Single-molecule dynamics reveals cooperative binding-folding in protein recognition

The study of associations between two biomolecules is the key to understanding molecular function and recognition. Molecular function is often thought to be determined by underlying structures. Here, combining a single-molecule study of protein binding with an energy-landscape–inspired microscopic model, we found strong evidence that biomolecular recognition is determined by flexibilities in addition to structures. Our model is based on coarse-grained molecular dynamics on the residue level with the energy function biased toward the native binding structure (the Go model). With our model, the underlying free-energy landscape of the binding can be explored. There are two distinct conformational states at the free-energy minimum, one with partial folding of CBD itself and significant interface binding of CBD to Cdc42, and the other with native folding of CBD itself and native interface binding of CBD to Cdc42. This shows that the binding process proceeds with a significant interface binding of CBD with Cdc42 first, without a complete folding of CBD itself, and that binding and folding are then coupled to reach the native binding state. The single-molecule experimental finding of dynamic fluctuations among the loosely and closely bound conformational states can be identified with the theoretical, calculated free-energy minimum and explained quantitatively in the model as a result of binding associated with large conformational changes. The theoretical predictions identified certain key residues for binding that were consistent with mutational experiments. The combined study identified fundamental mechanisms and provided insights about designing and further exploring biomolecular recognition with large conformational changes.     

How maltose influences structural changes to bind to maltose‐binding protein: Results from umbrella sampling simulation

A well‐studied periplasmic‐binding protein involved in the abstraction of maltose is maltose‐binding protein (MBP), which undergoes a ligand‐induced conformational transition from an open (ligand‐free) to a closed (ligand‐bound) state. Umbrella sampling simulations have been us to estimate the free energy of binding of maltose to MBP and to trace the potential of mean force of the unbinding event using the center‐of‐mass distance between the protein and ligand as the reaction coordinate. The free energy thus obtained compares nicely with the experimentally measured value justifying our theoretical basis. Measurement of the domain angle (N‐terminal‐domain – hinge – C‐terminal‐domain) along the unbinding pathway established the existence of three different states. Starting from a closed state, the protein shifts to an open conformation during the initial unbinding event of the ligand then resides in a semi‐open conformation and later resides predominantly in an open‐state. These transitions along the ligand unbinding pathway have been captured in greater depth using principal component analysis. It is proposed that in mixed‐model, both conformational selection and an induced‐fit mechanism combine to the ligand recognition process in MBP. Proteins 2013. © 2012 Wiley Periodicals, Inc.     

Modulation of effector affinity by hinge region mutations also modulates switching activity in an engineered allosteric TEM1 beta-lactamase switch

RG13 is an engineered allosteric beta-lactamase (BLA) for which maltose is a positive effector. RG13 is a hybrid protein between TEM1 BLA and maltose-binding protein (MBP). Maltose binding to MBP is known to convert the open form of the protein to the closed form through conformational changes about the hinge region. We have constructed and genetically selected several variants of RG13 modified in the hinge region of the MBP domain and explored their effect on beta-lactam hydrolysis, maltose affinity and maltose-induced switching. Hinge mutations that increased maltose affinity the most (and thus presumably close the apo-MBP domain the most) also abrogated switching the most. We provide evidence for a model of RG13 switching in which there exists a threshold conformation between the open to closed form of the MBP domain that divides states that catalyze beta-lactam hydrolysis with different relative rates of acylation and deacylation.     

Mapping the Dynamics Landscape of Conformational Transitions in Enzyme: The Adenylate Kinase Case

Conformational transition describes the essential dynamics and mechanism of enzymes in pursuing their various functions. The fundamental and practical challenge to researchers is to quantitatively describe the roles of large-scale dynamic transitions for regulating the catalytic processes. In this study, we tackled this challenge by exploring the pathways and free energy landscape of conformational changes in adenylate kinase (AdK), a key ubiquitous enzyme for cellular energy homeostasis. Using explicit long-timescale (up to microseconds) molecular dynamics and bias-exchange metadynamics simulations, we determined at the atomistic level the intermediate conformational states and mapped the transition pathways of AdK in the presence and absence of ligands. There is clearly chronological operation of the functional domains of AdK. Specifically in the ligand-free AdK, there is no significant energy barrier in the free energy landscape separating the open and closed states. Instead there are multiple intermediate conformational states, which facilitate the rapid transitions of AdK. In the ligand-bound AdK, the closed conformation is energetically most favored with a large energy barrier to open it up, and the conformational population prefers to shift to the closed form coupled with transitions. The results suggest a perspective for a hybrid of conformational selection and induced fit operations of ligand binding to AdK. These observations, depicted in the most comprehensive and quantitative way to date, to our knowledge, emphasize the underlying intrinsic dynamics of AdK and reveal the sophisticated conformational transitions of AdK in fulfilling its enzymatic functions. The developed methodology can also apply to other proteins and biomolecular systems.     

