Sequence-Based Prediction of Fuzzy Protein Interactions

J Mol Biol. 2020 Mar 27;432(7):2289-2303. doi: 10.1016/j.jmb.2020.02.017. Epub 2020 Feb 27.


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 ( 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.

Keywords: disordered proteins; folding upon binding; fuzzy complexes; fuzzy interactions; protein binding.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Amino Acid Sequence
  • Databases, Protein*
  • Fuzzy Logic*
  • Humans
  • Intrinsically Disordered Proteins / chemistry
  • Intrinsically Disordered Proteins / metabolism*
  • Models, Molecular
  • Protein Binding
  • Protein Conformation
  • Protein Domains
  • Protein Folding
  • Protein Interaction Domains and Motifs*
  • Sequence Analysis, Protein / methods*
  • Sequence Homology


  • Intrinsically Disordered Proteins