Effects of Molecular Crowding on the Dynamics of Intrinsically Disordered Proteins

Inside cells, the concentration of macromolecules can reach up to 400 g/L. In such crowded environments, proteins are expected to behave differently than in vitro. It has been shown that the stability and the folding rate of a globular protein can be altered by the excluded volume effect produced by a high density of macromolecules. However, macromolecular crowding effects on intrinsically disordered proteins (IDPs) are less explored. These proteins can be extremely dynamic and potentially sample a wide ensemble of conformations under non-denaturing conditions. The dynamic properties of IDPs are intimately related to the timescale of conformational exchange within the ensemble, which govern target recognition and how these proteins function. In this work, we investigated the macromolecular crowding effects on the dynamics of several IDPs by measuring the NMR spin relaxation parameters of three disordered proteins (ProTα, TC1, and α-synuclein) with different extents of residual structures. To aid the interpretation of experimental results, we also performed an MD simulation of ProTα. Based on the MD analysis, a simple model to correlate the observed changes in relaxation rates to the alteration in protein motions under crowding conditions was proposed. Our results show that 1) IDPs remain at least partially disordered despite the presence of high concentration of other macromolecules, 2) the crowded environment has differential effects on the conformational propensity of distinct regions of an IDP, which may lead to selective stabilization of certain target-binding motifs, and 3) the segmental motions of IDPs on the nanosecond timescale are retained under crowded conditions. These findings strongly suggest that IDPs function as dynamic structural ensembles in cellular environments.     

The free energy folding penalty accompanying binding of intrinsically disordered α‐helical motifs

Intrinsically disordered proteins (IDPs) are abundant in eukaryotic proteomes and preform critical roles in many cellular processes, most often through the association with globular proteins. Despite lacking a stable three‐dimensional structure by themselves, they may acquire a defined conformation upon binding globular targets. The most common type of secondary structure acquired by these binding motifs entails formation of an α‐helix. It has been hypothesized that such disorder‐to‐order transitions are associated with a significant free energy penalty due to IDP folding, which reduces the overall IDP‐target affinity. However, the exact magnitude of IDP folding penalty in α‐helical binding motifs has not been systematically estimated. Here, we report the folding penalty contributions for 30 IDPs undergoing folding‐upon‐binding and find that the average IDP folding penalty is +2.0 kcal/mol and ranges from 0.7 to 3.5 kcal/mol. We observe that the folding penalty scales approximately linearly with the change in IDP helicity upon binding, which provides a simple empirical way to estimate folding penalty. We analyze to what extent do pre‐structuring and target‐bound IDP dynamics (fuzziness) reduce the folding penalty and find that these effects combined, on average, reduce the folding cost by around half. Taken together, the presented analysis provides a quantitative basis for understanding the role of folding penalty in IDP‐target interactions and introduces a method estimate this quantity. Estimation and reduction of IDP folding penalty may prove useful in the rational design of helix‐stabilized inhibitors of IDP‐target interactions.StatementThe α‐helical binding motifs are ubiquitous among the intrinsically disordered proteins (IDPs). Upon binding their targets, they undergo a disorder‐to‐order transition, which is accompanied by a significant folding penalty whose magnitude is generally not known. Here, we use recently developed statistical‐thermodynamic model to estimate the folding penalties for 30 IDPs and clarify the roles of IDP pre‐folding and bound‐state dynamics in reducing the folding penalty.     

Towards the physical basis of how intrinsic disorder mediates protein function

Intrinsically disordered proteins (IDPs) are an important class of functional proteins that is highly prevalent in biology and has broad association with human diseases. In contrast to structured proteins, free IDPs exist as heterogeneous and dynamical conformational ensembles under physiological conditions. Many concepts have been discussed on how such intrinsic disorder may provide crucial functional advantages, particularly in cellular signaling and regulation. Establishing the physical basis of these proposed phenomena requires not only detailed characterization of the disordered conformational ensembles, but also mechanistic understanding of the roles of various ensemble properties in IDP interaction and regulation. Here, we review the experimental and computational approaches that may be integrated to address many important challenges of establishing a "structural" basis of IDP function, and discuss some of the key emerging ideas on how the conformational ensembles of IDPs may mediate function, especially in coupled binding and folding interactions.     