Multi-scaled explorations of binding-induced folding of intrinsically disordered protein inhibitor IA3 to its target enzyme

Biomolecular function is realized by recognition, and increasing evidence shows that recognition is determined not only by structure but also by flexibility and dynamics. We explored a biomolecular recognition process that involves a major conformational change - protein folding. In particular, we explore the binding-induced folding of IA3, an intrinsically disordered protein that blocks the active site cleft of the yeast aspartic proteinase saccharopepsin (YPrA) by folding its own N-terminal residues into an amphipathic alpha helix. We developed a multi-scaled approach that explores the underlying mechanism by combining structure-based molecular dynamics simulations at the residue level with a stochastic path method at the atomic level. Both the free energy profile and the associated kinetic paths reveal a common scheme whereby IA3 binds to its target enzyme prior to folding itself into a helix. This theoretical result is consistent with recent time-resolved experiments. Furthermore, exploration of the detailed trajectories reveals the important roles of non-native interactions in the initial binding that occurs prior to IA3 folding. In contrast to the common view that non-native interactions contribute only to the roughness of landscapes and impede binding, the non-native interactions here facilitate binding by reducing significantly the entropic search space in the landscape. The information gained from multi-scaled simulations of the folding of this intrinsically disordered protein in the presence of its binding target may prove useful in the design of novel inhibitors of aspartic proteinases.     

PolyUbiquitin Chain Linkage Topology Selects the Functions from the Underlying Binding Landscape

Ubiquitin (Ub) can generate versatile molecular signals and lead to different celluar fates. The functional poly-valence of Ub is believed to be resulted from its ability to form distinct polymerized chains with eight linkage types. To provide a full picture of ubiquitin code, we explore the binding landscape of two free Ub monomers and also the functional landscapes of of all eight linkage types by theoretical modeling. Remarkably, we found that most of the compact structures of covalently connected dimeric Ub chains (diUbs) pre-exist on the binding landscape. These compact functional states were subsequently validated by corresponding linkage models. This leads to the proposal that the folding architecture of Ub monomer has encoded all functional states into its binding landscape, which is further selected by different topologies of polymeric Ub chains. Moreover, our results revealed that covalent linkage leads to symmetry breaking of interfacial interactions. We further propose that topological constraint not only limits the conformational space for effective switching between functional states, but also selects the local interactions for realizing the corresponding biological function. Therefore, the topological constraint provides a way for breaking the binding symmetry and reaching the functional specificity. The simulation results also provide several predictions that qualitatively and quantitatively consistent with experiments. Importantly, the K48 linkage model successfully predicted intermediate states. The resulting multi-state energy landscape was further employed to reconcile the seemingly contradictory experimental data on the conformational equilibrium of K48-diUb. Our results further suggest that hydrophobic interactions are dominant in the functional landscapes of K6-, K11-, K33- and K48 diUbs, while electrostatic interactions play a more important role in the functional landscapes of K27, K29, K63 and linear linkages.     

Ligand-induced structural changes to maltodextrin-binding protein as studied by solution NMR spectroscopy

Solution NMR studies on the physiologically relevant ligand-free and maltotriose-bound states of maltodextrin-binding protein (MBP) are presented. Together with existing data on MBP in complex with beta-cyclodextrin (non-physiological, inactive ligand), these new results provide valuable information on changes in local structure, dynamics and global fold that occur upon ligand binding to this two-domain protein. By measuring a large number of different one-bond residual dipolar couplings, the domain conformations, critical for biological function, were investigated for all three states of MBP. Structural models of the solution conformation of MBP in a number of different forms were generated from the experimental dipolar coupling data and X-ray crystal structures using a quasi-rigid-body domain orientation algorithm implemented in the structure calculation program CNS. Excellent agreement between relative domain orientations in ligand-free and maltotriose-bound solution conformations and the corresponding crystal structures is observed. These results are in contrast to those obtained for the MBP/beta-cyclodextrin complex where the solution state is found to be approximately 10 degrees more closed than the crystalline state. The present study highlights the utility of residual dipolar couplings for orienting protein domains or macromolecules with respect to each other.     

