Folding Pathway Research Articles

Pathway and mechanism of tubulin folding mediated by TRiC/CCT along its ATPase cycle revealed using cryo-EM

The eukaryotic chaperonin TRiC/CCT assists the folding of about 10% of cytosolic proteins through an ATP-driven conformational cycle, and the essential cytoskeleton protein tubulin is the obligate substrate of TRiC. Here, we present an ensemble of cryo-EM structures of endogenous human TRiC throughout its ATPase cycle, with three of them revealing endogenously engaged tubulin in different folding stages. The open-state TRiC-tubulin-S1 and -S2 maps show extra density corresponding to tubulin in the cis-ring chamber of TRiC. Our structural and XL-MS analyses suggest a gradual upward translocation and stabilization of tubulin within the TRiC chamber accompanying TRiC ring closure. In the closed TRiC-tubulin-S3 map, we capture a near-natively folded tubulin—with the tubulin engaging through its N and C domains mainly with the A and I domains of the CCT3/6/8 subunits through electrostatic and hydrophilic interactions. Moreover, we also show the potential role of TRiC C-terminal tails in substrate stabilization and folding. Our study delineates the pathway and molecular mechanism of TRiC-mediated folding of tubulin along the ATPase cycle of TRiC, and may also inform the design of therapeutic agents targeting TRiC-tubulin interactions.

Non-Native Structures of Apomyoglobin and Apoleghemoglobin in Folding Intermediates Related to the Protein Misfolding.

Protein folding is essential for a polypeptide chain to acquire its proper structure and function. Globins are a superfamily of ubiquitous heme-binding α-helical proteins whose function is principally to regulate oxygen homoeostasis. In this review, we explore the hierarchical helical formation in the globin proteins apomyoglobin and leghemoglobin, and we discuss the existence of non-native and misfolded structures occurring during the course of folding to its native state. This review summarizes the research aimed at characterizing and comparing the equilibrium and kinetic intermediates, as well as delineating the complete folding pathway at a molecular level, in order to answer the following questions: "What is the mechanism of misfolding via a folding intermediate? Does the non-native structure stabilize the contemporary intermediate structure? Does the non-native structure induce slower folding?" The role of the non-native structures in the folding intermediate related to misfolding is also discussed.

A Novel Peptide Reagent for Investigating Disulfide-Coupled Folding Intermediates of Mid-Size Proteins.

Investigations of protein folding have largely involved the use of disulfide-containing proteins, since the disulfide-coupled folding of proteins allows folding intermediates to be trapped and their conformations determined. However, studies of the folding mechanisms of mid-size proteins face several problems, one of which is that detecting folding intermediates is difficult. Therefore, to solve this issue, a novel peptide reagent, maleimidohexanoyl-Arg5-Tyr-NH2, was designed and applied to the detection of folding intermediates of model proteins. BPTI was chosen as a model small protein to estimate the ability of the novel reagent to detect folding intermediates. In addition, a precursor protein (prococoonase) of Bombyx mori cocoonase was used as a model mid-size protein. Cocoonase is classified as a serine protease and has a high homology with trypsin. We recently found that the propeptide sequence of prococoonase (proCCN) is important for the folding of cocoonase. However, it was difficult to study the folding pathway of proCCN since the folding intermediates could not be separated on a reversed-phase HPLC (RP-HPLC). Therefore, to separate the folding intermediates by RP-HPLC, the novel labeling reagent was used to accomplish this for proCCN. The results indicated that the peptide reagent allowed the intermediates to be captured, separated on SDS-PAGE, and analyzed by RP-HPLC without the occurrence of undesirable disulfide-exchange reactions during the labeling reactions. The peptide reagent reported herein is a practical tool for investigating the mechanisms of disulfide-coupled folding of mid-size proteins.

N-glycosylation mediated folding and quality control in serine proteases of the hepsin family.

