Quantifying Protein Disorder through Measures of Excess Conformational Entropy

Conflicting Interfacial Electrostatic Interactions as a Design Principle to Modulate Long-Range Interdomain Communication

The extent and molecular basis of interdomain communication in multidomain proteins, central to understanding allostery and function, is an open question. One simple evolutionary strategy could involve the selection of either conflicting or favorable electrostatic interactions across the interface of two closely spaced domains to tune the magnitude of interdomain connectivity. Here, we study a bilobed domain FF34 from the eukaryotic p190A RhoGAP protein to explore one such design principle that mediates interdomain communication. We find that while the individual structural units in wild-type FF34 are marginally coupled, they exhibit distinct intrinsic stabilities and low cooperativity, manifesting as slow folding. The FF3-FF4 interface harbors a frustrated network of highly conserved electrostatic interactions-a charge troika-that promotes the population of multiple, decoupled, and non-native structural modes on a rugged native landscape. Perturbing this network via a charge-reversal mutation not only enhances stability and cooperativity but also dampens the fluctuations globally and speeds up the folding rate by at least an order of magnitude. Our work highlights how a conserved but nonoptimal network of interfacial electrostatic interactions shapes the native ensemble of a bilobed protein, a feature that could be exploited in designing molecular systems with long-range connectivity and enhanced cooperativity.

Thermodynamic architecture and conformational plasticity of GPCRs

G-protein-coupled receptors (GPCRs) are ubiquitous integral membrane proteins involved in diverse cellular signaling processes. Here, we carry out a large-scale ensemble thermodynamic study of 45 ligand-free GPCRs employing a structure-based statistical mechanical framework. We find that multiple partially structured states co-exist in the GPCR native ensemble, with the TM helices 1, 6 and 7 displaying varied folding status, and shaping the conformational landscape. Strongly coupled residues are anisotropically distributed, accounting for only 13% of the residues, illustrating that a large number of residues are inherently dynamic. Active-state GPCRs are characterized by reduced conformational heterogeneity with altered coupling-patterns distributed throughout the structural scaffold. In silico alanine-scanning mutagenesis reveals that extra- and intra-cellular faces of GPCRs are coupled thermodynamically, highlighting an exquisite structural specialization and the fluid nature of the intramolecular interaction network. The ensemble-based perturbation methodology presented here lays the foundation for understanding allosteric mechanisms and the effects of disease-causing mutations in GCPRs.

Phosphorylation of Thr9 Affects the Folding Landscape of the N-Terminal Segment of Human AGT Enhancing Protein Aggregation of Disease-Causing Mutants

The mutations G170R and I244T are the most common disease cause in primary hyperoxaluria type I (PH1). These mutations cause the misfolding of the AGT protein in the minor allele AGT-LM that contains the P11L polymorphism, which may affect the folding of the N-terminal segment (NTT-AGT). The NTT-AGT is phosphorylated at T9, although the role of this event in PH1 is unknown. In this work, phosphorylation of T9 was mimicked by introducing the T9E mutation in the NTT-AGT peptide and the full-length protein. The NTT-AGT conformational landscape was studied by circular dichroism, NMR, and statistical mechanical methods. Functional and stability effects on the full-length AGT protein were characterized by spectroscopic methods. The T9E and P11L mutations together reshaped the conformational landscape of the isolated NTT-AGT peptide by stabilizing ordered conformations. In the context of the full-length AGT protein, the T9E mutation had no effect on the overall AGT function or conformation, but enhanced aggregation of the minor allele (LM) protein and synergized with the mutations G170R and I244T. Our findings indicate that phosphorylation of T9 may affect the conformation of the NTT-AGT and synergize with PH1-causing mutations to promote aggregation in a genotype-specific manner. Phosphorylation should be considered a novel regulatory mechanism in PH1 pathogenesis.

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.

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. STATEMENT: The 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.

