High-Resolution Mapping of the Folding Transition State of a WW Domain

From covalent transition states in chemistry to noncovalent in biology: from β- to Φ-value analysis of protein folding

Solving the mechanism of a chemical reaction requires determining the structures of all the ground states on the pathway and the elusive transition states linking them. 2024 is the centenary of Brønsted's landmark paper that introduced the β-value and structure-activity studies as the only experimental means to infer the structures of transition states. It involves making systematic small changes in the covalent structure of the reactants and analysing changes in activation and equilibrium-free energies. Protein engineering was introduced for an analogous procedure, Φ-value analysis, to analyse the noncovalent interactions in proteins central to biological chemistry. The methodology was developed first by analysing noncovalent interactions in transition states in enzyme catalysis. The mature procedure was then applied to study transition states in the pathway of protein folding - 'part (b) of the protein folding problem'. This review describes the development of Φ-value analysis of transition states and compares and contrasts the interpretation of β- and Φ-values and their limitations. Φ-analysis afforded the first description of transition states in protein folding at the level of individual residues. It revealed the nucleation-condensation folding mechanism of protein domains with the transition state as an expanded, distorted native structure, containing little fully formed secondary structure but many weak tertiary interactions. A spectrum of transition states with various degrees of structural polarisation was then uncovered that spanned from nucleation-condensation to the framework mechanism of fully formed secondary structure. Φ-analysis revealed how movement of the expanded transition state on an energy landscape accommodates the transition from framework to nucleation-condensation mechanisms with a malleability of structure as a unifying feature of folding mechanisms. Such movement follows the rubric of analysis of classical covalent chemical mechanisms that began with Brønsted. Φ-values are used to benchmark computer simulation, and Φ and simulation combine to describe folding pathways at atomic resolution.

Atomic-level thermodynamics analysis of the binding free energy of SARS-CoV-2 neutralizing antibodies

Understanding how protein-protein binding affinity is determined from molecular interactions at the interface is essential in developing protein therapeutics such as antibodies, but this has not yet been fully achieved. Among the major difficulties are the facts that it is generally difficult to decompose thermodynamic quantities into contributions from individual molecular interactions and that the solvent effect-dehydration penalty-must also be taken into consideration for every contact formation at the binding interface. Here, we present an atomic-level thermodynamics analysis that overcomes these difficulties and illustrate its utility through application to SARS-CoV-2 neutralizing antibodies. Our analysis is based on the direct interaction energy computed from simulated antibody-protein complex structures and on the decomposition of solvation free energy change upon complex formation. We find that the formation of a single contact such as a hydrogen bond at the interface barely contributes to binding free energy due to the dehydration penalty. On the other hand, the simultaneous formation of multiple contacts between two interface residues favorably contributes to binding affinity. This is because the dehydration penalty is significantly alleviated: the total penalty for multiple contacts is smaller than a sum of what would be expected for individual dehydrations of those contacts. Our results thus provide a new perspective for designing protein therapeutics of improved binding affinity.

Advances in the understanding of protein misfolding and aggregation through molecular dynamics simulation

Aberrant protein folding known as protein misfolding is counted as one of the striking factors of neurodegenerative diseases. The extensive range of pathologies caused by protein misfolding, aggregation and subsequent accumulation are mainly classified into either gain of function diseases or loss of function diseases. In order to seek for novel strategies for treatment and diagnosis of neurodegenerative diseases, insights into the mechanism of misfolding and aggregation is essential. A comprehensive knowledge on the factors influencing misfolding and aggregation is required as well. An extensive experimental study on protein aggregation is somewhat challenging due to the insoluble and noncrystalline nature of amyloid fibrils. Thus there has been a growing use of computational approaches including Monte Carlo simulation, docking simulation, molecular dynamics simulation in the study of protein misfolding and aggregation. The review presents a discussion on molecular dynamics simulation alone as to how it has emerged as a promising tool in the understanding of protein misfolding and aggregation in general, detailing upon three different aspects considering four misfold prone proteins in particular. It is noticeable that all four proteins considered in this review i.e prion, superoxide dismutase1, huntingtin and amyloid β are linked to chronic neurodegenerative diseases with debilitating effects. Initially the review elaborates on the factors influencing the misfolding and aggregation. Next, it addresses our current understanding of the amyloid structures and the associated aggregation mechanisms, finally, summarizing the contribution of this computational tool in the search for therapeutic strategies against the respective protein-deposition diseases.

