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. This journal is © the Owner Societies 2015.

Athi Narayanan Naganathan

Department Of Biotechnology

Soundhararajan Gopi

Nandakumar Rajasekaran

Animesh Singh

EIF4EBP2 PROTEIN, HUMAN

INITIATION FACTOR

chemistry

Human

metabolism

phosphorylation

protein conformation

Protein folding

Thermodynamics

EUKARYOTIC INITIATION FACTORS

Humans

Fulltext

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Physical Chemistry Chemical Physics

How many structurally different microscopic routes are accessible to a protein molecule while folding? This has been a challenging question to address experimentally as single-molecule studies are constrained by the limited number of observed folding events while ensemble measurements, by definition, report only an average and not the distribution of the quantity under study. Atomistic simulations, on the other hand, are restricted by sampling and the inability to reproduce thermodynamic observables directly. We overcome these bottlenecks in the current work and provide a quantitative description of folding pathway heterogeneity by developing a comprehensive, scalable and yet experimentally consistent approach combining concepts from statistical mechanics, physical kinetics and graph theory. We quantify the folding pathway heterogeneity of five single-domain proteins under two thermodynamic conditions from an analysis of 100.000 folding events generated from a statistical mechanical model incorporating the detailed energetics from more than a million conformational states. The resulting microstate energetics predicts the results of protein engineering experiments, the thermodynamic stabilities of secondary-structure segments from NMR studies, and the end-to-end distance estimates from single-molecule force spectroscopy measurements. We find that a minimum of ∼3-200 microscopic routes, with a diverse ensemble of transition-path structures, are required to account for the total folding flux across the five proteins and the thermodynamic conditions. The partitioning of flux amongst the numerous pathways is shown to be subtly dependent on the experimental conditions that modulate protein stability, topological complexity and the structural resolution at which the folding events are observed. Our predictive methodology thus reveals the presence of rich ensembles of folding mechanisms that are generally invisible in experiments, reconciles the contradictory observations from experiments and simulations and provides an experimentally consistent avenue to quantify folding heterogeneity. © 2017 the Owner Societies.

Toward a quantitative description of microscopic pathway heterogeneity in protein folding

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 ∼2N 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. © 2016 American Chemical Society.

Journal of Physical Chemistry B

Quantifying Protein Disorder through Measures of Excess Conformational Entropy

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. © the Owner Societies 2015.

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

High-resolution experiments on several apparently two-state proteins point to the existence of partially structured excited- or intermediate-states in dynamic equilibrium with native states. Are these intermediate states the byproducts of functional constraints that are by necessity evolutionarily conserved or are they merely the hidden imprints of evolutionary processes? To investigate this, we characterize the folding of Barstar that has a rich history of complex conformational behavior employing a combination of methods-statistical-mechanical model, electrostatic calculations, MD simulations and multiple-sequence alignment-that provide a detailed yet consistent view of its landscape in agreement with experiments. We find that the multistate folding in Barstar is the direct consequence of a strong evolutionary pressure to maintain its binding affinity with Barnase through a large negative electrostatic potential on one face. A single mutation (E76K or E80K) at the binding site is shown to not only enhance the native-state stability but also alter the Barstar folding mechanism to resemble an unfrustrated two-state-like system. Our results argue that though natural proteins are expected to be minimally frustrated, functional constraints can singularly determine the folding mechanism even if it occurs at the expense of frustrated multistate folding. (Graph Presented). © 2014 American Chemical Society.

Are protein folding intermediates the evolutionary consequence of functional constraints?

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. © 2014 American Chemical Society.

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

Engineering the conformational stabilities of proteins through mutations has immense potential in biotechnological applications. It is, however, an inherently challenging problem given the weak noncovalent nature of the stabilizing interactions. In this regard, we present here a robust and fast strategy to engineer protein stabilities through mutations involving charged residues using a structure-based statistical mechanical model that accounts for the ensemble nature of folding. We validate the method by predicting the absolute changes in stability for 138 experimental mutations from 16 different proteins and enzymes with a correlation of 0.65 and importantly with a success rate of 81%. Multiple point mutants are predicted with a higher success rate (90%) that is validated further by comparing meosphile-thermophile protein pairs. In parallel, we devise a methodology to rapidly engineer mutations in silico which we benchmark against experimental mutations of ubiquitin (correlation of 0.95) and check for its feasibility on a larger therapeutic protein DNase I. We expect the method to be of importance as a first and rapid step to screen for protein mutants with specific stability in the biotechnology industry, in the construction of stability maps at the residue level (i.e., hot spots), and as a robust tool to probe for mutations that enhance the stability of protein-based drugs. © 2013 American Chemical Society.

A rapid, ensemble and free energy based method for engineering protein stabilities

The stability of the repeat protein IκBα, a transcriptional inhibitor in mammalian cells, is critical in the functioning of the NF-κB signaling module implicated in an array of cellular processes, including cell growth, disease, immunity and apoptosis. Structurally, IκBα is complex, with both ordered and disordered regions, thus posing a challenge to the available computational protocols to model its conformational behavior. Here, we introduce a simple procedure to model disorder in systems that undergo binding-induced folding that involves modulation of the contact map guided by equilibrium experimental observables in combination with an Ising-like Wako-Saitô-Muñoz-Eaton model. This one-step procedure alone is able to reproduce a variety of experimental observables, including ensemble thermodynamics (scanning calorimetry, pre-transitions, m-values) and kinetics (roll-over in chevron plot, intermediates and their identity), and is consistent with hydrogen-deuterium exchange measurements. We further capture the intricate distance-dynamics between the domains as measured by single-molecule FRET by combining the model predictions with simple polymer physics arguments. Our results reveal a unique mechanism at work in IκBα folding, wherein disorder in one domain initiates a domino-like effect partially destabilizing neighboring domains, thus highlighting the effect of symmetry-breaking at the level of primary sequences. The offshoot is a multi-state and a dynamic conformational landscape that is populated by increasingly partially folded ensembles upon destabilization. Our results provide, in a straightforward fashion, a rationale to the promiscuous binding and short intracellular half-life of IκBα evolutionarily engineered into it through repeats with variable stabilities and expand the functional repertoire of disordered regions in proteins. © 2013 Sivanandan, Naganathan.

Journal	Data powered by TypesetPhysical Chemistry Chemical Physics
Publisher	Data powered by TypesetRoyal Society of Chemistry
ISSN	14639076
Open Access	No