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.

Thermally versus Chemically Denatured Protein States

Protein unfolding thermodynamic parameters are conventionally extracted from equilibrium thermal and chemical denaturation experiments. Despite decades of work, the degree of structure and the compactness of denatured states populated in these experiments are still open questions. Here, building on previous works, we show that thermally and chemically denatured protein states are distinct from the viewpoint of far-ultraviolet circular dichroism experiments that report on the local conformational status of peptide bonds. The differences identified are independent of protein length, structural class, or experimental conditions, highlighting the presence of two sub-ensembles within the denatured states. The sub-ensembles, U_T and U_D for thermally induced and denaturant-induced unfolded states, respectively, can exclusively exchange populations as a function of temperature at high chemical denaturant concentrations. Empirical analysis suggests that chemically denatured states are ∼50% more expanded than the thermally denatured chains of the same protein. Our observations hint that the strength of protein backbone-backbone interactions and identity versus backbone-solvent/co-solvent interactions determine the conformational distributions. We discuss the implications for protein folding mechanisms, the heterogeneity in relaxation rates, and folding diffusion coefficients.

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.

pStab: prediction of stable mutants, unfolding curves, stability maps and protein electrostatic frustration

Summary

We present a web-server for rapid prediction of changes in protein stabilities over a range of temperatures and experimental conditions upon single- or multiple-point substitutions of charged residues. Potential mutants are identified by a charge-shuffling procedure while the stability changes (i.e. an unfolding curve) are predicted employing an ensemble-based statistical-mechanical model. We expect this server to be a simple yet detailed tool for engineering stabilities, identifying electrostatically frustrated residues, generating local stability maps and in constructing fitness landscapes.

Availability and implementation

The web-server is freely available at http://pbl.biotech.iitm.ac.in/pStab and supports recent versions of all major browsers.

Contact

athi@iitm.ac.in.

Supplementary information

Supplementary data are available at Bioinformatics online.

Insight into the specificity and severity of pathogenic mechanisms associated with missense mutations through experimental and structural perturbation analyses

Most pathogenic missense mutations cause specific molecular phenotypes through protein destabilization. However, how protein destabilization is manifested as a given molecular phenotype is not well understood. We develop here a structural and energetic approach to describe mutational effects on specific traits such as function, regulation, stability, subcellular targeting or aggregation propensity. This approach is tested using large-scale experimental and structural perturbation analyses in over thirty mutations in three different proteins (cancer-associated NQO1, transthyretin related with amyloidosis and AGT linked to primary hyperoxaluria type I) and comprising five very common pathogenic mechanisms (loss-of-function and gain-of-toxic function aggregation, enzyme inactivation, protein mistargeting and accelerated degradation). Our results revealed that the magnitude of destabilizing effects and, particularly, their propagation through the structure to promote disease-associated conformational states largely determine the severity and molecular mechanisms of disease-associated missense mutations. Modulation of the structural perturbation at a mutated site is also shown to cause switches between different molecular phenotypes. When very common disease-associated missense mutations were investigated, we also found that they were not among the most deleterious possible missense mutations at those sites, and required additional contributions from codon bias and effects of CpG sites to explain their high frequency in patients. Our work sheds light on the molecular basis of pathogenic mechanisms and genotype–phenotype relationships, with implications for discriminating between pathogenic and neutral changes within human genome variability from whole genome sequencing studies.

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.

A Universal Pattern in the Percolation and Dissipation of Protein Structural Perturbations

Understanding the extent to which information is transmitted through the intramolecular interaction network of proteins upon a perturbation, that is, an allosteric effect, has long remained an unsolved problem. Through an analysis of high-resolution NMR data from the literature on 28 different proteins and 49 structural perturbations, we show that the extent of induced structural changes through mutations and molecular events including protein-protein, protein-peptide, protein-ligand binding, and post-translational modifications exhibit a near-universal exponential functional form. The extent of percolation into the protein structures can be up to 20-25 Å despite no apparent change in the 3D structures. These observations are also consistent with theoretical expectations, elementary graph theoretic analysis of protein structures, detailed molecular dynamics simulations, and experimental double-mutant cycles. Our analysis highlights that most molecular events would contribute to allosteric effects independent of protein structure, topology, or identity and provides a simple avenue to test and potentially model their effects.

Tuning the Continuum of Structural States in the Native Ensemble of a Regulatory Protein

The mesoscale nature of proteins allows for an efficient coupling between environmental cues and conformational changes, enabling their function as molecular transducers. Delineating the precise structural origins of such a connection and the expected spectroscopic response has, however, been challenging. In this work, we perform a combination of urea-temperature double perturbation experiments and theoretical modeling to probe the conformational landscape of Cnu, a natural thermosensor protein. We observe unique ensemble signatures that point to a continuum of conformational substates in the native ensemble and that respond intricately to perturbations upon monitoring secondary and tertiary structures, distances between an intrinsic FRET pair, and hydrodynamic volumes. Binding assays further reveal a weakening of the Cnu functional complex with temperature, highlighting the molecular origins of signal transduction critical for pathogenic response in enterobacteriaceae.