Protein Stabilization by Alginate Binding and Suppression of Thermal Aggregation

Polymers designed to stabilize proteins exploit direct interactions or crowding, but mechanisms underlying increased stability or reduced aggregation are rarely established. Alginate is widely used to encapsulate proteins for drug delivery and tissue regeneration despite limited knowledge of its impact on protein stability. Here, we present evidence that alginate can both increase protein folding stability and suppress the aggregation of unfolded protein through direct interactions without crowding. We used a fluorescence-based conformational reporter of two proteins, the metabolic protein phosphoglycerate kinase (PGK) and the hPin1 WW domain to monitor protein stability and aggregation as a function of temperature and the weight percent of alginate in solution. Alginate stabilizes PGK by up to 14.5 °C, but stabilization is highly protein-dependent, and the much smaller WW domain is stabilized by only 3.5 °C against thermal denaturation. Stabilization is greatest at low alginate weight percent and decreases at higher alginate concentrations. This trend cannot be explained by crowding, and ionic screening suggests that alginate stabilizes proteins through direct interactions with a significant electrostatic component. Alginate also strongly suppresses aggregation at high temperature by irreversibly associating with unfolded proteins and preventing refolding. Both the beneficial and negative impacts of alginate on protein stability and aggregation have important implications for practical applications.

Identification of novel functional mini-receptors by combinatorial screening of split-WW domains

β-Sheet motifs such as the WW domain are increasingly being explored as building blocks for synthetic biological applications. Since the sequence-structure relationships of β-sheet motifs are generally complex compared to the well-studied α-helical coiled coil (CC), other approaches such as combinatorial screening should be included to vary the function of the peptide. In this study, we present a combinatorial approach to identify novel functional mini-proteins based on the WW-domain scaffold, which takes advantage of the successful reconstitution of the fragmented WW domain of hPin1 (hPin1WW) by CC association. Fragmentation of hPin1WW was performed in both loop 1 (CC-hPin1WW-L1) and loop 2 (CC-hPin1WW-L2), and the respective fragments were linked to the strands of an antiparallel heterodimeric CC. Structural analysis by CD and NMR spectroscopy revealed structural reconstitution of the WW-domain scaffold only in CC-hPin1WW-L1, but not in CC-hPin1WW-L2. Furthermore, by using 1H-15N HSQC NMR, fluorescence and CD spectroscopy, we demonstrated that binding properties of fragmented hPin1WW in CC-hPin1WW-L1 were fully restored by CC association. To demonstrate the power of this approach as a combinatorial screening platform, we synthesized a four-by-six library of N- and C-terminal hPin1WW-CC peptide fragments that was screened for a WW domain that preferentially binds to ATP over cAMP, phophocholine, or IP6. Using this screening platform, we identified one WW domain, which specifically binds ATP, and a phosphorylcholine-specific WW-based mini-receptor, both having binding dissociation constants in the lower micromolar range.

Exploring the Effect of Enhanced Sampling on Protein Stability Prediction

Changes in protein stability due to side-chain mutations are evaluated by alchemical free-energy calculations based on classical molecular dynamics (MD) simulations in explicit solvent using the GROMOS force field. Three proteins of different complexity with a total number of 93 single-point mutations are analyzed, and the relative free-energy differences are discussed with respect to configurational sampling and (dis)agreement with experimental data. For the smallest protein studied, a 34-residue WW domain, the starting structure dependence of the alchemical free-energy changes, is discussed in detail. Deviations from previous simulations for the two other proteins are shown to result from insufficient sampling in the earlier studies. Hamiltonian replica exchange in combination with multiple starting structures and sufficient sampling time of more than 100 ns per intermediate alchemical state is required in some cases to reach convergence.

