Energetic and topological determinants of a phosphorylation-induced disorder-to-order protein conformational switch

The Wako-Saitô-Muñoz-Eaton Model for Predicting Protein Folding and Dynamics

Despite the recent advances in the prediction of protein structures by deep neutral networks, the elucidation of protein-folding mechanisms remains challenging. A promising theory for describing protein folding is a coarse-grained statistical mechanical model called the Wako-Saitô-Muñoz-Eaton (WSME) model. The model can calculate the free-energy landscapes of proteins based on a three-dimensional structure with low computational complexity, thereby providing a comprehensive understanding of the folding pathways and the structure and stability of the intermediates and transition states involved in the folding reaction. In this review, we summarize previous and recent studies on protein folding and dynamics performed using the WSME model and discuss future challenges and prospects. The WSME model successfully predicted the folding mechanisms of small single-domain proteins and the effects of amino-acid substitutions on protein stability and folding in a manner that was consistent with experimental results. Furthermore, extended versions of the WSME model were applied to predict the folding mechanisms of multi-domain proteins and the conformational changes associated with protein function. Thus, the WSME model may contribute significantly to solving the protein-folding problem and is expected to be useful for predicting protein folding, stability, and dynamics in basic research and in industrial and medical applications.

A hierarchy of coupling free energies underlie the thermodynamic and functional architecture of protein structures

Protein sequences and structures evolve by satisfying varied physical and biochemical constraints. This multi-level selection is enabled not just by the patterning of amino acids on the sequence, but also via coupling between residues in the native structure. Here, we employ an energetically detailed statistical mechanical model with millions of microstates to extract such long-range structural correlations, i.e. thermodynamic coupling free energies, from a diverse family of protein structures. We find that despite the intricate and anisotropic distribution of coupling patterns, the majority of residues (>70%) are only marginally coupled contributing to functional motions and catalysis. Physical origins of ‘sectors’, determinants of native ensemble heterogeneity in extant, ancient and designed proteins, and the basis for allostery emerge naturally from coupling free energies. The statistical framework highlights how evolutionary selection and optimization occur at the level of global interaction network for a given protein fold impacting folding, function, and allosteric outputs.

•

Evolution of protein structures occurs at the level of global interaction network.

•

More than 70% of the protein residues are weakly or marginally coupled.

•

Functional ‘sector’ regions are a manifestation of marginal coupling.

•

Coupling indices vary across the entire proteins in extant-ancient and natural-designed pairs.

•

The proposed methodology can be used to understand allostery and epistasis.

Investigation of Phosphorylation-Induced Folding of an Intrinsically Disordered Protein by Coarse-Grained Molecular Dynamics

Apart from being the most common mechanism of regulating protein function and transmitting signals throughout the cell, phosphorylation has an ability to induce disorder-to-order transition in an intrinsically disordered protein. In particular, it was shown that folding of the intrinsically disordered protein, eIF4E-binding protein isoform 2 (4E-BP2), can be induced by multisite phosphorylation. Here, the principles that govern the folding of phosphorylated 4E-BP2 (pT37pT46 4E-BP2_18-62) are investigated by analyzing canonical and replica exchange molecular dynamics trajectories, generated with the coarse-grained united-residue force field, in terms of local and global motions and the time dependence of formation of contacts between C^αs of selected pairs of residues. The key residues involved in the folding of the pT37pT46 4E-BP2_18-62 are elucidated by this analysis. The correlations between local and global motions are identified. Moreover, for a better understanding of the physics of the formation of the folded state, the experimental structure of the pT37pT46 4E-BP2_18-62 is analyzed in terms of a kink (heteroclinic standing wave solution) of a generalized discrete nonlinear Schrödinger equation. It is shown that without molecular dynamics simulations the kinks are able to identify not only the phosphorylated sites of protein, the key players in folding, but also the reasons for the weak stability of the pT37pT46 4E-BP2_18-62.