The Conformational Ensembles of α-Synuclein and Tau: Combining Single-Molecule FRET and Simulations

Intrinsically disordered proteins (IDPs) are increasingly recognized for their important roles in a range of biological contexts, both in normal physiological function and in a variety of devastating human diseases. However, their structural characterization by traditional biophysical methods, for the purposes of understanding their function and dysfunction, has proved challenging. Here, we investigate the model IDPs α-Synuclein (αS) and tau, that are involved in major neurodegenerative conditions including Parkinson’s and Alzheimer’s diseases, using excluded volume Monte Carlo simulations constrained by pairwise distance distributions from single-molecule fluorescence measurements. Using this, to our knowledge, novel approach we find that a relatively small number of intermolecular distance constraints are sufficient to accurately determine the dimensions and polymer conformational statistics of αS and tau in solution. Moreover, this method can detect local changes in αS and tau conformations that correlate with enhanced aggregation. Constrained Monte Carlo simulations produce ensembles that are in excellent agreement both with experimental measurements on αS and tau and with all-atom, explicit solvent molecular dynamics simulations of αS, with much lower configurational sampling requirements and computational expense.Abbreviations used: AAMD, all-atom molecular dynamics; ECMC, experimentally constrained Monte Carlo; ET_eff, energy transfer efficiency; (sm)FRET, (single molecule) Förster resonance energy transfer; IDP, intrinsically disordered protein; LJ, Lennard-Jones; MC, Monte Carlo; MD, molecular dynamics; PRE, paramagnetic relaxation enhancement; SAX(N)S, small-angle x-ray (neutron) scattering; UMC, unconstrained Monte Carlo     

Criticality in the conformational phase transition among self-similar groups in intrinsically disordered proteins: Probed by salt-bridge dynamics

Intrinsically disordered proteins (IDP) serve as one of the key components in the global proteome. In contrast to globular proteins, they harbor an enormous amount of physical flexibility enforcing them to be retained in conformational ensembles rather than stable folds. Previous studies in an aligned direction have revealed the importance of transient dynamical phenomena like that of salt-bridge formation in IDPs to support their physical flexibility and have further highlighted their functional relevance. For this characteristic flexibility, IDPs remain amenable and accessible to different ordered binding partners, supporting their potential multi-functionality. The current study further addresses this complex structure-functional interplay in IDPs using phase transition dynamics to conceptualize the underlying (avalanche type) mechanism of their being distributed across and hopping around degenerate structural states (conformational ensembles). For this purpose, extensive molecular dynamics simulations have been done and the data analyzed from a statistical physics perspective. Investigation of the plausible scope of 'self-organized criticality' (SOC) to fit into the complex dynamics of IDPs was found to be assertive, relating the conformational degeneracy of these proteins to their functional multiplicity. In accordance with the transient nature of 'salt-bridge dynamics', the study further uses it as a probe to explain the structural basis of the proposed criticality in the conformational phase transition among self-similar groups in IDPs. The analysis reveal scale-invariant self-similar fractal geometries in the structural conformations of different IDPs. The insights from the study has the potential to be extended further to benefit structural tinkering of IDPs in their functional characterization and drugging.     

Nullspace Sampling with Holonomic Constraints Reveals Molecular Mechanisms of Protein Gαs

Proteins perform their function or interact with partners by exchanging between conformational substates on a wide range of spatiotemporal scales. Structurally characterizing these exchanges is challenging, both experimentally and computationally. Large, diffusional motions are often on timescales that are difficult to access with molecular dynamics simulations, especially for large proteins and their complexes. The low frequency modes of normal mode analysis (NMA) report on molecular fluctuations associated with biological activity. However, NMA is limited to a second order expansion about a minimum of the potential energy function, which limits opportunities to observe diffusional motions. By contrast, kino-geometric conformational sampling (KGS) permits large perturbations while maintaining the exact geometry of explicit conformational constraints, such as hydrogen bonds. Here, we extend KGS and show that a conformational ensemble of the α subunit Gαs of heterotrimeric stimulatory protein Gs exhibits structural features implicated in its activation pathway. Activation of protein Gs by G protein-coupled receptors (GPCRs) is associated with GDP release and large conformational changes of its α-helical domain. Our method reveals a coupled α-helical domain opening motion while, simultaneously, Gαs helix α₅ samples an activated conformation. These motions are moderated in the activated state. The motion centers on a dynamic hub near the nucleotide-binding site of Gαs, and radiates to helix α₄. We find that comparative NMA-based ensembles underestimate the amplitudes of the motion. Additionally, the ensembles fall short in predicting the accepted direction of the full activation pathway. Taken together, our findings suggest that nullspace sampling with explicit, holonomic constraints yields ensembles that illuminate molecular mechanisms involved in GDP release and protein Gs activation, and further establish conformational coupling between key structural elements of Gαs.     