Site-Specific Backbone and Side-Chain Contributions to Thermodynamic Stabilizing Forces of the WW Domain

The native structure of a protein is stabilized by a number of interactions such as main-chain hydrogen bonds and side-chain hydrophobic contacts. However, it has been challenging to determine how these interactions contribute to protein stability at single amino acid resolution. Here, we quantified site-specific thermodynamic stability at the molecular level to extend our understanding of the stabilizing forces in protein folding. We derived the free energy components of individual amino acid residues separately for the folding of the human Pin WW domain based on simulated structures. A further decomposition of the thermodynamic properties into contributions from backbone and side-chain groups enabled us to identify the critical residues in the secondary structure and hydrophobic core formation, without introducing physical modifications to the system as in site-directed mutagenesis methods. By relating the structural and thermodynamic changes upon folding for each residue, we find that the simultaneous formation of the backbone hydrogen bonds and side-chain contacts cooperatively stabilizes the folded structure. The identification of stabilizing interactions in a folding protein at atomic resolution will provide molecular insights into understanding the origin of the protein structure and into engineering a more stable protein.

Local Interactions That Contribute Minimal Frustration Determine Foldability

Earlier experiments suggest that the evolutionary information (conservation and coevolution) encoded in protein sequences is necessary and sufficient to specify the fold of a protein family. However, there is no computational work to quantify the effect of such evolutionary information on the folding process. Here we explore the role of early folding steps for sequences designed using coevolution and conservation through a combination of computational and experimental methods. We simulated a repertoire of native and designed WW domain sequences to analyze early local contact formation and found that the N-terminal β-hairpin turn would not form correctly due to strong non-native local contacts in unfoldable sequences. Through a maximum likelihood approach, we identified five local contacts that play a critical role in folding, suggesting that a small subset of amino acid pairs can be used to solve the "needle in the haystack" problem to design foldable sequences. Thus, using the contact probability of those five local contacts that form during the early stage of folding, we built a classification model that predicts the foldability of a WW sequence with 81% accuracy. This classification model was used to redesign WW domain sequences that could not fold due to frustration and make them foldable by introducing a few mutations that led to the stabilization of these critical local contacts. The experimental analysis shows that a redesigned sequence folds and binds to polyproline peptides with a similar affinity as those observed for native WW domains. Overall, our analysis shows that evolutionary-designed sequences should not only satisfy the folding stability but also ensure a minimally frustrated folding landscape.

Mapping Conformational Space of All 8000 Tripeptides by Quantum Chemical Methods: What Strain Is Affordable within Folded Protein Chains?

To gain more insight into the physicochemical aspects of a protein structure from the first principles, conformational space of all 8000 "capped" tripeptides (i.e., N-Ac-X₁X₂X₃-NH-CH₃, where X_i is one of the 20 natural amino acids) was investigated computationally. An enormous dataset (denoted P-CONF_1.6M and containing close to 1 600 000 conformers in total) has been obtained by employing a composite protocol combining density functional theory, semiempirical quantum mechanics (SQM), and state-of-the-art solvation methods with 1000 K molecular dynamics (MD) used to generate initial structures (200 snapshots for each tripeptide). This allowed us to present the first rigorous QM-based glimpse at the vast conformational space spanned by small protein fragments. The same computational procedure was repeated for tripeptide fragments taken from the SCOPe database of three-dimensional protein folds, by restraining them to their geometry in a protein. Such complementary data allowed us to compare the distribution of conformational strain energies of unrestrained tripeptidic fragments "in solvent" with those in existing protein chains. Besides providing a rigorous (ab initio) proof of a few well-known concepts and hypotheses concerning protein structures, such as the distribution of (φ, ψ) angles in Ramachandran plots, we have made several observations that came as a certain surprise: (1) distribution of conformational energies does not significantly differ between the "unbiased/unrestrained" conformers obtained from MD sampling in solvent and the biased conformers, i.e., those of a given tripeptide obtained from protein structures; (2) conformational (strain) energy window up to ∼20 to 25 kcal·mol^-1 is readily available to tripeptide fragments within the context of a protein chain; (3) overpopulation in certain regions of Ramachandran plot was observed for the unbiased conformers. Last but not least, the massive dataset of accurate (DFT-D3//COSMO-RS) conformational (free) energies of ∼1.6 M peptide conformers, P-CONF_1.6M, obtained throughout this work may serve as excellent dataset for calibrating and benchmarking of popular force fields.