The regulation mechanism of phosphorylation and mutations in intrinsically disordered protein 4E-BP2

Eukaryotic translation initiation factor 4E binding protein 2 (4E-BP2) is an inhibitor of mRNA cap-dependent translations. Wild-type (WT) 4E-BP2 is intrinsically disordered under physiological conditions, while phosphorylation converts the disordered fragments 18-62 into a four-stranded β-sheet structure. The regulation mechanism of phosphorylation on 4E-BP2 still remains ambiguous. In this study, replica-exchange molecular dynamics (REMD) simulations were utilized to sample the conformation spaces of WT, phosphorylated WT (pWT), and phosphorylated mutated (pMT) 4E-BP2. Starting from extended structures, the folded structures were only observed in pWT simulations. The folding pathway shows that the folded structures of pWT are formed in the order of β1/β4, β3, and β2. The formation of β-turns on pWT, which are driven by hydrogen bonds between the phosphorylated residues and adjacent residues, are the rate-limiting steps in the folding process. The long-range electrostatic interactions contribute toward the stabilization of the folded structures. Moreover, the disruption of β-turn structures induced by mutations would prevent the folding of pMT 4E-BP2. Our finding is helpful in understanding the regulation of the structural ensembles of intrinsically disordered proteins.

Multifunnel Energy Landscapes for Phosphorylated Translation Repressor 4E-BP2 and Its Mutants

Upon phosphorylation of specific sites, eukaryotic translation initiation factor 4E (eIF4E) binding protein 2 (4E-BP2) undergoes a fundamental structural transformation from a disordered state to a four-stranded β-sheet, leading to decreased binding affinity for its partner. This change reflects the significant effects of phosphate groups on the underlying energy landscapes of proteins. In this study, we combine high-temperature molecular dynamics simulations and discrete path sampling to construct energy landscapes for a doubly phosphorylated 4E-BP2_18-62 and two mutants (a single site mutant D33K and a double mutant Y54A/L59A). The potential and free energy landscapes for these three systems are multifunneled with the folded state and several alternative states lying close in energy, suggesting perhaps a multifunneled and multifunctional protein. Hydrogen bonds between phosphate groups and other residues not only stabilize these low-lying conformations to different extents but also play an important role in interstate transitions. From the energy landscape perspective, our results explain some interesting experimental observations, including the low stability of doubly phosphorylated 4E-BP2 and its moderate binding to eIF4E and the inability of phosphorylated Y54A/L59A to fold.

Thermodynamics and folding landscapes of large proteins from a statistical mechanical model

Statistical mechanical models that afford an intermediate resolution between macroscopic chemical models and all-atom simulations have been successful in capturing folding behaviors of many small single-domain proteins. However, the applicability of one such successful approach, the Wako-Saitô-Muñoz-Eaton (WSME) model, is limited by the size of the protein as the number of conformations grows exponentially with protein length. In this work, we surmount this size limitation by introducing a novel approximation that treats stretches of 3 or 4 residues as blocks, thus reducing the phase space by nearly three orders of magnitude. The performance of the 'bWSME' model is validated by comparing the predictions for a globular enzyme (RNase H) and a repeat protein (IκBα), against experimental observables and the model without block approximation. Finally, as a proof of concept, we predict the free-energy surface of the 370-residue, multi-domain maltose binding protein and identify an intermediate in good agreement with single-molecule force-spectroscopy measurements. The bWSME model can thus be employed as a quantitative predictive tool to explore the conformational landscapes of large proteins, extract the structural features of putative intermediates, identify parallel folding paths, and thus aid in the interpretation of both ensemble and single-molecule experiments.

From Levinthal's Paradox to the Effects of Cell Environmental Perturbation on Protein Folding

BACKGROUND

The rapidly increasing number of known protein sequences calls for more efficient methods to predict the Three-Dimensional (3D) structures of proteins, thus providing basic knowledge for rational drug design. Understanding the folding mechanism of proteins is valuable for predicting their 3D structures and for designing proteins with new functions and medicinal applications. Levinthal's paradox is that although the astronomical number of conformations possible even for proteins as small as 100 residues cannot be fully sampled, proteins in nature normally fold into the native state within timescales ranging from microseconds to hours. These conflicting results reveal that there are factors in organisms that can assist in protein folding.

METHODS

In this paper, we selected a crowded cell-like environment and temperature, and the top three Posttranslational Modifications (PTMs) as examples to show that Levinthal's paradox does not reflect the folding mechanism of proteins. We then revealed the effects of these factors on protein folding.

RESULTS

The results summarized in this review indicate that a crowded cell-like environment, temperature, and the top three PTMs reshape the Free Energy Landscapes (FELs) of proteins, thereby regulating the folding process. The balance between entropy and enthalpy is the key to understanding the effect of the crowded cell-like environment and PTMs on protein folding. In addition, the stability/flexibility of proteins is regulated by temperature.