N-linked glycans are specifically attached to asparagine residues in a N-X-S/T motif of secretory pathway glycoproteins. N-glycosylation of newly synthesized glycoproteins directs their folding via the lectin chaperones calnexin and calreticulin that are associated with protein-folding enzymes and glycosidases of the endoplasmic reticulum (ER). Misfolded glycoproteins are retained in the ER by the same lectin chaperones. The work by Sun etal. (FEBS J 2023, 10.1111/febs.16757) in this issue focusses on hepsin, a serine protease on the surface of liver and other organs. The authors deduce that spatial positioning of N-glycans on one side of a conserved domain of hepsin, known as the scavenger receptor-rich cysteine domain, regulates calnexin selection for hepsin maturation and transport through the secretory pathway. If N-glycosylation is elsewhere on hepsin, then it is misfolded and has a prolonged accumulation with calnexin and BiP. This association coincides with the engagement of stress response pathways thatsense glycoprotein misfolding. The topological considerations of N-glycosylation dissected by Sun etal. may help unravel how key sites of N-glycosylation sites required for protein folding and transport have evolved to select the lectin chaperone calnexin pathway for folding and quality control.

Generating Protein Folding Trajectories Using Contact-Map-Driven Directed Walks.

Recent advances in machine learning methods have had a significant impact on protein structure prediction, but accurate generation and characterization of protein-folding pathways remains intractable. Here, we demonstrate how protein folding trajectories can be generated using a directed walk strategy operating in the space defined by the residue-level contact-map. This double-ended strategy views protein folding as a series of discrete transitions between connected minima on the potential energy surface. Subsequent reaction-path analysis for each transition enables thermodynamic and kinetic characterization of each protein-folding path. We validate the protein-folding paths generated by our discretized-walk strategy against direct molecular dynamics simulations for a series of model coarse-grained proteins constructed from hydrophobic and polar residues. This comparison demonstrates that ranking discretized paths based on the intermediate energy barriers provides a convenient route to identifying physically sensible folding ensembles. Importantly, by using directed walks in the protein contact-map space, we circumvent several of the traditional challenges associated with protein-folding studies, namely, long time scales required and the choice of a specific order parameter to drive the folding process. As such, our approach offers a useful new route for studying the protein-folding problem.

Impact of the yeast S0/uS2-cluster ribosomal protein rpS21/eS21 on rRNA folding and the architecture of small ribosomal subunit precursors.

RpS0/uS2, rpS2/uS5, and rpS21/eS21 form a cluster of ribosomal proteins (S0-cluster) at the head-body junction near the central pseudoknot of eukaryotic small ribosomal subunits (SSU). Previous work in yeast indicated that S0-cluster assembly is required for the stabilisation and maturation of SSU precursors at specific post-nucleolar stages. Here, we analysed the role of S0-cluster formation for rRNA folding. Structures of SSU precursors isolated from yeast S0-cluster expression mutants or control strains were analysed by cryogenic electron microscopy. The obtained resolution was sufficient to detect individual 2'-O-methyl RNA modifications using an unbiased scoring approach. The data show how S0-cluster formation enables the initial recruitment of the pre-rRNA processing factor Nob1 in yeast. Furthermore, they reveal hierarchical effects on the pre-rRNA folding pathway, including the final maturation of the central pseudoknot. Based on these structural insights we discuss how formation of the S0-cluster determines at this early cytoplasmic assembly checkpoint if SSU precursors further mature or are degraded.

Protein structure and folding pathway prediction based on remote homologs recognition using PAthreader

Recognition of remote homologous structures is a necessary module in AlphaFold2 and is also essential for the exploration of protein folding pathways. Here, we propose a method, PAthreader, to recognize remote templates and explore folding pathways. Firstly, we design a three-track alignment between predicted distance profiles and structure profiles extracted from PDB and AlphaFold DB, to improve the recognition accuracy of remote templates. Secondly, we improve the performance of AlphaFold2 using the templates identified by PAthreader. Thirdly, we explore protein folding pathways based on our conjecture that dynamic folding information of protein is implicitly contained in its remote homologs. The results show that the average accuracy of PAthreader templates is 11.6% higher than that of HHsearch. In terms of structure modelling, PAthreader outperform AlphaFold2 and ranks first on the CAMEO blind test for the latest three months. Furthermore, we predict protein folding pathways for 37 proteins, in which the results of 7 proteins are almost consistent with those of biological experiments, and the other 30 human proteins have yet to be verified by biological experiments, revealing that folding information can be exploited from remote homologous structures.