New Insights into Folding, Misfolding, and Nonfolding Dynamics of a WW Domain

Intermediate states in protein folding are associated with formation of amyloid fibrils, which are responsible for a number of neurodegenerative diseases. Therefore, prevention of the aggregation of folding intermediates is one of the most important problems to overcome. Recently, we studied the origins and prevention of formation of intermediate states with the example of the Formin binding protein 28 (FBP28) WW domain. We demonstrated that the replacement of Leu26 by Asp26 or Trp26 (in ∼15% of the folding trajectories) can alter the folding scenario from three-state folding, a major folding scenario for the FBP28 WW domain (WT) and its mutants, toward two-state or downhill folding at temperatures below the melting point. Here, for a better understanding of the physics of the formation/elimination of intermediates, (i) the dynamics and energetics of formation of β-strands in folding, misfolding, and nonfolding trajectories of these mutants (L26D and L26W) is investigated; (ii) the experimental structures of WT, L26D, and L26W are analyzed in terms of a kink (heteroclinic standing wave solution) of a generalized discrete nonlinear Schrödinger equation. We show that the formation of each β-strand in folding trajectories is accompanied by the emergence of kinks in internal coordinate space as well as a decrease in local free energy. In particular, the decrease in downhill folding trajectory is ∼7 kcal/mol, while it varies between 31 and 48 kcal/mol for the three-state folding trajectory. The kink analyses of the experimental structures give new insights into formation of intermediates, which may become a useful tool for preventing aggregation.

Interplay between Conformational Strain and Intramolecular Interaction in Protein Structures: Which of Them Is Evolutionarily Conserved?

By computing strain energies of peptide fragments within protein structures and their intramolecular interaction energies, we attempt to reveal general biophysical trends behind the secondary structure formation in the context of protein evolution. Our "protein basis set" consisted of 1143 representatives of different folds obtained from curated SCOPe database, and for each member of the set, the strain and intramolecular energy was calculated on the "rolling tripeptide" basis, employing the DFT-D3/COSMO-RS method for the former and the QM-calibrated force field method (MM) for the latter. The calculated data, strain and interactions, were correlated with the conservation of amino acid residues in secondary structure elements and also with the level of the residue burial within the protein three-dimensional structure. It allowed us to formulate several observations concerning fundamental differences between two main secondary structure motifs: α-helices and β-strands. We have shown that a strong interaction is one of the determining characteristics of the β-sheet formation, at least at the level of tripeptides (and likely penta- or heptapeptides, too), and that the β-strand is a prevailing secondary structure in the strongly-interacting regions of the protein folds conserved by evolution. On the other hand, low strain was neither proven to be an important physicochemical property conserved by evolution nor does it correlate with the propensity for the α-helix and β-strand. Finally, it has been demonstrated that the strong interaction has a certain level of connection with residue burial; however, we demonstrate that these two characteristics should be rather regarded as two complementary factors. These findings represent an important contribution to understanding protein folding from first principles, which is a complementary approach to ongoing efforts to solve the protein folding problem by knowledge-based approaches and machine-learning.

