The influence of intrinsic folding mechanism of an unfolded protein on the coupled folding-binding process during target recognition

Intrinsically disordered proteins (IDPs) are extensively involved in dynamic signaling processes which require a high association rate and a high dissociation rate for rapid binding/unbinding events and at the same time a sufficient high affinity for specific recognition. Although the coupled folding-binding processes of IDPs have been extensively studied, it is still impossible to predict whether an unfolded protein is suitable for molecular signaling via coupled folding-binding. In this work, we studied the interplay between intrinsic folding mechanisms and coupled folding-binding process for unfolded proteins through molecular dynamics simulations. We first studied the folding process of three representative IDPs with different folded structures, that is, c-Myb, AF9, and E3 rRNase. We found the folding free energy landscapes of IDPs are downhill or show low barriers. To further study the influence of intrinsic folding mechanism on the binding process, we modulated the folding mechanism of barnase via circular permutation and simulated the coupled folding-binding process between unfolded barnase permutant and folded barstar. Although folding of barnase was coupled to target binding, the binding kinetics was significantly affected by the intrinsic folding free energy barrier, where reducing the folding free energy barrier enhances binding rate up to two orders of magnitude. This accelerating effect is different from previous results which reflect the effect of structure flexibility on binding kinetics. Our results suggest that coupling the folding of an unfolded protein with no/low folding free energy barrier with its target binding may provide a way to achieve high specificity and rapid binding/unbinding kinetics simultaneously.     

The Universal Statistical Distributions of the Affinity,Equilibrium Constants,Kinetics and Specificity in Biomolecular Recognition

We uncovered the universal statistical laws for the biomolecular recognition/binding process. We quantified the statistical energy landscapes for binding, from which we can characterize the distributions of the binding free energy (affinity), the equilibrium constants, the kinetics and the specificity by exploring the different ligands binding with a particular receptor. The results of the analytical studies are confirmed by the microscopic flexible docking simulations. The distribution of binding affinity is Gaussian around the mean and becomes exponential near the tail. The equilibrium constants of the binding follow a log-normal distribution around the mean and a power law distribution in the tail. The intrinsic specificity for biomolecular recognition measures the degree of discrimination of native versus non-native binding and the optimization of which becomes the maximization of the ratio of the free energy gap between the native state and the average of non-native states versus the roughness measured by the variance of the free energy landscape around its mean. The intrinsic specificity obeys a Gaussian distribution near the mean and an exponential distribution near the tail. Furthermore, the kinetics of binding follows a log-normal distribution near the mean and a power law distribution at the tail. Our study provides new insights into the statistical nature of thermodynamics, kinetics and function from different ligands binding with a specific receptor or equivalently specific ligand binding with different receptors. The elucidation of distributions of the kinetics and free energy has guiding roles in studying biomolecular recognition and function through small-molecule evolution and chemical genetics.     

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.     

Reducing intrinsic biochemical noise in cells and its thermodynamic limit

In living cells, the specificity of biomolecular recognition can be amplified and the noise from non-specific interactions can be reduced at the expense of cellular free energy. This is the seminal idea in the Hopfield-Ninio theory of kinetic proofreading: The specificity is increased via cyclic network kinetics without altering molecular structures and equilibrium affinites. We show a thermodynamic limit of the specificity amplification with a given amount of available free energy. For a normal cell under physiological condition with sustained phosphorylation potential, this gives a factor of 10(10) as the upper bound in specificity amplification. We also study an optimal kinetic network design that is capable of approaching the thermodynamic limit.     

Recent successes of the energy landscape theory of protein folding and function

Protein folding and binding can be understood using energy landscape theory. When seeming deviations from the predictions of the funnel hypothesis are found, landscape theory helps us locate the cause. Sometimes the deviation reflects symmetry effects, allowing extra degeneracies to occur. Such effects seem to explain some kinetic anomalies in helical bundles. When binding processes were found to use apparently non-funneled landscapes this was traced to an inadequate understanding of biomolecular forces. The discrepancy allowed the discovery of new water-mediated forces - some of which act between hydrophilic residues. Introducing such forces into the algorithms greatly improves the quality of structure predictions.     