Atomic-level characterization of disordered protein ensembles

The roles of unfolded states of proteins in normal folding and in diseases involving aggregation, as well as the prevalence and regulatory functions of intrinsically disordered proteins, have become increasingly recognized. The structural representation of these disordered states as ensembles of interconverting conformers can therefore provide critical insights. Experimental methods can be used to probe ensemble-averaged structural properties of disordered states and computational approaches generate representative ensembles of conformers using experimental restraints. In particular, NMR and small-angle X-ray scattering provide quantitative data that can readily be incorporated into calculations. These techniques have gleaned structural information about denatured, unfolded and intrinsically disordered proteins. The use of experimental data in different computational approaches, including ensemble molecular dynamics simulations and algorithms that assign populations to pregenerated conformers, has highlighted the presence of both local and long-range structure, and the occurrence of native-like and non-native interactions in unfolded and denatured states. Analysis of the resulting ensembles has suggested important implications of this fluctuating structure for folding, aggregation and binding.     

Energy Landscapes of Protein Aggregation and Conformation Switching in Intrinsically Disordered Proteins

The protein folding problem was apparently solved recently by the advent of a deep learning method for protein structure prediction called AlphaFold. However, this program is not able to make predictions about the protein folding pathways. Moreover, it only treats about half of the human proteome, as the remaining proteins are intrinsically disordered or contain disordered regions. By definition these proteins differ from natively folded proteins and do not adopt a properly folded structure in solution. However these intrinsically disordered proteins (IDPs) also systematically differ in amino acid composition and uniquely often become folded upon binding to an interaction partner. These factors preclude solving IDP structures by current machine-learning methods like AlphaFold, which also cannot solve the protein aggregation problem, since this meta-folding process can give rise to different aggregate sizes and structures. An alternative computational method is provided by molecular dynamics simulations that already successfully explored the energy landscapes of IDP conformational switching and protein aggregation in multiple cases. These energy landscapes are very different from those of ‘simple’ protein folding, where one energy funnel leads to a unique protein structure. Instead, the energy landscapes of IDP conformational switching and protein aggregation feature a number of minima for different competing low-energy structures. In this review, I discuss the characteristics of these multifunneled energy landscapes in detail, illustrated by molecular dynamics simulations that elucidated the underlying conformational transitions and aggregation processes.     

The Disordered Region of the HCV Protein NS5A: Conformational Dynamics,SH3 Binding,and Phosphorylation

Intrinsically disordered proteins (IDPs) perform their physiological role without possessing a well-defined three-dimensional structure. Still, residual structure and conformational dynamics of IDPs are crucial for the mechanisms underlying their functions. For example, regions of transient secondary structure are often involved in molecular recognition, with the structure being stabilized (or not) upon binding. Long-range interactions, on the other hand, determine the hydrodynamic radius of the IDP, and thus the distance over which the protein can catch binding partners via so-called fly-casting mechanisms. The modulation of long-range interactions also presents a convenient way of fine-tuning the protein’s interaction network, by making binding sites more or less accessible. Here we studied, mainly by nuclear magnetic resonance spectroscopy, residual secondary structure and long-range interactions in nonstructural protein 5A (NS5A) from hepatitis C virus (HCV), a typical viral IDP with multiple functions during the viral life cycle. NS5A comprises an N-terminal folded domain, followed by a large (∼250-residue) disordered C-terminal part. Comparing nuclear magnetic resonance spectra of full-length NS5A with those of a protein construct composed of only the C-terminal residues 191–447 (NS5A-D2D3) allowed us to conclude that there is no significant interaction between the globular and disordered parts of NS5A. NS5A-D2D3, despite its overall high flexibility, shows a large extent of local residual (α-helical and β-turn) structure, as well as a network of electrostatic long-range interactions. Furthermore, we could demonstrate that these long-range interactions become modulated upon binding to the host protein Bin1, as well as after NS5A phosphorylation by CK2. As the charged peptide regions involved in these interactions are well conserved among the different HCV genotypes, these transient long-range interactions may be important for some of the functions of NS5A over the course of the HCV life cycle.     