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.

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

We show that the phosphorylation of 4E-BP2 acts as a triggering event to shape its folding-function landscape that is delicately balanced between conflicting favorable energetics and intrinsically unfavorable topological connectivity. We further provide first evidence that the fitness landscapes of proteins at the threshold of disorder can differ considerably from ordered domains.

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.

Imprints of function on the folding landscape: functional role for an intermediate in a conserved eukaryotic binding protein

In the computational characterization of single domain protein folding, the effective free energies of numerous microstates are projected onto few collective degrees of freedom that in turn serve as well-defined reaction coordinates. In this regard, one-dimensional (1D) free energy profiles are widely used mainly for their simplicity. Since folding and functional landscapes are interlinked, how well can these reduced representations capture the structural and dynamic features of functional states while being simultaneously consistent with experimental observables? We investigate this issue by characterizing the folding of the four-helix bundle bovine acyl-CoA binding protein (bACBP), which exhibits complex equilibrium and kinetic behaviours, employing an Ising-like statistical mechanical model and molecular simulations. We show that the features of the 1D free energy profile are sufficient to quantitatively reproduce multiple experimental observations including millisecond chevron-like kinetics and temperature dependence, a microsecond fast phase, barrier heights, unfolded state movements, the intermediate structure and average ϕ-values. Importantly, we find that the structural features of the native-like intermediate (partial disorder in helix 1) are intricately linked to a unique interplay between packing and electrostatics in this domain. By comparison with available experimental data, we propose that this intermediate determines the promiscuous functional behaviour of bACBP that exhibits broad substrate specificity. Our results present evidence to the possibility of employing the statistical mechanical model and the resulting 1D free energy profile to not just understand folding mechanisms but to even extract features of functionally relevant states and their energetic origins.

Folding RaCe: a robust method for predicting changes in protein folding rates upon point mutations

MOTIVATION

Protein engineering methods are commonly employed to decipher the folding mechanism of proteins and enzymes. However, such experiments are exceedingly time and resource intensive. It would therefore be advantageous to develop a simple computational tool to predict changes in folding rates upon mutations. Such a method should be able to rapidly provide the sequence position and chemical nature to modulate through mutation, to effect a particular change in rate. This can be of importance in protein folding, function or mechanistic studies.

RESULTS

We have developed a robust knowledge-based methodology to predict the changes in folding rates upon mutations formulated from amino and acid properties using multiple linear regression approach. We benchmarked this method against an experimental database of 790 point mutations from 26 two-state proteins. Mutants were first classified according to secondary structure, accessible surface area and position along the primary sequence. Three prime amino acid features eliciting the best relationship with folding rates change were then shortlisted for each class along with an optimized window length. We obtained a self-consistent mean absolute error of 0.36 s(-1) and a mean Pearson correlation coefficient (PCC) of 0.81. Jack-knife test resulted in a MAE of 0.42 s(-1) and a PCC of 0.73. Moreover, our method highlights the importance of outlier(s) detection and studying their implications in the folding mechanism.

AVAILABILITY AND IMPLEMENTATION

A web server 'Folding RaCe' has been developed and is available at http://www.iitm.ac.in/bioinfo/proteinfolding/foldingrace.html.

CONTACT

gromiha@iitm.ac.in

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Evidence for the sequential folding mechanism in RNase H from an ensemble-based model

The number of distinct protein folding pathways starting from an unfolded ensemble, and hence, the folding mechanism is an intricate function of protein size, sequence complexity, and stability conditions. This has traditionally been a contentious issue particularly because of the ensemble nature of conventional experiments that can mask the complexity of the underlying folding landscape. Recent hydrogen-exchange experiments combined with mass spectrometry (HX-MS) reveal that the folding of RNase H proceeds in a hierarchical fashion with distinct intermediates and following a single discrete path. In our current work, we provide computational evidence for this unique folding mechanism by employing a structure-based statistical mechanical model. Upon calibrating the energetic terms of the model with equilibrium measurements, we predict multiple intermediate states in the folding of RNase H that closely resemble experimental observations. Remarkably, a simplified landscape representation adequately captures the folding complexity and predicts the possibility of a well-defined sequence of folding events. We supplement the statistical model study with both explicit solvent molecular simulations of the helical units and electrostatic calculations to provide structural and energetic insights into the early and late stages of RNase H folding that hint at the frustrated nature of its folding landscape.