Optimal specificity and function for flexible biomolecular recognition

Biomolecular associations often accompanied by large conformational changes, sometimes folding and unfolding. By exploring an exactly solvable model, we constructed the free energy landscape and established a general framework for studying the biomolecular flexible binding process. We derived an optimal criterion for the specificity and function for flexible biomolecular binding where the binding and conformational folding are coupled.     

Enthalpy-entropy compensation and cooperativity as thermodynamic epiphenomena of structural flexibility in ligand-receptor interactions

Ligand binding is a thermodynamically cooperative process in many biochemical systems characterized by the conformational flexibility of the reactants. However, the contribution of conformational entropy to cooperativity of ligation needs to be elucidated. Here, we perform kinetic and thermodynamic analyses on a panel of cycle-mutated peptides, derived from influenza H3 HA(306-319), interacting with wild type and a mutant HLA-DR. We observe that, within a certain range of peptide affinity, this system shows isothermal entropy-enthalpy compensation (iEEC). The incremental increases in conformational entropy measured as disruptive mutations are added in the ligand or receptor are more than sufficient in magnitude to account for the experimentally observed lack of free-energy decrease cooperativity. Beyond this affinity range, compensation is not observed, and therefore, the ability of the residual interactions to form a stable complex decreases in an exponential fashion. Taken together, our results indicate that cooperativity and iEEC constitute the thermodynamic epiphenomena of the structural fluctuation that accompanies ligand-receptor complex formation in flexible systems. Therefore, ligand binding affinity prediction needs to consider how each source of binding energy contributes synergistically to the folding and kinetic stability of the complex in a process based on the trade-off between structural tightening and restraint of conformational mobility.     

Exploring the energy landscapes of molecular recognition by a genetic algorithm: Analysis of the requirements for robust docking of HIV-1 protease and FKBP-12 complexes

Energy landscapes of molecular recognition are explored by performing “semi-rigid” docking of FK-506 and rapamycin with the Fukisawa binding protein (FKBP-12), and flexible docking simulations of the Ro-31-8959 and AG-1284 inhibitors with HIV-1 protease by a genetic algorithm. The requirements of a molecular recognition model to meet thermodynamic and kinetic criteria of ligand-protein docking simultaneously are investigated using a family of simple molecular recognition energy functions. The critical factor that determines the success rate in predicting the structure of ligand-protein complexes is found to be the roughness of the binding energy landscape, in accordance with a minimal frustration principle. The results suggest that further progress in structure prediction of ligand-protein complexes can be achieved by designing molecular recognition energy functions that generate binding landscapes with reduced frustration. © 1996 Wiley-Liss, Inc.     

Disparate degrees of hypervariable loop flexibility control T-cell receptor cross-reactivity, specificity, and binding mechanism

αβ T-cell receptors (TCRs) recognize multiple antigenic peptides bound and presented by major histocompatibility complex molecules. TCR cross-reactivity has been attributed in part to the flexibility of TCR complementarity-determining region (CDR) loops, yet there have been limited direct studies of loop dynamics to determine the extent of its role. Here we studied the flexibility of the binding loops of the αβ TCR A6 using crystallographic, spectroscopic, and computational methods. A significant role for flexibility in binding and cross-reactivity was indicated only for the CDR3α and CDR3β hypervariable loops. Examination of the energy landscapes of these two loops indicated that CDR3β possesses a broad, smooth energy landscape, leading to rapid sampling in the free TCR of a range of conformations compatible with different ligands. The landscape for CDR3α is more rugged, resulting in more limited conformational sampling that leads to specificity for a reduced set of peptides as well as the major histocompatibility complex protein. In addition to informing on the mechanisms of cross-reactivity and specificity, the energy landscapes of the two loops indicate a complex mechanism for TCR binding, incorporating elements of both conformational selection and induced fit in a manner that blends features of popular models for TCR recognition.     

