diversity. Characterised β-solenoid repeat proteins are known to form regions in bacterial and viral virulence factors, antifreeze proteins and functional amyloids. For many of these proteins, the experimental structure has not been solved, as they are difficult to crystallise or model. Here we use various deep learning-based structure-modelling methods to discover novel predicted β-solenoids, perform structural database searches to mine further structural neighbours and relate their predicted structure to possible functions. We find both eukaryotic and prokaryotic adhesins, confirming a known functional linkage between adhesin function and the β-solenoid fold. We further identify exceptionally long, flat β-solenoid folds as possible structures of mucin tandem repeat regions and unprecedentedly small β-solenoid structures. Additionally, we characterise a novel β-solenoid coil shape, the FapC Greek key β-solenoid as well as plausible complexes between it and other proteins involved in Pseudomonas functional amyloid fibres.