CONCLUSION

This paper concludes that the cellular environment could directly intervene in protein folding. The long-term interactions of the cellular environment and sequence evolution may enable proteins to fold efficiently. Therefore, to correctly understand the folding mechanism of proteins, the effect of the cellular environment on protein folding should be considered.

Extracting the Hidden Distributions Underlying the Mean Transition State Structures in Protein Folding

The inherent conflict between noncovalent interactions and the large conformational entropy of the polypeptide chain forces folding reactions and their mechanisms to deviate significantly from chemical reactions. Accordingly, measures of structure in the transition state ensemble (TSE) are strongly influenced by the underlying distributions of microscopic folding pathways that are challenging to discern experimentally. Here, we present a detailed analysis of 150,000 folding transition paths of five proteins at three different thermodynamic conditions from an experimentally consistent statistical mechanical model. We find that the underlying TSE structural distributions are rarely unimodal, and the average experimental measures arise from complex underlying distributions. Unfolding pathways also exhibit subtle differences from folding counterparts due to a combination of Hammond behavior and native-state movements. Local interactions and topological complexity, to a lesser extent, are found to determine pathway heterogeneity, underscoring the importance of the balance between local and nonlocal energetics in protein folding.

Toward a quantitative description of microscopic pathway heterogeneity in protein folding

Experimentally consistent statistical modeling of protein folding thermodynamics reveals unprecedented complexity with numerous parallel folding routes in five different proteins.

Mechanism of Phosphorylation-Induced Folding of 4E-BP2 Revealed by Molecular Dynamics Simulations

Site-specific phosphorylation of an intrinsically disordered protein, eIF4E-binding protein isoform 2 (4E-BP2), can suppress its native function by folding it into a four-stranded β-sheet, but the mechanism of this phosphorylation-induced folding is unclear. In this work, we use all-atom molecular dynamics simulations to investigate both the folded and unfolded states of 4E-BP2 under different phosphorylation states of T37 and T46. The results show that the phosphorylated forms of both T37 and T46 play important roles in stabilizing the folded structure, especially for the β-turns and the sequestered binding motif. The phosphorylated residues not only guide the folding of the protein through several intermediate states but also affect the conformational distribution of the unfolded ensemble. Significantly, the phosphorylated residues can function as nucleation sites for the folding of the protein by forming certain local structures that are stabilized by hydrogen bonding involving the phosphate group. The region around phosphorylated T46 appears to fold before that around phosphorylated T37. These findings provide new insight into the intricate effects of protein phosphorylation.

Quantifying Protein Disorder through Measures of Excess Conformational Entropy

Intrinsically disordered proteins (IDPs) and proteins with a large degree of disorder are abundant in the proteomes of eukaryotes and viruses, and play a vital role in cellular homeostasis and disease. One fundamental question that has been raised on IDPs is the process by which they offset the entropic penalty involved in transitioning from a heterogeneous ensemble of conformations to a much smaller collection of binding-competent states. However, this has been a difficult problem to address, as the effective entropic cost of fixing residues in a folded-like conformation from disordered amino acid neighborhoods is itself not known. Moreover, there are several examples where the sequence complexity of disordered regions is as high as well-folded regions. Disorder in such cases therefore arises from excess conformational entropy determined entirely by correlated sequence effects, an entropic code that is yet to be identified. Here, we explore these issues by exploiting the order-disorder transitions of a helix in Pbx-Homeodomain together with a dual entropy statistical mechanical model to estimate the magnitude and sign of the excess conformational entropy of residues in disordered regions. We find that a mere 2.1-fold increase in the number of allowed conformations per residue (∼0.7kBT favoring the unfolded state) relative to a well-folded sequence, or ∼2(N) additional conformations for a N-residue sequence, is sufficient to promote disorder under physiological conditions. We show that this estimate is quite robust and helps in rationalizing the thermodynamic signatures of disordered regions in important regulatory proteins, modeling the conformational folding-binding landscapes of IDPs, quantifying the stability effects characteristic of disordered protein loops and their subtle roles in determining the partitioning of folding flux in ordered domains. In effect, the dual entropy model we propose provides a statistical thermodynamic basis for the relative conformational propensities of amino acids in folded and disordered environments in proteins. Our work thus lays the foundation for understanding and quantifying protein disorder through measures of excess conformational entropy.