Physical Chemistry of the Protein Backbone: Enabling the Mechanisms of Intrinsic Protein Disorder

Abstract

Over the last two decades it has become clear that well-defined structure is not a requisite for proteins to properly function. Rather, spectra of functionally competent, structurally disordered states have been uncovered requiring canonical paradigms in molecular biology to be revisited or reimagined. It is enticing and oftentimes practical to divide the proteome into structured and unstructured, or disordered, proteins. While function, composition, and structural properties largely differ, these two classes of protein are built upon the same scaffold, namely, the protein backbone. The versatile physicochemical properties of the protein backbone must accommodate structural disorder, order, and transitions between these states. In this review, we survey these properties through the conceptual lenses of solubility and conformational populations and in the context of protein-disorder mediated phenomena (e.g., phase separation, order-disorder transitions, allostery). Particular attention is paid to the results of computational studies, which, through thermodynamic decomposition and dissection of molecular interactions, can provide valuable mechanistic insight and testable hypotheses to guide further solution experiments. Lastly, we discuss changes in the dynamics of side chains and order-disorder transitions of the protein backbone as two modes or realizations of "entropic reservoirs" capable of tuning coupled thermodynamic processes.

Figure 1.

Free energy landscape of a well-structured protein (left) and an IDR (right). The ordinate represents the conformational free energy and the abscissa as some hypothetical, structural reaction coordinate. The free energy landscape for a well-structured protein (A) is often depicted as a rugged funnel (one reaction coordinate) with folding driven down the funnel to a stable conformation with a global, energetic minima. The free energy landscape of an IDR (B) is comparatively flat and rugged with smaller energetic barriers between conformational populations, permitting IDRs to interconvert between them. We have highlighted three hypothetical conformational states, numbered i = 1–3, and their associated probabilities as P_i. The fraction of conformers populating each state is given by eqs 1 and 2. Ligand binding or changes in the environment, for example, can remodel the free energy landscape of an IDR (C) and reapportion the conformational populations enabling the propagation of an allosteric signal through the disordered ensemble.

Figure 2.

Thermodynamic cycle often used in solubility calculations using a saturated solution reference.

Figure 3.

Collapse and aggregation of polypeptides and IDRs as analogous, solubility driven events. (Top) The effective, local concentration of residues increases with chain length in a manner analogous to the increasing total number of molecules (global concentration) in solution (bottom). Despite the fact that solvation free energies of IDRs may be favorable and decrease with chain length, at some local or global concentration intrapeptide interactions (dashed, red lines) saturate to drive collapse or aggregation.

Figure 4.

Population-based view of the relationship between modulation of the structural ensemble of disordered proteins and conformational entropy. Figure originally appeared in Heller et al. and reproduced here under the terms of Creative Commons CC-BY license and with permission from the author. In that article, the red line represented an apo-ensemble or population while blue represented a structural ensemble modulated or redistributed as a result of small-molecule binding. Here, we conceptually generalize the notions of entropic expansion, shift, and collapse to be the result of any process as means to couple the thermodynamics (i.e., entropy) associated with IDR structural transitions. Reprinted with permission from ref 110. Copyright 2018 Elsevier.

Figure 5.

Binding free energy (blue) and diverse conformational entropy signatures (red) for 28 protein–ligand complexes. Side chain conformational entropies were estimated using the NMR-based entropy meter approach.^, The figure was recreated from supplemental data tables in Caro et al. and corresponds to Figure 2 in that article.

Figure 6.

Illustration of the entropic reservoir concept as mediated by changes in the structural fluctuations or dynamics of protein side chains (sc) (top) and backbone (bb) (bottom). These regulatory modes are expected to couple significantly to thermodynamic processes through conformational entropy changes of the solute. However, it is important to note that the effects of conformational fluctuations will also propagate to solute–solvent, solvent–solvent, and solvent–solvent interaction energies and structural network of the solvent.