Src kinase conformational activation: thermodynamics, pathways, and mechanisms

Tyrosine kinases of the Src-family are large allosteric enzymes that play a key role in cellular signaling. Conversion of the kinase from an inactive to an active state is accompanied by substantial structural changes. Here, we construct a coarse-grained model of the catalytic domain incorporating experimental structures for the two stable states, and simulate the dynamics of conformational transitions in kinase activation. We explore the transition energy landscapes by constructing a structural network among clusters of conformations from the simulations. From the structural network, two major ensembles of pathways for the activation are identified. In the first transition pathway, we find a coordinated switching mechanism of interactions among the αC helix, the activation-loop, and the β strands in the N-lobe of the catalytic domain. In a second pathway, the conformational change is coupled to a partial unfolding of the N-lobe region of the catalytic domain. We also characterize the switching mechanism for the αC helix and the activation-loop in detail. Finally, we test the performance of a Markov model and its ability to account for the structural kinetics in the context of Src conformational changes. Taken together, these results provide a broad framework for understanding the main features of the conformational transition taking place upon Src activation.     

Computational modeling suggests binding-induced expansion of Epsin disordered regions upon association with AP2

Intrinsically disordered regions (IDRs) are prevalent in the eukaryotic proteome. Common functional roles of IDRs include forming flexible linkers or undergoing allosteric folding-upon-binding. Recent studies have suggested an additional functional role for IDRs: generating steric pressure on the plasma membrane during endocytosis, via molecular crowding. However, in order to accomplish useful functions, such crowding needs to be regulated in space (e.g., endocytic hotspots) and time (e.g., during vesicle formation). In this work, we explore binding-induced regulation of IDR steric volume. We simulate the IDRs of two proteins from Clathrin-mediated endocytosis (CME) to see if their conformational spaces are regulated via binding-induced expansion. Using Monte-Carlo computational modeling of excluded volumes, we generate large conformational ensembles (3 million) for the IDRs of Epsin and Eps15 and dock the conformers to the alpha subunit of Adaptor Protein 2 (AP2α), their CME binding partner. Our results show that as more molecules of AP2α are bound, the Epsin-derived ensemble shows a significant increase in global dimensions, measured as the radius of Gyration (R_G) and the end-to-end distance (EED). Unlike Epsin, Eps15-derived conformers that permit AP2α binding at one motif were found to be more likely to accommodate binding of AP2α at other motifs, suggesting a tendency toward co-accessibility of binding motifs. Co-accessibility was not observed for any pair of binding motifs in Epsin. Thus, we speculate that the disordered regions of Epsin and Eps15 perform different roles during CME, with accessibility in Eps15 allowing it to act as a recruiter of AP2α molecules, while binding-induced expansion of the Epsin disordered region could impose steric pressure and remodel the plasma membrane during vesicle formation.     

Mapping the Structural and Dynamical Features of Kinesin Motor Domains

Kinesin motor proteins drive intracellular transport by coupling ATP hydrolysis to conformational changes that mediate directed movement along microtubules. Characterizing these distinct conformations and their interconversion mechanism is essential to determining an atomic-level model of kinesin action. Here we report a comprehensive principal component analysis of 114 experimental structures along with the results of conventional and accelerated molecular dynamics simulations that together map the structural dynamics of the kinesin motor domain. All experimental structures were found to reside in one of three distinct conformational clusters (ATP-like, ADP-like and Eg5 inhibitor-bound). These groups differ in the orientation of key functional elements, most notably the microtubule binding α4–α5, loop8 subdomain and α2b-β4-β6-β7 motor domain tip. Group membership was found not to correlate with the nature of the bound nucleotide in a given structure. However, groupings were coincident with distinct neck-linker orientations. Accelerated molecular dynamics simulations of ATP, ADP and nucleotide free Eg5 indicate that all three nucleotide states could sample the major crystallographically observed conformations. Differences in the dynamic coupling of distal sites were also evident. In multiple ATP bound simulations, the neck-linker, loop8 and the α4–α5 subdomain display correlated motions that are absent in ADP bound simulations. Further dissection of these couplings provides evidence for a network of dynamic communication between the active site, microtubule-binding interface and neck-linker via loop7 and loop13. Additional simulations indicate that the mutations G325A and G326A in loop13 reduce the flexibility of these regions and disrupt their couplings. Our combined results indicate that the reported ATP and ADP-like conformations of kinesin are intrinsically accessible regardless of nucleotide state and support a model where neck-linker docking leads to a tighter coupling of the microtubule and nucleotide binding regions. Furthermore, simulations highlight sites critical for large-scale conformational changes and the allosteric coupling between distal functional sites.     