E-Volve: understanding the impact of mutations in SARS-CoV-2 variants spike protein on antibodies and ACE2 affinity through patterns of chemical interactions at protein interfaces

Background

The SARS-CoV-2 pandemic reverberated, posing health and social hygiene obstacles throughout the globe. Mutant lineages of the virus have concerned scientists because of convergent amino acid alterations, mainly on the viral spike protein. Studies have shown that mutants have diminished activity of neutralizing antibodies and enhanced affinity with its human cell receptor, the ACE2 protein.

Methods

Hence, for real-time measuring of the impacts caused by variant strains in such complexes, we implemented E-Volve, a tool designed to model a structure with a list of mutations requested by users and return analyses of the variant protein. As a proof of concept, we scrutinized the spike-antibody and spike-ACE2 complexes formed in the variants of concern, B.1.1.7 (Alpha), B.1.351 (Beta), and P.1 (Gamma), by using contact maps depicting the interactions made amid them, along with heat maps to quantify these major interactions.

Results

The results found in this study depict the highly frequent interface changes made by the entire set of mutations, mainly conducted by N501Y and E484K. In the spike-Antibody complex, we have noticed alterations concerning electrostatic surface complementarity, breaching essential sites in the P17 and BD-368-2 antibodies. Alongside, the spike-ACE2 complex has presented new hydrophobic bonds.

Discussion

Molecular dynamics simulations followed by Poisson-Boltzmann calculations corroborate the higher complementarity to the receptor and lower to the antibodies for the K417T/E484K/N501Y (Gamma) mutant compared to the wild-type strain, as pointed by E-Volve, as well as an intensification of this effect by changes at the protein conformational equilibrium in solution. A local disorder of the loop α1'/β1', as well its possible effects on the affinity to the BD-368-2 antibody were also incorporated to the final conclusions after this analysis. Moreover, E-Volve can depict the main alterations in important biological structures, as shown in the SARS-CoV-2 complexes, marking a major step in the real-time tracking of the virus mutant lineages. E-Volve is available at http://bioinfo.dcc.ufmg.br/evolve.

Structural-Energetic Basis for Coupling between Equilibrium Fluctuations and Phosphorylation in a Protein Native Ensemble

The functioning of proteins is intimately tied to their fluctuations in the native ensemble. The structural-energetic features that determine fluctuation amplitudes and hence the shape of the underlying landscape, which in turn determine the magnitude of the functional output, are often confounded by multiple variables. Here, we employ the FF1 domain from human p190A RhoGAP protein as a model system to uncover the molecular basis for phosphorylation of a buried tyrosine, which is crucial to the transcriptional activity associated with transcription factor TFII-I. Combining spectroscopy, calorimetry, statistical-mechanical modeling, molecular simulations, and in vitro phosphorylation assays, we show that the FF1 domain samples a diverse array of conformations in its native ensemble, some of which are phosphorylation-competent. Upon eliminating unfavorable charge-charge interactions through a single charge-reversal (K53E) or charge-neutralizing (K53Q) mutation, we observe proportionately lower phosphorylation extents due to the altered structural coupling, damped equilibrium fluctuations, and a more compact native ensemble. We thus establish a conformational selection mechanism for phosphorylation in the FF1 domain with K53 acting as a "gatekeeper", modulating the solvent exposure of the buried tyrosine. Our work demonstrates the role of unfavorable charge-charge interactions in governing functional events through the modulation of native ensemble characteristics, a feature that could be prevalent in ordered protein domains.

Folding Intermediates, Heterogeneous Native Ensembles and Protein Function

Single domain proteins fold via diverse mechanisms emphasizing the intricate relationship between energetics and structure, which is a direct consequence of functional constraints and demands imposed at the level of sequence. On the other hand, elucidating the interplay between folding mechanisms and function is challenging in large proteins, given the inherent shortcomings in identifying metastable states experimentally and the sampling limitations associated with computational methods. Here, we show that free energy profiles and surfaces of large systems (>150 residues), as predicted by a statistical mechanical model, display a wide array of folding mechanisms with ubiquitous folding intermediates and heterogeneous native ensembles. Importantly, residues around the ligand binding or enzyme active site display a larger tendency to partially unfold and this manifests as intermediates or excited states along the folding coordinate in ligand binding domains, transcription repressors, and representative enzymes from all the six classes, including the SARS-CoV-2 receptor binding domain (RBD) of the spike protein and the protease M^pro. It thus appears that it is relatively easier to distill the imprints of function on the folding landscape of larger proteins as opposed to smaller systems. We discuss how an understanding of energetic-entropic features in ordered proteins can pinpoint specific avenues through which folding mechanisms, populations of partially structured states and function can be engineered.

