Sequence-Based Prediction of Fuzzy Protein Interactions.
Journal:
Journal of molecular biology
PMID:
32112804
Abstract
It is becoming increasingly recognised that disordered proteins may be fuzzy, in that they can exhibit a wide variety of binding modes. In addition to the well-known process of folding upon binding (disorder-to-order transition), many examples are emerging of interacting proteins that remain disordered in their bound states (disorder-to-disorder transitions). Furthermore, disordered proteins may populate ordered and disordered states to different extents depending on their partners (context-dependent binding). Here we assemble three datasets comprising disorder-to-order, context-dependent, and disorder-to-disorder transitions of 828 protein regions represented in 2157 complexes and elucidate the sequence-determinants of the different interaction modes. We found that fuzzy interactions originate from local sequence compositions that promote the sampling of a wide range of different structures. Based on this observation, we developed the FuzPred method (http://protdyn-fuzpred.org) of predicting the binding modes of disordered proteins based on their amino acid sequences, without specifying their partners. We thus illustrate how the amino acid sequences of proteins can encode a wide range of conformational changes upon binding, including transitions from disordered to ordered and from disordered to disordered states.