Residual Structure Accelerates Binding of Intrinsically Disordered ACTR by Promoting Efficient Folding upon Encounter

Intrinsically disordered proteins (IDPs) often fold into stable structures upon specific binding. The roles of residual structure of unbound IDPs in coupling binding and folding have been under much debate. While many studies emphasize the importance of conformational flexibility for IDP recognition, it was recently demonstrated that stabilization the N-terminal helix of intrinsically disordered ACTR accelerated its binding to another IDP, NCBD of the CREB-binding protein. To understand how enhancing ACTR helicity accelerates binding, we derived a series of topology-based coarse-grained models that mimicked various ACTR mutants with increasing helical contents and reproduced their NCBD binding affinities. Molecular dynamics simulations were then performed to sample hundreds of reversible coupled binding and folding transitions. The results show that increasing ACTR helicity does not alter the baseline mechanism of synergistic folding, which continues to follow “extended conformational selection” with multiple stages of selection and induced folding. Importantly, these coarse-grained models, while only calibrated based on binding thermodynamics, recapitulate the observed kinetic acceleration with increasing ACTR helicity. However, the residual helices do not enhance the association kinetics via more efficient seeding of productive collisions. Instead, they allow the nonspecific collision complexes to evolve more efficiently into the final bound and folded state, which is the primary source of accelerated association kinetics. Meanwhile, reduced dissociation kinetics with increasing ACTR helicity can be directly attributed to smaller entropic cost of forming the bound state. Altogether, this study provides important mechanistic insights into how residual structure may modulate thermodynamics and kinetics of IDP interactions.     

Understanding the Folding-Function Tradeoff in Proteins

When an amino-acid sequence cannot be optimized for both folding and function, folding can get compromised in favor of function. To understand this tradeoff better, we devise a novel method for extracting the “function-less” folding-motif of a protein fold from a set of structurally similar but functionally diverse proteins. We then obtain the β-trefoil folding-motif, and study its folding using structure-based models and molecular dynamics simulations. CompariA protein sequence serves two purpson with the folding of wild-type β-trefoil proteins shows that function affects folding in two ways: In the slower folding interleukin-1β, binding sites make the fold more complex, increase contact order and slow folding. In the faster folding hisactophilin, residues which could have been part of the folding-motif are used for function. This reduces the density of native contacts in functional regions and increases folding rate. The folding-motif helps identify subtle structural deviations which perturb folding. These may then be used for functional annotation. Further, the folding-motif could potentially be used as a first step in the sequence design of function-less scaffold proteins. Desired function can then be engineered into these scaffolds.     

CIDER: Resources to Analyze Sequence-Ensemble Relationships of Intrinsically Disordered Proteins

Intrinsically disordered proteins and regions (IDPs) represent a large class of proteins that are defined by conformational heterogeneity and lack of persistent tertiary/secondary structure. IDPs play important roles in a range of biological functions, and their dysregulation is central to numerous diseases, including neurodegeneration and cancer. The conformational ensembles of IDPs are encoded by their amino acid sequences. Here, we present two computational tools that are designed to enable rapid and high-throughput analyses of a wide range of physicochemical properties encoded by IDP sequences. The first, CIDER, is a user-friendly webserver that enables rapid analysis of IDP sequences. The second, localCIDER, is a high-performance software package that enables a wide range of analyses relevant to IDP sequences. In addition to introducing the two packages, we demonstrate the utility of these resources using examples where sequence analysis offers biophysical insights.