Combining Ancestral Reconstruction with Folding-Landscape Simulations to Engineer Heterologous Protein Expression

Obligate symbionts typically exhibit high evolutionary rates. Consequently, their proteins may differ considerably from their modern and ancestral homologs in terms of both sequence and properties, thus providing excellent models to study protein evolution. Also, obligate symbionts are challenging to culture in the lab and proteins from uncultured organisms must be produced in heterologous hosts using recombinant DNA technology. Obligate symbionts thus replicate a fundamental scenario of metagenomics studies aimed at the functional characterization and biotechnological exploitation of proteins from the bacteria in soil. Here, we use the thioredoxin from Candidatus Photodesmus katoptron, an uncultured symbiont of flashlight fish, to explore evolutionary and engineering aspects of protein folding in heterologous hosts. The symbiont protein is a standard thioredoxin in terms of 3D-structure, stability and redox activity. However, its folding outside the original host is severely impaired, as shown by a very slow refolding in vitro and an inefficient expression in E. coli that leads mostly to insoluble protein. By contrast, resurrected Precambrian thioredoxins express efficiently in E. coli, plausibly reflecting an ancient adaptation to unassisted folding. We have used a statistical-mechanical model of the folding landscape to guide back-to-ancestor engineering of the symbiont protein. Remarkably, we find that the efficiency of heterologous expression correlates with the in vitro (i.e., unassisted) folding rate and that the ancestral expression efficiency can be achieved with only 1-2 back-to-ancestor replacements. These results demonstrate a minimal-perturbation, sequence-engineering approach to rescue inefficient heterologous expression which may potentially be useful in metagenomics efforts targeting recent adaptations.

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.

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

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

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

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

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

The metal cofactor zinc and interacting membranes modulate SOD1 conformation-aggregation landscape in an in vitro ALS model

Aggregation of Cu-Zn superoxide dismutase (SOD1) is implicated in the motor neuron disease, amyotrophic lateral sclerosis (ALS). Although more than 140 disease mutations of SOD1 are available, their stability or aggregation behaviors in membrane environment are not correlated with disease pathophysiology. Here, we use multiple mutational variants of SOD1 to show that the absence of Zn, and not Cu, significantly impacts membrane attachment of SOD1 through two loop regions facilitating aggregation driven by lipid-induced conformational changes. These loop regions influence both the primary (through Cu intake) and the gain of function (through aggregation) of SOD1 presumably through a shared conformational landscape. Combining experimental and theoretical frameworks using representative ALS disease mutants, we develop a 'co-factor derived membrane association model' wherein mutational stress closer to the Zn (but not to the Cu) pocket is responsible for membrane association-mediated toxic aggregation and survival time scale after ALS diagnosis.

Diverse Native Ensembles Dictate the Differential Functional Responses of Nuclear Receptor Ligand-Binding Domains

Native states of folded proteins are characterized by a large ensemble of conformations whose relative populations and interconversion dynamics determine the functional output. This is more apparent in transcription factors that have evolved to be inherently sensitive to small perturbations, thus fine-tuning gene expression. To explore the extent to which such functional features are imprinted on the folding landscape of transcription factor ligand-binding domains (LBDs), we characterize paralogous LBDs of the nuclear receptor (NR) family employing an energetically detailed and ensemble-based Ising-like statistical mechanical model. We find that the native ensembles of the LBDs from glucocorticoid receptor, PPAγ, and thyroid hormone receptor display a remarkable diversity in the width of the native wells, the number and nature of partially structured states, and hence the degree of conformational order. Monte Carlo simulations employing the full state representation of the ensemble highlight that many of the functional conformations coexist in equilibrium, whose relative populations are sensitive to both temperature and the strength of ligand binding. Allosteric modulation of the degree of structure at a coregulator binding site on ligand binding is shown to arise via a redistribution of populations in the native ensembles of glucocorticoid and PPAγ LBDs. Our results illustrate how functional requirements can drive the evolution of conformationally diverse native ensembles in paralogs.