Functional, pathogenic, and pharmacological roles of protein folding intermediates.

Protein expression and function in eukaryotic cells are tightly harmonized processes modulated by the combination of different layers of regulation, including transcription, processing, stability, and translation of messenger RNA, as well as assembly, maturation, sorting, recycling, and degradation of polypeptides. Integrating all these pathways and the protein quality control machinery, deputed to avoid the production and accumulation of aberrantly folded proteins, determines protein homeostasis. Over the last decade, the combined development of accurate time-resolved experimental techniques and efficient computer simulations has opened the possibility of investigating biological mechanisms at atomic resolution with physics-based models. A meaningful example is the reconstruction of protein folding pathways at atomic resolution, which has enabled the characterization of the folding kinetics of biologically relevant globular proteins consisting of a few hundred amino acids. Combining these innovative computational technologies with rigorous experimental approaches reveals the existence of non-native metastable states transiently appearing along the folding process of such proteins. Here, we review the primary evidence indicating that these protein folding intermediates could play roles in disparate biological processes, from the posttranslational regulation of protein expression to disease-relevant protein misfolding mechanisms. Finally, we discuss how the information encoded into protein folding pathways could be exploited to design an entirely new generation of pharmacological agents capable of promoting the selective degradation of protein targets.

Investigating the role of computer simulations in modeling complex biological systems

The use of computer simulations in modeling complex biological systems has become an important tool for biotechnology research. This study investigates the role of computer simulations in modeling complex biological systems and their potential applications in biotechnology. The focus of the study was on protein folding, a complex biological process that plays a critical role in the structure and function of proteins. The simulation was carried out using molecular dynamics techniques that allowed the simulation of the movement of the protein molecules over time. The simulation results were compared to experimental data and showed a good agreement with the actual protein structure. Furthermore, the simulation provided insights into the dynamics of the protein folding process, such as the folding pathway and the stability of the intermediate states. These insights can be used to design new drugs and therapies that target specific protein structures and functions. The study concludes that computer simulations are a valuable tool in biotechnology research and have the potential to revolutionize the field by providing accurate and detailed information about complex biological systems. Future research could investigate the use of advanced computer simulations and machine learning algorithms in biotechnology applications to improve their accuracy and efficiency.

Inferring Pathways of Oxidative Folding from Prefolding Free Energy Landscapes of Disulfide-Rich Toxins.

Short, cysteine-rich peptides can exist in stable or metastable structural ensembles due to the number of possible patterns of formation of their disulfide bonds. One interesting subset of this peptide group is the conotoxins, which are produced by aquatic snails in the family Conidae. The μ conotoxins, which are antagonists and blockers of the voltage-gated sodium channel, exist in a folding spectrum: on one end of the spectrum are more hirudin-like folders, which form disulfide bonds and then reshuffle them, leading to an ensemble of kinetically trapped isomers, and on the other end are more BPTI-like folders, which form the native disulfide bonds one by one in a particular order, leading to a preponderance of conformations existing in a single stable state. In this Article, we employ the composite diffusion map approach to study the unified free energy surface of prefolding μ-conotoxin equilibrium. We identify the two most important nonlinear collective modes of the unified folding landscape and demonstrate that in the absence of their disulfides, the conotoxins can be thought of as largely disordered polymers. A small increase in the number of hydrophobic residues in the protein shifts the free energy landscape toward hydrophobically collapsed coil conformations responsible for cysteine proximity in hirudin-like folders, compared to semiextended coil conformations with more distal cysteines in BPTI-like folders. Overall, this work sheds important light on the folding processes and free energy landscapes of cysteine-rich peptides and demonstrates the extent to which sequence and length contribute to these landscapes.

Biophysical Correlates of Enhanced Immunogenicity of a Stabilized Variant of the Receptor Binding Domain of SARS-CoV-2.