Adaptive Markov state model estimation using short reseeding trajectories

In the last decade, advances in molecular dynamics (MD) and Markov State Model (MSM) methodologies have made possible accurate and efficient estimation of kinetic rates and reactive pathways for complex biomolecular dynamics occurring on slow time scales. A promising approach to enhanced sampling of MSMs is to use "adaptive" methods, in which new MD trajectories are "seeded" preferentially from previously identified states. Here, we investigate the performance of various MSM estimators applied to reseeding trajectory data, for both a simple 1D free energy landscape and mini-protein folding MSMs of WW domain and NTL9(1-39). Our results reveal the practical challenges of reseeding simulations and suggest a simple way to reweight seeding trajectory data to better estimate both thermodynamic and kinetic quantities.

Factors Stabilizing β-Sheets in Protein Structures from a Quantum-Chemical Perspective

Protein folds are determined by the interplay between various (de)stabilizing forces, which can be broadly divided into a local strain of the protein chain and intramolecular interactions. In contrast to the α-helix, the β-sheet secondary protein structure is significantly stabilized by long-range interactions between the individual β-strands. It has been observed that quite diverse amino acid sequences can form a very similar small β-sheet fold, such as in the three-β-strand WW domain. Employing "calibrated" quantum-chemical methods, we show herein on two sequentially diverse examples of the WW domain that the internal strain energy is higher in the β-strands and lower in the loops, while the interaction energy has an opposite trend. Low strain energy computed for peptide sequences in the loop 1 correlates with its postulated early formation in the folding process. The relatively high strain energy within the β-strands (up to 8 kcal mol^-1 per amino acid residue) is compensated by even higher intramolecular interaction energy (up to 15 kcal mol^-1 per residue). It is shown in a quantitative way that the most conserved residues across the structural family of WW domains have the highest contributions to the intramolecular interaction energy. On the other hand, the residues in the regions with the lowest strain are not conserved. We conclude that the internal interaction energy is the physical quantity tuned by evolution to define the β-sheet protein fold.

Proline Restricts Loop I Conformation of the High Affinity WW Domain from Human Nedd4-1 to a Ligand Binding-Competent Type I β-Turn

Sequence alignment of the four WW domains from human Nedd4-1 (neuronal precursor cell expressed developmentally down-regulated gene 4-1) reveals that the highest sequence diversity exists in loop I. Three residues in this type I β-turn interact with the PPxY motif of the human epithelial Na⁺ channel (hENaC) subunits, indicating that peptide affinity is defined by the loop I sequence. The third WW domain (WW3*) has the highest ligand affinity and unlike the other three hNedd4-1 WW domains or other WW domains studied contains the highly statistically preferred proline at the ( i + 1) position found in β-turns. In this report, molecular dynamics simulations and experimental data were combined to characterize loop I stability and dynamics. Exchange of the proline to the equivalent residue in WW4 (Thr) results in the presence of a predominantly open seven residue Ω loop rather than the type I β-turn conformation for the wild-type apo-WW3*. In the presence of the ligand, the structure of the mutated loop I is locked into a type I β-turn. Thus, proline in loop I ensures a stable peptide binding-competent β-turn conformation, indicating that amino acid sequence modulates local flexibility to tune binding preferences and stability of dynamic interaction motifs.