Slow Folding of a Helical Protein: Large Barriers, Strong Internal Friction, or a Shallow, Bumpy Landscape?

The rate at which a protein molecule folds is determined by opposing energetic and entropic contributions to the free energy that shape the folding landscape. Delineating the extent to which they impact the diffusional barrier-crossing events, including the magnitude of internal friction and barrier height, has largely been a challenging task. In this work, we extract the underlying thermodynamic and dynamic contributions to the folding rate of an unusually slow-folding helical DNA-binding domain, PurR, which shares the characteristics of ultrafast downhill-folding proteins but nonetheless appears to exhibit an apparent two-state equilibrium. We combine equilibrium spectroscopy, temperature-viscosity-dependent kinetics, statistical mechanical modeling, and coarse-grained simulations to show that the conformational behavior of PurR is highly heterogeneous characterized by a large spread in melting temperatures, marginal thermodynamic barriers, and populated partially structured states. PurR appears to be at the threshold of disorder arising from frustrated electrostatics and weak packing that in turn slows down folding due to a shallow, bumpy landscape and not due to large thermodynamic barriers or strong internal friction. Our work highlights how a strong temperature dependence on the pre-exponential could signal a shallow landscape and not necessarily a slow-folding diffusion coefficient, thus determining the folding timescales of even millisecond folding proteins and hints at possible structural origins for the shallow landscape.

A Disordered Loop Mediates Heterogeneous Unfolding of an Ordered Protein by Altering the Native Ensemble

The high flexibility of long disordered or partially structured loops in folded proteins allows for entropic stabilization of native ensembles. Destabilization of such loops could alter the native ensemble or promote alternate conformations within the native ensemble if the ordered regions themselves are held together weakly. This is particularly true of downhill folding systems that exhibit weak unfolding cooperativity. Here, we combine experimental and computational methods to probe the response of the native ensemble of a helical, downhill folding domain PDD, which harbors an 11-residue partially structured loop, to perturbations. Statistical mechanical modeling points to continuous structural changes on both temperature and mutational perturbations driven by entropic stabilization of partially structured conformations within the native ensemble. Long time-scale simulations of the wild-type protein and two mutants showcase a remarkable conformational switching behavior wherein the parallel helices in the wild-type protein sample an antiparallel orientation in the mutants, with the C-terminal helix and the loop connecting the helices displaying high flexibility, disorder, and non-native interactions. We validate these computational predictions via the anomalous fluorescence of a native tyrosine located at the interface of the helices. Our observations highlight the role of long loops in determining the unfolding mechanisms, sensitivity of the native ensembles to mutational perturbations and provide experimentally testable predictions that can be explored in even two-state folding systems.

Non-specific DNA-driven quinary interactions promote structural transitions in proteins

The nature and distribution of charged residues on the surface of proteins play a vital role in determining the binding affinity, selectivity and kinetics of association to ligands. When it comes to DNA-binding domains (DBDs), these functional features manifest as anisotropic distribution of positively charged residues on the protein surface driven by the requirement to bind DNA, a highly negatively charged polymer. In this work, we compare the thermodynamic behavior of nine different proteins belonging to three families - LacR, engrailed and Brk - some of which are disordered in solution in the absence of DNA. Combining detailed electrostatic calculations and statistical mechanical modeling of folding landscapes at different distances and relative orientations with respect to DNA, we show that non-specific electrostatic interactions between the protein and DNA can promote structural transitions in DBDs. Such quinary interactions that are strictly agnostic to the DNA sequence induce varied behaviors including folding of disordered domains, partial unfolding of ordered proteins and (de-)population of intermediate states. Our work highlights that the folding landscape of proteins can be tuned as a function of distance from DNA and hints at possible reasons for DBDs exhibiting complex kinetic-thermodynamic behaviors in the absence of DNA.