Coevolution of function and the folding landscape: correlation with density of native contacts

The relationship between the folding landscape and function of evolved proteins is explored by comparison of the folding mechanisms for members of the flavodoxin fold. CheY, Spo0F, and NtrC have unrelated functions and low sequence homology but share an identical topology. Recent coarse-grained simulations show that their folding landscapes are uniquely tuned to properly suit their respective biological functions. Enhanced packing in Spo0F and its limited conformational dynamics compared to CheY or NtrC lead to frustration in its folding landscape. Simulation as well as experimental results correlate with the local density of native contacts for these and a sample of other proteins. In particular, protein regions of low contact density are observed to become structured late in folding; concomitantly, these dynamic regions are often involved in binding or conformational rearrangements of functional importance. These observations help to explain the widespread success of Gomacr;-like coarse-grained models in reproducing protein dynamics.     

A salt-bridge motif involved in ligand binding and large-scale domain motions of the maltose-binding protein

The uptake of nutrients is essential for the survival of bacterial cells. Many specialized systems have evolved, such as the maltose-dependent ABC transport system that transfers oligosaccharides through the cytoplasmic membrane. The maltose/maltodextrin-binding protein (MBP) serves as an initial high-affinity binding component in the periplasm that delivers the bound sugar into the cognate ABC transporter MalFGK(2). We have investigated the domain motions induced by the binding of the ligand maltotriose into the binding cleft using molecular dynamics simulations. We find that MBP is predominantly in the open state without ligand and in the closed state with ligand bound. Oligosaccharide binding induces a closure motion (30.0 degrees rotation), whereas ligand removal leads to domain opening (32.6 degrees rotation) around a well-defined hinge affecting key areas relevant for chemotaxis and transport. Our simulations suggest that a "hook-and-eye" motif is involved in the binding. A salt bridge between Glu-111 and Lys-15 forms that effectively locks the protein-ligand complex in a semiclosed conformation inhibiting any further opening and promoting complete closure. This previously unrecognized feature seems to secure the ligand in the binding site and keeps MBP in the closed conformation and suggests a role in the initial steps of substrate transport.     

Identification and thermodynamic characterization of molten globule states of periplasmic binding proteins

Molten globule-like intermediates have been shown to occur during protein folding and are thought to be involved in protein translocation and membrane insertion. However, the determinants of molten globule stability and the extent of specific packing in molten globules is currently unclear. Using far- and near-UV CD and intrinsic and ANS fluorescence, we show that four periplasmic binding proteins (LBP, LIVBP, MBP, and RBP) form molten globules at acidic pH values ranging from 3.0 to 3.4. Only two of these (LBP and LIVBP) have similar sequences, but all four proteins adopt similar three-dimensional structures. We found that each of the four molten globules binds to its corresponding ligand without conversion to the native state. Ligand binding affinity measured by isothermal titration calorimetry for the molten globule state of LIVBP was found to be comparable to that of the corresponding native state, whereas for LBP, MBP, and RBP, the molten globules bound ligand with approximately 5-30-fold lower affinity than the corresponding native states. All four molten globule states exhibited cooperative thermal unfolding assayed by DSC. Estimated values of DeltaCp of unfolding show that these molten globule states contain 28-67% of buried surface area relative to the native states. The data suggest that molten globules of these periplasmic binding proteins retain a considerable degree of long range order. The ability of these sequentially unrelated proteins to form highly ordered molten globules may be related to their large size as well as an intrinsic property of periplasmic binding protein folds.     

Kinetic partitioning mechanism governs the folding of the third FnIII domain of tenascin-C: evidence at the single-molecule level

Statistical mechanics and molecular dynamics simulations proposed that the folding of proteins can follow multiple parallel pathways on a rugged energy landscape from unfolded state en route to their folded native states. Kinetic partitioning mechanism is one of the possible mechanisms underlying such complex folding dynamics. Here, we use single-molecule atomic force microscopy technique to directly probe the multiplicity of the folding pathways of the third fibronectin type III domain from the extracellular matrix protein tenascin-C (TNfn3). By stretching individual (TNfn3)₈ molecules, we forced TNfn3 domains to undergo mechanical unfolding and refolding cycles, allowing us to directly observe the folding pathways of TNfn3. We found that, after being mechanically unraveled and then relaxed to zero force, TNfn3 follows multiple parallel pathways to fold into their native states. The majority of TNfn3 fold into the native state in a simple two-state fashion, while a small percentage of TNfn3 were found to be trapped into kinetically stable folding intermediate states with well-defined three-dimensional structures. Furthermore, the folding of TNfn3 was also influenced by its neighboring TNfn3 domains. Complex misfolded states of TNfn3 were observed, possibly due to the formation of domain-swapped dimeric structures. Our studies revealed the ruggedness of the folding energy landscape of TNfn3 and provided direct experimental evidence that the folding dynamics of TNfn3 are governed by the kinetic partitioning mechanism. Our results demonstrated the unique capability of single-molecule AFM to probe the folding dynamics of proteins at the single-molecule level.     