Using Cooperatively Folded Peptides To Measure Interaction Energies and Conformational Propensities

The rates and equilibria of the folding of biopolymers are determined by the conformational preferences of the subunits that make up the sequence of the biopolymer and by the interactions that are formed in the folded state in aqueous solution. Because of the centrality of these processes to life, quantifying conformational propensities and interaction strengths is vitally important to understanding biology. In this Account, we describe our use of peptide model systems that fold cooperatively yet are small enough to be chemically synthesized to measure such quantities. The necessary measurements are made by perturbing an interaction or conformation of interest by mutation and measuring the difference between the folding free energies of the wild type (in which the interaction or conformation is undisturbed) and the mutant model peptides (in which the interaction has been eliminated or the conformational propensities modified). With the proper controls and provided that the peptide model system in question folds via a two-state process, these folding free energy differences can be accurate measures of interaction strengths or conformational propensities. This method has the advantage of having high sensitivity and high dynamic range because the energies of interest are coupled to folding free energies, which can be measured with precisions on the order of a few tenths of a kilocalorie by well-established biophysical methods, like chaotrope or thermal denaturation studies monitored by fluorescence or circular dichroism. In addition, because the model peptides can be chemically synthesized, the full arsenal of natural and unnatural amino acids can be used to tune perturbations to be as drastic or subtle as desired. This feature is particularly noteworthy because it enables the use of analytical tools developed for physical organic chemistry, especially linear free energy relationships, to decompose interaction energies into their component parts to obtain a deeper understanding of the forces that drive interactions in biopolymers. We have used this approach, primarily with the WW domain derived from the human Pin1 protein as our model system, to assess hydrogen bond strengths (especially those formed by backbone amides), the dependence of hydrogen bond strengths on the environment in which they form, β-turn propensities of both natural sequences and small molecule β-turn mimics, and the energetics of carbohydrate-protein interactions. In each case, the combination of synthetic accessibility, the ease of measuring folding energies, and the robustness of the structure of the Pin1 WW domain to mutation enabled us to obtain incisive measurements of quantities that have been challenging to measure by other methods.

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.

The Dependence of Carbohydrate-Aromatic Interaction Strengths on the Structure of the Carbohydrate

Interactions between proteins and carbohydrates are ubiquitous in biology. Therefore, understanding the factors that determine their affinity and selectivity are correspondingly important. Herein, we have determined the relative strengths of intramolecular interactions between a series of monosaccharides and an aromatic ring close to the glycosylation site in an N-glycoprotein host. We employed the enhanced aromatic sequon, a structural motif found in the reverse turns of some N-glycoproteins, to facilitate face-to-face monosaccharide-aromatic interactions. A protein host was used because the dependence of the folding energetics on the identity of the monosaccharide can be accurately measured to assess the strength of the carbohydrate-aromatic interaction. Our data demonstrate that the carbohydrate-aromatic interaction strengths are moderately affected by changes in the stereochemistry and identity of the substituents on the pyranose rings of the sugars. Galactose seems to make the weakest and allose the strongest sugar-aromatic interactions, with glucose, N-acetylglucosamine (GlcNAc) and mannose in between. The NMR solution structures of several of the monosaccharide-containing N-glycoproteins were solved to further understand the origins of the similarities and differences between the monosaccharide-aromatic interaction energies. Peracetylation of the monosaccharides substantially increases the strength of the sugar-aromatic interaction in the context of our N-glycoprotein host. Finally, we discuss our results in light of recent literature regarding the contribution of electrostatics to CH-π interactions and speculate on what our observations imply about the absolute conservation of GlcNAc as the monosaccharide through which N-linked glycans are attached to glycoproteins in eukaryotes.

Can Local Probes Go Global? A Joint Experiment-Simulation Analysis of λ(6-85) Folding

The process of protein folding is known to involve global motions in a cooperative affair; the structure of most of the protein sequences is gained or lost over a narrow range of temperature, denaturant, or pressure perturbations. At the same time, recent simulations and experiments reveal a complex structural landscape with a rich set of local motions and conformational changes. We couple experimental kinetic and thermodynamic measurements with specifically tailored analysis of simulation data to isolate local versus global folding probes. We find that local probes exhibit lower melting temperatures, smaller surface area changes, and faster kinetics compared to global ones. We also see that certain local probes of folding match the global behavior more closely than others. Our work highlights the importance of using multiple probes to fully characterize protein folding dynamics by theory and experiment.

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.