Molecular origins of folding rate differences in the thioredoxin family

Thioredoxins are a family of conserved oxidoreductases responsible for maintaining redox balance within cells. They have also served as excellent model systems for protein design and engineering studies particularly through ancestral sequence reconstruction methods. The recent work by Gamiz-Arco et al. [Biochem J (2019) 476, 3631–3647] answers fundamental questions on how specific sequence differences can contribute to differences in folding rates between modern and ancient thioredoxins but also among a selected subset of modern thioredoxins. They surprisingly find that rapid unassisted folding, a feature of ancient thioredoxins, is not conserved in the modern descendants suggestive of co-evolution of better folding machinery that likely enabled the accumulation of mutations that slow-down folding. The work thus provides an interesting take on the expected folding-stability-function constraint while arguing for additional factors that contribute to sequence evolution and hence impact folding efficiency.

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.

Towards a thermodynamic mechanistic model for the effect of temperature on arthropod vector competence for transmission of arboviruses

Arboviruses such as West Nile virus (WNV), bluetongue virus (BTV), dengue virus (DENV) and chikungunya virus (CHIKV) infect their arthropod vectors over a range of average temperatures depending on the ambient temperature. How the transmission efficiency of an arbovirus (i.e. vector competence) varies with temperature influences not only the short term risk of arbovirus outbreaks in humans and livestock but also the long term impact of climate change on the geographical range of the virus. The strength of the interaction between viral surface (glyco)protein (GP) and the host cell receptor (Cr) on binding of virus to host cell is defined by the thermodynamic dissociation constant K_{d_receptor} which is assumed to equal 10^-3 M (at 37 °C) for binding of a sialic acid (SA) on the arthropod midgut epithelial cell surface to a SA-binding site on the surface of BTV, for example. Here virus binding affinity is modelled with increasing number of GP/Cr contacts at temperatures from 10 °C to 35 °C taking into account the change in entropy on immobilization of the whole virus on binding (ΔS_{a_immob}). Based on published data, three thermodynamic GP/Cr binding scenarios, namely enthalpy-driven, entropy-assisted and entropy-driven, are shown to affect the temperature sensitivity of virus binding in different ways. Thus for enthalpy-driven GP/Cr binding, viruses bind host cells much more strongly at 10 °C than 35 °C. A mechanistic model is developed for the number of arthropod midgut cells with bound virus and by building in a kinetic component for the rate of arbovirus replication and subsequent spread to the arthropod salivary glands, a model for the effect of temperature on vector competence is developed. The model separates the opposing effects of temperature on midgut cell binding affinity from the kinetic component of virogenesis. It successfully accommodates both increases in vector competence with temperature as for DENV and WNV in mosquitoes and decreases as for the CHIKV 2010-1909 strain in various populations of Aedes albopictus mosquitoes. Enhanced cell binding at lower temperatures through enthalpy-driven GP/Cr binding compensates for the lower replication rate to some degree such that some transmission can still occur at lower temperatures. In contrast, the strength of entropy-driven GP/Cr binding diminishes at low temperatures although there is no minimum temperature threshold for transmission efficiency. The magnitude of ΔS_{a_immob} is an important data gap. It is concluded that thermodynamic and kinetic data obtained at the molecular level will prove important in modelling vector competence with temperature.

