Abstract
Interactions between disordered proteins involve a wide range of changes in the structure and dynamics of the partners involved. These changes can be classified in terms of binding modes, which include disorder-to-order (DO) transitions, when proteins fold upon binding, as well as disorder-to-disorder (DD) transitions, when the conformational heterogeneity is maintained in the bound states. Furthermore, systematic studies of these interactions are revealing that proteins may exhibit different binding modes with different partners. Proteins that exhibit this context-dependent binding can be referred to as fuzzy proteins. Here we investigate amino acid code for fuzzy binding in terms of the entropy of the probability distribution of transitions towards decreasing order. We implement these entropy calculations into the FuzPred (http://protdyn-fuzpred.org) algorithm to predict the range of context-dependent binding modes of proteins from their amino acid sequences. As we illustrate through a variety of examples, this method identifies those binding sites that are sensitive to the cellular context or post-translational modifications, and may serve as regulatory points of cellular pathways.
Highlights
With the advent of fast sequencing methods there has been an explosion in the number of proteins of known amino acid sequence
Great advances have been made in the last several decades in deciphering how the behavior of proteins is encoded in their amino acid sequences
A variety of sequence-based prediction methods have been developed to estimate a wide range of properties of proteins, including secondary structure propensity, native state structures, preference for being disordered and tendency to aggregate
Summary
With the advent of fast sequencing methods there has been an explosion in the number of proteins of known amino acid sequence. Great advances have been made in this area, with several methods introduced in the last two decades [1,2,3,4] Another major recent advance in molecular biology has been the discovery of disordered proteins, which do not fold into well-defined three-dimensional structures but remain conformationally heterogeneous in their native states [5, 6]. This discovery has further promoted the development of sequence-based prediction methods to facilitate the study of the properties of these proteins. More recently it has been realised that the presence of multiple modes, or fuzziness, in protein interactions is required for liquid-liquid phase separation [15, 16]
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