The receptor binding domain (RBD) of SARS-CoV-2 is the primary target of neutralizing antibodies. We have previously reported the design and characterization of a mammalian cell expressed RBD derivative, mRBD1-3.2, that has higher thermal stability and greatly enhanced immunogenicity relative to the wild type mRBD. The protein is highly thermotolerant and immunogenic and is being explored for use in room temperature stable Covid-19 vaccine formulations. In the current study, we have investigated the folding pathway of both WT and stabilized RBD. It was found that chemical denaturation of RBD proceeds through a stable equilibrium intermediate. Thermal and chemical denaturation is reversible, as assayed by binding to the receptor ACE2. Unusually, in its native state, RBD binds to the hydrophobic probe ANS, and enhanced ANS binding is observed for the equilibrium intermediate state. Further characterization of the folding of mRBD1-3.2, both in solution and after reconstitution of lyophilized protein stored for a month at 37 °C, revealed a higher stability represented by higher Cm, faster refolding, slower unfolding, and enhanced resistance to proteolytic cleavage relative to WT. In contrast to WT RBD, the mutant showed decreased interaction with the hydrophobic moiety linoleic acid. Collectively, these data suggest that the enhanced immunogenicity results from reduced conformational fluctuations that likely enhance in vivo half-life as well as reduce the exposure of irrelevant non-neutralizing epitopes to the immune system.

Learning to self-fold at a bifurcation.

Disordered mechanical systems can deform along a network of pathways that branch and recombine at special configurations called bifurcation points. Multiple pathways are accessible from these bifurcation points; consequently, computer-aided design algorithms have been sought to achieve a specific structure of pathways at bifurcations by rationally designing the geometry and material properties of these systems. Here, we explore an alternative physical training framework in which the topology of folding pathways in a disordered sheet is changed in a desired manner due to changes in crease stiffnesses induced by prior folding. We study the quality and robustness of such training for different "learning rules," that is, different quantitative ways in which local strain changes the local folding stiffness. We experimentally demonstrate these ideas using sheets with epoxy-filled creases whose stiffnesses change due to folding before the epoxy sets. Our work shows how specific forms of plasticity in materials enable them to learn nonlinear behaviors through their prior deformation history in a robust manner.

Protein folding pathway and intermediates on the dimensionality reduced landscape with UMAP and native contact likelihood.

To understand protein folding mechanisms from molecular dynamics (MD) simulations, it is important to explore not only folded/unfolded states but also representative intermediate structures on the conformational landscape. Generally, such a conformational landscape is obtained by linear dimensionality reduction methods, principal component analysis (PCA) or time-lagged independent component analysis (tICA), for instance. However, it is often difficult to apply these linear methods to large-scale, nonlinear conformational changes such as protein folding. Here, we propose a novel approach to construct the landscape using the uniform manifold approximation and projection (UMAP) method, which nonlinearly reduces the dimensionality without losing data-point proximity. In the approach, native contact likelihood, a measure for native contact formation, is used as feature variables rather than the conventional Cartesian coordinates or dihedral angles of protein structures. We tested the performance of UMAP for coarse-grained MD simulation trajectories of B1 domain in protein G and observed on-pathway transient structures and other metastable states on the UMAP conformational landscape. In contrast, these structures were not clearly distinguished on the dimensionality reduced landscape using PCA or tICA. This approach is also useful to obtain dynamical information through Markov State Modeling and would be applicable to large-scale conformational changes in many other biomacromolecules.

Investigating the mechanism of suppression of human γD-crystallin aggregation by myo-inositol.