Tunable order-disorder continuum in protein-DNA interactions

DNA-binding protein domains (DBDs) sample diverse conformations in equilibrium facilitating the search and recognition of specific sites on DNA over millions of energetically degenerate competing sites. We hypothesize that DBDs have co-evolved to sense and exploit the strong electric potential from the array of negatively charged phosphate groups on DNA. We test our hypothesis by employing the intrinsically disordered DBD of cytidine repressor (CytR) as a model system. CytR displays a graded increase in structure, stability and folding rate on increasing the osmolarity of the solution that mimics the non-specific screening by DNA phosphates. Electrostatic calculations and an Ising-like statistical mechanical model predict that CytR exhibits features of an electric potential sensor modulating its dimensions and landscape in a unique distance-dependent manner, while DNA plays the role of a non-specific macromolecular chaperone. Accordingly, CytR binds its natural half-site faster than the diffusion-controlled limit and even random DNA conforming to an electrostatic-steering binding mechanism. Our work unravels for the first time the synergistic features of a natural electrostatic potential sensor, a novel binding mechanism driven by electrostatic frustration and disorder, and the role of DNA in promoting distance-dependent protein structural transitions critical for switching between specific and non-specific DNA-binding modes.

Engineering Order and Cooperativity in a Disordered Protein

Structural disorder in proteins arises from a complex interplay between weak hydrophobicity and unfavorable electrostatic interactions. The extent to which the hydrophobic effect contributes to the unique and compact native state of proteins is, however, confounded by large compensation between multiple entropic and energetic terms. Here we show that protein structural order and cooperativity arise as emergent properties upon hydrophobic substitutions in a disordered system with non-intuitive effects on folding and function. Aided by sequence-structure analysis, equilibrium, and kinetic spectroscopic studies, we engineer two hydrophobic mutations in the disordered DNA-binding domain of CytR that act synergistically, but not in isolation, to promote structure, compactness, and stability. The double mutant, with properties of a fully ordered domain, exhibits weak cooperativity with a complex and rugged conformational landscape. The mutant, however, binds cognate DNA with an affinity only marginally higher than that of the wild type, though nontrivial differences are observed in the binding to noncognate DNA. Our work provides direct experimental evidence of the dominant role of non-additive hydrophobic effects in shaping the molecular evolution of order in disordered proteins and vice versa, which could be generalized to even folded proteins with implications for protein design and functional manipulation.

Switching Protein Conformational Substates by Protonation and Mutation

Protein modules that regulate the availability and conformational status of transcription factors determine the rapidity, duration, and magnitude of cellular response to changing conditions. One such system is the single-gene product Cnu, a four-helix bundle transcription co-repressor, which acts as a molecular thermosensor regulating the expression of virulence genes in enterobacteriaceae through modulation of its native conformational ensemble. Cnu and related genes have also been implicated in pH-dependent expression of virulence genes. We hypothesize that protonation of a conserved buried histidine (H45) in Cnu promotes large electrostatic frustration, thus disturbing the H-NS, a transcription factor, binding face. Spectroscopic and calorimetric methods reveal that H45 exhibits a suppressed p K_a of ∼5.1, the protonation of which switches the conformation to an alternate native ensemble in which the fourth helix is disordered. The population redistribution can also be achieved through a mutation H45V, which does not display any switching behavior at pH values greater than 4. The Wako-Saitô-Muñoz-Eaton (WSME) statistical mechanical model predicts specific differences in the conformations and fluctuations of the fourth and first helices of Cnu determining the observed pH response. We validate these predictions through fluorescence lifetime measurements of a sole tryptophan, highlighting the presence of both native and non-native interactions in the regions adjoining the binding face of Cnu. Our combined experimental-computational study thus shows that Cnu acts both as a thermo- and pH-sensor orchestrated via a subtle but quantifiable balance between the weak packing of a structural element and protonation of a buried histidine that promotes electrostatic frustration.

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.

Using thermodynamic parameters to calibrate a mechanistic dose-response for infection of a host by a virus