Engineering substrate preference in subtilisin: structural and kinetic analysis of a specificity mutant

Bacillus subtilisin has been a popular model protein for engineering altered substrate specificity. Although some studies have succeeded in increasing the specificity of subtilisin, they also demonstrate that high specificity is difficult to achieve solely by engineering selective substrate binding. In this paper, we analyze the structure and transient state kinetic behavior of Sbt160, a subtilisin engineered to strongly prefer substrates with phenylalanine or tyrosine at the P4 position. As in previous studies, we measure improvements in substrate affinity and overall specificity. Structural analysis of an inactive version of Sbt160 in complex with its cognate substrate reveals improved interactions at the S4 subsite with a P4 tyrosine. Comparison of transient state kinetic behavior against an optimal sequence (DFKAM) and a similar, but suboptimal, sequence (DVRAF) reveals the kinetic and thermodynamic basis for increased specificity, as well as the limitations of this approach. While highly selective substrate binding is achieved in Sbt160, several factors cause sequence specificity to fall short of that observed with natural processing subtilisins. First, for substrate sequences which are nearly optimal, the acylation reaction becomes faster than substrate dissociation. As a result, the level of discrimination among these substrates diminishes due to the coupling between substrate binding and the first chemical step (acylation). Second, although Sbt160 has 24-fold higher substrate affinity for the optimal substrate DFKAM than for DVRAF, the increased substrate binding energy is not translated into improved transition state stabilization of the acylation reaction. Finally, as interactions at subsites become stronger, the rate-determining step in peptide hydrolysis changes from acylation to product release. Thus, the release of the product becomes sluggish and leads to a low k(cat) for the reaction. This also leads to strong product inhibition of substrate turnover as the reaction progresses. The structural and kinetic analysis reveals that differences in the binding modes at subsites for substrates, transition states, and products are subtle and difficult to manipulate via straightforward protein engineering. These findings suggest several new strategies for engineering highly sequence selective enzymes.     

Dimerization-induced folding of MST1 SARAH and the influence of the intrinsically unstructured inhibitory domain: low thermodynamic stability of monomer

The serine/threonine mammalian sterile 20-like kinase (MST1) is involved in promotion of caspase-dependent and independent apoptosis. Phosphorylation and oligomerization are required for its activation. The oligomerization domain, denoted as SARAH domain, forms an antiparallel coiled coil dimer, and it is important for both MST1 autophosphorylation and interactions with other proteins like the Rassf proteins containing also a SARAH domain. Here we show that the monomeric state of SARAH is thermodynamically unstable and that homodimerization is coupled with folding. Moreover, the influence of the inhibitory domain on SARAH stability and affinity is addressed. By investigating the thermal denaturation using differential scanning calorimetry and circular dichroism, we have found that the SARAH domain dissociates and unfolds cooperatively, without a stable intermediate monomeric state. Combining the data with information from isothermal titration calorimetry, a low thermodynamic stability of the monomeric species is obtained. Thus, it is proposed that the transition from MST1 SARAH homodimer to some specific heterodimer implies a non-native monomer intermediate. The inhibitory domain is found to be highly flexible and intrinsically unfolded, not only in isolation but also in the dimeric state of the inhibitory-SARAH construct. The existence of two caspase recognition motifs within the inhibitory domain suggests that its structural flexibility might be important for activation of MST1 during apoptosis. Moreover, the inhibitory domain increases the thermodynamic stability of the SARAH dimer and the homodimer affinity, while having almost no effect on the SARAH domain in the monomeric state. These results emphasize the importance of flexibility and binding-induced folding for specificity, affinity, and the capacity to switch from one state to another.     