Aggregation of γ-crystallins in the lens of the eye is implicated in cataract disease. Misfolding of this protein under oxidative conditions, such as those present in the ageing eye lens, and mutations in the CRYGD gene correlate with cataract formation. Previous studies from our group indicated that non-native disulfide bonds in early unfolding intermediates kinetically trap misfolded conformations of γD-crystallin, which then aggregate by a mechanism akin to domain-swapping. Recent biophysical experiments from our group have shown that myo-inositol, a small molecule that is abundant in the healthy lens, disrupts the aggregation of human γD-crystallin in vitro and inhibits formation of the aggregation precursors. In this project, theoretical techniques are used to complement these experiments by providing more detailed, atomistic insights into the mechanism of aggregation suppression. Monte Carlo (MC) simulations with a statistical potential, replica exchange and umbrella biasing are used to generate structures for folding intermediates for γD-crystallin and several constructs with experimentally relevant, aggregation-prone mutations, and folding pathways are elucidated from these simulations using our group's previously validated DBFOLD algorithm. Theoretical results are validated against experimental data by comparing calculated misfolding parameters with known experimental aggregation propensities. In addition, Molecular Dynamics (MD) simulations are used to probe the transient chemical interactions between myo-inositol and γD-crystallin folding intermediates, and results from these simulations are compared to insights from aggregation assays, NMR data, and other spectroscopic experiments. The aim is to predict and characterize key chemical interactions whereby myo-inositol shifts γD-crystallin away from aggregation-permissive conformations, which would enable development of improved drug candidates to treat or prevent cataract disease. Our approach to simulating structures of γD-crystallin aggregation precursors and modelling their interactions with small molecules may generalize to other protein misfolding diseases.

DNA folding by protamine from loops to stacks.

In sperm, DNA undergoes a dramatic reorganization to a semi-crystalline state. This incredible compaction is the work of positively charged protamine proteins which bend and loop negatively charged DNA into a series of toroids. Interestingly, other positively charged molecules such as spermine or cations such as cobalt (+3) have been shown to form these toroid structures in vitro, indicating that the physics that drives this process is likely to be electrostatic. Still, the exact mechanism and the states in the folding pathway are unknown. We have previously shown that multiple protamine molecules “bind and bend” the DNA into a loop. But, what happens after loop formation? To answer this question, we measured folding by protamine in vitro on DNA molecules (length = 600-3000 bp) that are known to form several loops. Using atomic force microscopy (AFM), we were able to identify several intermediate folded structures: molecules with a single loop (a loop), molecules with two or more loops that were connected at a single location like a flower (flowers), and molecules with two or more loops stacked on top of one another (stacks). Using a tethered particle motion (TPM) assay we measured real-time folding of the DNA into these structures. At low protamine concentrations (0.1 µM), we observed many, long-lived, discrete folded states indicative of protamine bending, but at higher concentrations (>0.1 µM) these states appeared as a single, initial folding event. We hypothesize that this single, initial folding event is protamine bending the DNA all along its length, causing multiple loops. These loops then collapse into a stack. More work is necessary to determine how these stacks eventually form toroids. This work is important for spermiogenesis and DNA condensation, but also may useful in DNA nanoengineering.

What does alphafold know about protein folding and peptide binding.

Machine learning approaches have recently revolutionized structural biology by predicting 3D structures of proteins at atomistic level from their sequence with high confidence and accuracy. The community is pushing the limits of interpretability and application of these algorithms beyond their original objective. Here, we present our studies on what deep neural network models for protein structure prediction such as AlphaFold can shed light on two fundamental biological processes: (1) protein folding and (2) protein-peptide binding. We first demonstrate our studies on deciphering the folding mechanism of protein G, L and their mutants, two pair of proteins with low sequence similarity that fold into the same topology. By using large-scale molecular dynamics simulations with advanced enhanced sampling methods and Markov state modeling analysis, we observed how the sequence difference impacts folding pathways and rate in unprecedented detail. Then, we show a novel fragment decomposition approach using AlphaFold to identify preferences for secondary structure element combinations that follow the order of events observed in the folding pathways. Standing upon the highly sensitive mapping of AlphaFold between the sequence and structure, we discovered how to directly use the model to identify high affinity peptide binders using a competitive binding assay. For systems in which the individual structures of the peptides are well predicted, the assay captures the higher affinity binder in the bound state, and the other peptide in the unbound form. The speed and robustness of the method will make it readily applicable in screening libraries of peptide sequences to prioritize for detailed experimental characterization.