On prediction of folding nuclei in globular proteins

The approach described in this paper on the prediction of folding nuclei in globular proteins with known three dimensional structures is based on a search of the lowest saddle points through the barrier separating the unfolded state from the native structure on the free-energy landscape of protein chain. This search is performed by a dynamic programming method. Comparison of theoretical results with experimental data on the folding nuclei of two dozen of proteins shows that our model provides good phi value predictions for proteins whose structures have been determined by X-ray analysis, with a less limited success for proteins whose structures have been determined by NMR techniques only. Consideration of a full ensemble of transition states results in more successful prediction than consideration of only the transition states with the minimal free energy. In conclusion we have predicted the localization of folding nuclei for three dimensional protein structures for which kinetics of folding is studied now but the localization of folding nuclei is still unknown.     

Catalysis of Protein Folding by Chaperones Accelerates Evolutionary Dynamics in Adapting Cell Populations

Although molecular chaperones are essential components of protein homeostatic machinery, their mechanism of action and impact on adaptation and evolutionary dynamics remain controversial. Here we developed a physics-based ab initio multi-scale model of a living cell for population dynamics simulations to elucidate the effect of chaperones on adaptive evolution. The 6-loci genomes of model cells encode model proteins, whose folding and interactions in cellular milieu can be evaluated exactly from their genome sequences. A genotype-phenotype relationship that is based on a simple yet non-trivially postulated protein-protein interaction (PPI) network determines the cell division rate. Model proteins can exist in native and molten globule states and participate in functional and all possible promiscuous non-functional PPIs. We find that an active chaperone mechanism, whereby chaperones directly catalyze protein folding, has a significant impact on the cellular fitness and the rate of evolutionary dynamics, while passive chaperones, which just maintain misfolded proteins in soluble complexes have a negligible effect on the fitness. We find that by partially releasing the constraint on protein stability, active chaperones promote a deeper exploration of sequence space to strengthen functional PPIs, and diminish the non-functional PPIs. A key experimentally testable prediction emerging from our analysis is that down-regulation of chaperones that catalyze protein folding significantly slows down the adaptation dynamics.     

Characterization of low-lying excited states of proteins by high-pressure NMR

Hydrostatic pressure alters the free energy of proteins by a few kJ mol⁻¹, with the amount depending on their partial molar volumes. Because the folded ground state of a protein contains cavities, it is always a state of large partial molar volume. Therefore pressure always destabilises the ground state and increases the population of partially and completely unfolded states. This is a mild and reversible conformational change, which allows the study of excited states under thermodynamic equilibrium conditions. Many of the excited states studied in this way are functionally relevant; they also seem to be very similar to kinetic folding intermediates, thus suggesting that evolution has made use of the ‘natural’ dynamic energy landscape of the protein fold and sculpted it to optimise function. This includes features such as ligand binding, structural change during the catalytic cycle, and dynamic allostery.     

Signal Peptide-rheostat Dynamics Delay Secretory Preprotein Folding

Sec secretory proteins are distinguished from cytoplasmic ones by N-terminal signal peptides with multiple roles during post-translational translocation. They contribute to preprotein targeting to the translocase by slowing down folding, binding receptors and triggering secretion. While signal peptides get cleaved after translocation, mature domains traffic further and/or fold into functional states. How signal peptides delay folding temporarily, to keep mature domains translocation-competent, remains unclear. We previously reported that the foldon landscape of the periplasmic prolyl-peptidyl isomerase is altered by its signal peptide and mature domain features. Here, we reveal that the dynamics of signal peptides and mature domains crosstalk. This involves the signal peptide’s hydrophobic helical core, the short unstructured connector to the mature domain and the flexible rheostat at the mature domain N-terminus. Through this cis mechanism the signal peptide delays the formation of early initial foldons thus altering their hierarchy and delaying mature domain folding. We propose that sequence elements outside a protein’s native core exploit their structural dynamics to influence the folding landscape.     