Relationship between folding and function in a sequence-specific miniature DNA-binding protein

Previously, we have described a miniature protein-based approach to the design of molecules that bind DNA or protein surfaces with high affinity and specificity. In this approach, the small, well-folded protein avian pancreatic polypeptide acts as a scaffold to present and stabilize an alpha-helical or PPII-helical recognition epitope. The first miniature protein designed in this way, a molecule called p007, presents the alpha-helical recognition epitope found on the bZIP protein GCN4 and binds DNA with nanomolar affinity and exceptional specificity. In this work we use alanine-scanning mutagenesis to explore the contributions of 29 p007 residues to DNA affinity, specificity, and secondary structure. Virtually every residue within the p007 alpha-helix, and most residues within the p007 PPII helix, contribute to both DNA affinity and specificity. These residues include those introduced to make specific and nonspecific DNA contacts, as well as those that complete the miniature protein core. Moreover, there exists a direct correlation between the affinity of a p007 variant for specific DNA and the ability of that variant to select for specific DNA over nonspecific DNA. Although we observe no correlation between alpha-helicity and affinity, we observe a limited correlation between alpha-helicity and sequence specificity that emphasizes the role of coupled binding/folding in the function of p007. Our results imply that formation of a highly evolved set of protein.DNA contacts in the context of a well-packed hydrophobic core, and not the extent of intrinsic alpha-helical structure, is the primary determinant of p007 function.     

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.     

Nonequilibrium capillary electrophoresis of equilibrium mixtures (NECEEM): A novel method for biomolecular screening

Nonequilibrium capillary electrophoresis of equilibrium mixtures (NECEEM) is a new separation-based affinity method. It has kinetic capabilities exceeding those of surface plasmon resonance (SPR) and does not require immobilization of molecules on the surface. Another distinctive feature of NECEEM is that--if it is combined with an advanced method for the mixing solutions inside a capillary, termed transverse diffusion of laminar flow profiles (TDLFP)--it requires only nanoliter volumes of solutions. The proven applications of NECEEM to biomolecular screening include 1) measuring kinetic and thermodynamic parameters of protein-ligand interactions, 2) quantitative affinity analyses of proteins and hybridization analyses of DNA and RNA, and 3) selection of binding ligands from combinatorial libraries. NECEEM is easy to automate and parallelize. Because of its simplicity and analytical power, NECEEM has the potential to become a workhorse in studies of biomolecular interactions. The author reviews theoretical bases of NECEEM and its applications to biomolecular screening.     

Smoothing molecular interactions: the "kinetic buffer" effect of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) widely participate in molecular recognition and signaling processes in cells by interacting with other molecules. Compared with ordered proteins, IDPs usually possess stronger intermolecular interactions in binding. As a result, the interface structure of IDPs in complexes is distinct from that of ordered-protein complexes, and this difference may have essential effect on the response to various perturbations in a cell. In this study, we examined the perturbations of intermolecular interactions and temperature on the coupled folding and binding processes of pKID to KIX domains by performing molecular dynamics simulations. By comparing a series of virtual pKID systems with various degree of disorder, we found that the complex stability and the binding kinetics of the disordered systems were less sensitive to the perturbations than the ordered systems. The origin of the lower response sensitivity of IDPs was attributed to their higher flexibility in the complex interface, which was further supported by an analysis on protein complex structures. On the basis of our simulations and results from the literature, we speculate IDPs may not only interact with their biological partners with high specificity and low affinity but also may be resistant to the perturbations in the environment and transmit signals fast and smooth. We proposed to name it the "kinetic buffer" effect.     

Towards understanding the mechanisms of molecular recognition by computer simulations of ligand-protein interactions

The thermodynamic and kinetic aspects of molecular recognition for the methotrexate (MTX)-dihydrofolate reductase (DHFR) ligand-protein system are investigated by the binding energy landscape approach. The impact of 'hot' and 'cold' errors in ligand mutations on the thermodynamic stability of the native MTX-DHFR complex is analyzed, and relationships between the molecular recognition mechanism and the degree of ligand optimization are discussed. The nature and relative stability of intermediates and thermodynamic phases on the ligand-protein association pathway are studied, providing new insights into connections between protein folding and molecular recognition mechanisms, and cooperativity of ligand-protein binding. The results of kinetic docking simulations are rationalized based on the thermodynamic properties determined from equilibrium simulations and the shape of the underlying binding energy landscape. We show how evolutionary ligand selection for a receptor active site can produce well-optimized ligand-protein systems such as MTX-DHFR complex with the thermodynamically stable native structure and a direct transition mechanism of binding from unbound conformations to the unique native structure.     