Assessing the risk of infection from emerging viruses or of existing viruses jumping the species barrier into novel hosts is limited by the lack of dose response data. The initial stages of the infection of a host by a virus involve a series of specific contact interactions between molecules in the host and on the virus surface. The strength of the interaction is quantified in the literature by the dissociation constant (K_d) which is determined experimentally and is specific for a given virus molecule/host molecule combination. Here, two stages of the initial infection process of host intestinal cells are modelled, namely escape of the virus in the oral challenge dose from the innate host defenses (e.g. mucin proteins in mucus) and the subsequent binding of any surviving virus to receptor molecules on the surface of the host epithelial cells. The strength of virus binding to host cells and to mucins may be quantified by the association constants, K_a and K_mucin, respectively. Here, a mechanistic dose-response model for the probability of infection of a host by a given virus dose is constructed using K_a and K_mucin which may be derived from published K_d values taking into account the number of specific molecular interactions. It is shown that the effectiveness of the mucus barrier is determined not only by the amount of mucin but also by the magnitude of K_mucin. At very high K_mucin values, slight excesses of mucin over virus are sufficient to remove all the virus according to the model. At lower K_mucin values, high numbers of virus may escape even with large excesses of mucin. The output from the mechanistic model is the probability (p₁) of infection by a single virion which is the parameter used in conventional dose-response models to predict the risk of infection of the host from the ingested dose. It is shown here how differences in K_a (due to molecular differences in an emerging virus strain or new host) affect p₁, and how these differences in K_a may be quantified in terms of two thermodynamic parameters, namely enthalpy and entropy. This provides the theoretical link between sequencing data and risk of infection. Lack of data on entropy is a limitation at present and may also affect our interpretation of K_d in terms of infectivity. It is concluded that thermodynamic approaches have a major contribution to make in developing dose-response models for emerging viruses.

Intrinsic Disorder in a Well-Folded Globular Protein

The folded structure of the heterodimeric sweet protein monellin mimics single-chain proteins with topology β1-α1-β2-β3-β4-β5 (chain A: β3-β4-β5; chain B: β1-α1-β2). Furthermore, like naturally occurring single-chain proteins of a similar size, monellin folds cooperatively with no detectable intermediates. However, the two monellin chains, A and B, are marginally structured in isolation and fold only upon binding to each other. Thus, monellin presents a unique opportunity to understand the design of intrinsically disordered proteins that fold upon binding. Here, we study the folding of a single-chain variant of monellin (scMn) using simulations of an all heavy-atom structure-based model. These simulations can explain mechanistic details derived from scMn experiments performed using several different structural probes. scMn folds cooperatively in our structure-based simulations, as is also seen in experiments. We find that structure formation near the transition-state ensemble of scMn is not uniformly distributed but is localized to a hairpin-like structure which contains one strand from each chain (β2, β3). Thus, the sequence and the underlying energetics of heterodimeric monellin promote the early formation of the interchain interface (β2-β3). By studying computational scMn mutants whose "interchain" interactions are deleted, we infer that this energy distribution allows the two protein chains to remain largely disordered when this interface is not folded. From these results, we suggest that cutting the protein backbone of a globular protein between residues which lie within its folding nucleus may be one way to construct two disordered fragments which fold upon binding.

A self-consistent structural perturbation approach for determining the magnitude and extent of allosteric coupling in proteins

Elucidating the extent of energetic coupling between residues in single-domain proteins, which is a fundamental determinant of allostery, information transfer and folding cooperativity, has remained a grand challenge. While several sequence- and structure-based approaches have been proposed, a self-consistent description that is simultaneously compatible with unfolding thermodynamics is lacking. We recently developed a simple structural perturbation protocol that captures the changes in thermodynamic stabilities induced by point mutations within the protein interior. Here, we show that a fundamental residue-specific component of this perturbation approach, the coupling distance, is uniquely sensitive to the environment of a residue in the protein to a distance of ∼15 Å. With just the protein contact map as an input, we reproduce the extent of percolation of perturbations within the structure as observed in network analysis of intra-protein interactions, molecular dynamics simulations and NMR-observed changes in chemical shifts. Using this rapid protocol that relies on a single structure, we explain the results of statistical coupling analysis (SCA) that requires hundreds of sequences to identify functionally critical sectors, the propagation and dissipation of perturbations within proteins and the higher-order couplings deduced from detailed NMR experiments. Our results thus shed light on the possible mechanistic origins of signaling through the interaction network within proteins, the likely distance dependence of perturbations induced by ligands and post-translational modifications and the origins of folding cooperativity through many-body interactions.

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.