Probing the kinetics of single molecule protein folding

We propose an approach to integrate the theory, simulations, and experiments in protein-folding kinetics. This is realized by measuring the mean and high-order moments of the first-passage time and its associated distribution. The full kinetics is revealed in the current theoretical framework through these measurements. In the experiments, information about the statistical properties of first-passage times can be obtained from the kinetic folding trajectories of single molecule experiments (for example, fluorescence). Theoretical/simulation and experimental approaches can be directly related. We study in particular the temperature-varying kinetics to probe the underlying structure of the folding energy landscape. At high temperatures, exponential kinetics is observed; there are multiple parallel kinetic paths leading to the native state. At intermediate temperatures, nonexponential kinetics appears, revealing the nature of the distribution of local traps on the landscape and, as a result, discrete kinetic paths emerge. At very low temperatures, exponential kinetics is again observed; the dynamics on the underlying landscape is dominated by a single barrier. The ratio between first-passage-time moments is proposed to be a good variable to quantitatively probe these kinetic changes. The temperature-dependent kinetics is consistent with the strange kinetics found in folding dynamics experiments. The potential applications of the current results to single-molecule protein folding are discussed.     

Using robotics to fold proteins and dock ligands

The problems of protein folding and ligand docking have been explored largely using molecular dynamics or Monte Carlo methods. These methods are very compute intensive because they often explore a much wider range of energies, conformations and time than necessary. In addition, Monte Carlo methods often get trapped in local minima. We initially showed that robotic motion planning permitted one to determine the energy of binding and dissociation of ligands from protein binding sites (Singh et al., 1999). The robotic motion planning method maps complicated three-dimensional conformational states into a much simpler, but higher dimensional space in which conformational rearrangements can be represented as linear paths. The dimensionality of the conformation space is of the same order as the number of degrees of conformational freedom in three-dimensional space. We were able to determine the relative energy of association and dissociation of a ligand to a protein by calculating the energetics of interaction for a few thousand conformational states in the vicinity of the protein and choosing the best path from the roadmap. More recently, we have applied roadmap planning to the problem of protein folding (Apaydin et al., 2002a). We represented multiple conformations of a protein as nodes in a compact graph with the edges representing the probability of moving between neighboring states. Instead of using Monte Carlo simulation to simulate thousands of possible paths through various conformational states, we were able to use Markov methods to calculate the steady state occupancy of each conformation, needing to calculate the energy of each conformation only once. We referred to this Markov method of representing multiple conformations and transitions as stochastic roadmap simulation or SRS. We demonstrated that the distribution of conformational states calculated with exhaustive Monte Carlo simulations asymptotically approached the Markov steady state if the same Boltzman energy distribution was used in both methods. SRS permits one to calculate contributions from all possible paths simultaneously with far fewer energy calculations than Monte Carlo or molecular dynamics methods. The SRS method also permits one to represent multiple unfolded starting states and multiple, near-native, folded states and all possible paths between them simultaneously. The SRS method is also independent of the function used to calculate the energy of the various conformational states. In a paper to be presented at this conference (Apaydin et al., 2002b) we have also applied SRS to ligand docking in which we calculate the dynamics of ligand-protein association and dissociation in the region of various binding sites on a number of proteins. SRS permits us to determine the relative times of association to and dissociation from various catalytic and non-catalytic binding sites on protein surfaces. Instead of just following the best path in a roadmap, we can calculate the contribution of all the possible binding or dissociation paths and their relative probabilities and energies simultaneously.     

Dynamics of protein folding: probing the kinetic network of folding-unfolding transitions with experiment and theory

The problem of spontaneous folding of amino acid chains into highly organized, biologically functional three-dimensional protein structures continues to challenge the modern science. Understanding how proteins fold requires characterization of the underlying energy landscapes as well as the dynamics of the polypeptide chains in all stages of the folding process. In recent years, important advances toward these goals have been achieved owing to the rapidly growing interdisciplinary interest and significant progress in both experimental techniques and theoretical methods. Improvements in the experimental time resolution led to determination of the timescales of the important elementary events in folding, such as formation of secondary structure and tertiary contacts. Sensitive single molecule methods made possible probing the distributions of the unfolded and folded states and following the folding reaction of individual protein molecules. Discovery of proteins that fold in microseconds opened the possibility of atomic-level theoretical simulations of folding and their direct comparisons with experimental data, as well as of direct experimental observation of the barrier-less folding transition. The ultra-fast folding also brought new questions, concerning the intrinsic limits of the folding rates and experimental signatures of barrier-less "downhill" folding. These problems will require novel approaches for even more detailed experimental investigations of the folding dynamics as well as for the analysis of the folding kinetic data. For theoretical simulations of folding, a main challenge is how to extract the relevant information from overwhelmingly detailed atomistic trajectories. New theoretical methods have been devised to allow a systematic approach towards a quantitative analysis of the kinetic network of folding-unfolding transitions between various configuration states of a protein, revealing the transition states and the associated folding pathways at multiple levels, from atomistic to coarse-grained representations. This article is part of a Special Issue entitled: Protein Dynamics: Experimental and Computational Approaches.