Single-molecule studies of riboswitch folding

The folding dynamics of riboswitches are central to their ability to modulate gene expression in response to environmental cues. In most cases, a structural competition between the formation of a ligand-binding aptamer and an expression platform (or some other competing off-state) determines the regulatory outcome. Here, we review single-molecule studies of riboswitch folding and function, predominantly carried out using single-molecule FRET or optical trapping approaches. Recent results have supplied new insights into riboswitch folding energy landscapes, the mechanisms of ligand binding, the roles played by divalent ions, the applicability of hierarchical folding models, and kinetic vs. thermodynamic control schemes. We anticipate that future work, based on improved data sets and potentially combining multiple experimental techniques, will enable the development of more complete models for complex RNA folding processes. This article is part of a Special Issue entitled: Riboswitches.     

Topology-based modeling of intrinsically disordered proteins: balancing intrinsic folding and intermolecular interactions

Coupled binding and folding is frequently involved in specific recognition of so-called intrinsically disordered proteins (IDPs), a newly recognized class of proteins that rely on a lack of stable tertiary fold for function. Here, we exploit topology-based Gō-like modeling as an effective tool for the mechanism of IDP recognition within the theoretical framework of minimally frustrated energy landscape. Importantly, substantial differences exist between IDPs and globular proteins in both amino acid sequence and binding interface characteristics. We demonstrate that established Gō-like models designed for folded proteins tend to over-estimate the level of residual structures in unbound IDPs, whereas under-estimating the strength of intermolecular interactions. Such systematic biases have important consequences in the predicted mechanism of interaction. A strategy is proposed to recalibrate topology-derived models to balance intrinsic folding propensities and intermolecular interactions, based on experimental knowledge of the overall residual structure level and binding affinity. Applied to pKID/KIX, the calibrated Gō-like model predicts a dominant multistep sequential pathway for binding-induced folding of pKID that is initiated by KIX binding via the C-terminus in disordered conformations, followed by binding and folding of the rest of C-terminal helix and finally the N-terminal helix. This novel mechanism is consistent with key observations derived from a recent NMR titration and relaxation dispersion study and provides a molecular-level interpretation of kinetic rates derived from dispersion curve analysis. These case studies provide important insight into the applicability and potential pitfalls of topology-based modeling for studying IDP folding and interaction in general.     

Combined thermodynamic and kinetic analysis of GroEL interacting with CXCR4 transmembrane peptides

GroEL along with ATP and its co-chaperonin GroES has been demonstrated to significantly enhance the folding of newly translated G-protein-coupled receptors (GPCRs). This work extends the previous studies to explore the guest capture and release processes in GroEL-assisted folding of GPCRs, by the reduced approach of employing CXCR4 transmembrane peptides as model substrates. Each of the CXCR4-derived peptides exhibited high affinity for GroEL with a binding stoichiometry near seven. It is found that the peptides interact with the paired α helices in the apical domain of the chaperonin which are similar with the binding sites of SBP (strongly binding peptide: SWMTTPWGFLHP). Complementary binding study with a single-ring version of GroEL indicates that each of the two chaperonin rings is competent for accommodating all the seven CXCR4 peptides bound to GroEL under saturation condition. Meanwhile, the binding kinetics of CXCR4 peptides with GroEL was also examined; ATP alone, or in combination of GroES evidently promoted the release of the peptide substrates from the chaperonin. The results obtained would be beneficial to understand the thermodynamic and kinetic nature of GroEL-GPCRs interaction which is the central molecular event in the assisted folding process.