Quantification of Conformational Entropy Unravels Effect of Disordered Flanking Region in Coupled Folding and Binding.
Frederik Friis TheisenLasse StabyFrederik Grønbæk TidemandCharlotte O'SheaAndreas PrestelMartin WillemoësBirthe B KragelundKaren SkriverPublished in: Journal of the American Chemical Society (2021)
Intrinsic disorder (ID) constitutes a new dimension to the protein structure-function relationship. The ability to undergo conformational changes upon binding is a key property of intrinsically disordered proteins and remains challenging to study using conventional methods. A 1994 paper by R. S. Spolar and M. T. Record presented a thermodynamic approach for estimating changes in conformational entropy based on heat capacity changes, allowing quantification of residues folding upon binding. Here, we adapt the method for studies of intrinsically disordered proteins. We integrate additional data to provide a broader experimental foundation for the underlying relations and, based on >500 protein-protein complexes involving disordered proteins, reassess a key relation between polar and nonpolar surface area changes, previously determined using globular protein folding. We demonstrate the improved suitability of the adapted method to studies of the folded αα-hub domain RST from radical-induced cell death 1, whose interactome is characterized by ID. From extensive thermodynamic data, quantifying the conformational entropy changes upon binding, and comparison to the NMR structure, the adapted method improves accuracy for ID-based studies. Furthermore, we apply the method, in conjunction with NMR, to reveal hitherto undetected effects of interaction-motif context. Thus, inclusion of the disordered context of the DREB2A RST-binding motif induces structuring of the binding motif, resulting in major enthalpy-entropy compensation in the interaction interface. This study, also evaluating additional interactions, demonstrates the strength of the ID-adapted Spolar-Record thermodynamic approach for dissection of structural features of ID-based interactions, easily overlooked in traditional studies, and for translation of these into mechanistic knowledge.
Keyphrases
- single molecule
- molecular dynamics simulations
- protein protein
- binding protein
- molecular dynamics
- cell death
- dna binding
- small molecule
- high resolution
- healthcare
- magnetic resonance
- electronic health record
- genome wide
- gene expression
- high glucose
- deep learning
- mass spectrometry
- cell proliferation
- single cell
- dna methylation
- solid state
- diabetic rats
- clinical evaluation