Stabilizing a centrifugal force microscope to study DNA folding

A centrifugal force microscope (CFM) is a highly cost-effective and user-friendly method to apply force with a desktop centrifuge. Applying force in a biophysical assay allows for studying the mechanics of motor proteins or the folding pathway of DNA or proteins. However, in comparison to other methods—such as atomic force microscopy, optical tweezers, and magnetic tweezers—measurements of position in the CFM are limited. Position is measured by video microscopy which is affected by the shaking of the centrifuge when it begins to rotate and the unfocusing of the camera. To improve stability, we followed the original designs from Yang (Methods in Molecular Biology 2016) and then worked to enhance focus stability over longer periods of time; investigated sample illumination; and altered the counterbalance scheme to reduce mechanical noise. An enhanced stability would allow reliable collection of position data to be used to produce a force-extension curve of DNA.

Learning reaction coordinates for enhanced sampling directly using atomic positions.

We present an approach for learning a reaction coordinate that can be used to enhance sampling directly between two biomolecular structures. The current method is based on our previous molecular simulation clustering algorithm entitled Size-and-Shape Space Gaussian Mixture Models (shapeGMM). By overcoming rotational invariance using robust alignment protocols, shapeGMM clusters molecular structures using particle positions. The result of shapeGMM is a set of cluster means and covariances that, unlike many internal coordinate methods, do not overdetermine the structures. shapeGMM was found to produce physically meaningful clusters on a 300-microsecond trajectory of a fast-folding HP35 Nle/Nle mutant; the trajectory was obtained from D. E. Shaw Research Institute. To further study the folding and unfolding pathways of this system, we compute a reaction coordinate between corresponding cluster means using Linear Discriminate Analysis (LDA); LDA is a supervised classification technique that identifies the linear coordinate which simultaneously maximizes the between cluster variance and minimizes the within cluster variance. Barriers in the free energy surface (FES) along the first linear discriminant (LD1) corresponded to the point where the committor is 0.5, suggesting this is a good reaction coordinate. Metadynamics simulations biased along LD1, a method we have implemented in PLUMED, achieved a FES in reasonable agreement with that generated from the long MD simulation, suggesting that LD1 is also a good sampling coordinate. FESs produced along coordinates obtained from subsets of the data close to the centers of the cluster means also agree well with the committor, suggesting this approach may be appropriate for situations where both states of a molecule are known, but extensive unbiased data is not available.

Folding and threading of leptin as a model for pierced lasso topologies.

The introduction of entanglements in proteins remains elusive, where the mechanism of formation is unclear. We have for the first time characterized the folding and threading mechanism of a “knot-like” protein. The recently discovered Pierced Lasso Topology (PLT) is a class of proteins in which a disulfide formed covalent loop is threaded by the protein backbone of a free terminus. Within the last decade PLTs have been identified in over 600 known protein structures across all kingdoms of life. These proteins vary in function from oxidoreductases to hydrolases and small hormones. Their presence in different cellular compartments is highly influenced by the redox potential of the environment acting as a potential molecular switch. A combination of experimental phi-value analysis and structure-based models were used to identify key residues within the folding pathway for the model human hormone leptin. Previous computational work uncovered that the threading event occurs within the early stage of the folding free energy landscape. Incorporation of a threading event adds ruggedness to the folding landscape, slowing the process. Our investigation of leptin's in vitro threading event utilized a variant designed to lock the structure in a pre-threaded conformation inhibiting unthreading of the chain in the denatured state. The designed variant folds 100 times faster than the wild type, demonstrating that leptin spontaneously threads/unthreads in oxidizing environments; with the covalent loop intact.

Oncogenic mutations in the DNA-binding domain of FOXO1 that disrupt folding: Quantitative insights from experiments and molecular simulation.

FOXO1, a member of the family of winged-helix motif Forkhead box (FOX) transcription factors, is the most abundantly expressed FOXO member in mature B cells. Sequencing of diffuse large B-cell lymphoma (DLBCL) tumors and cell lines identified specific mutations in the forkhead domain linked to loss of function. Differential scanning calorimetry and thermal shift assays were used to characterize how eight of these mutations affect the stability of the FOX domain. Mutations L183P and L183R were found to be particularly destabilizing. Electrophoresis mobility shift assays show these same mutations also disrupt FOXO1 binding to their canonical DNA sequences, suggesting that the loss of function is due to destabilization of the folded structure. Computational modeling of the effect of mutations on FOXO1 folding was performed using alchemical free energy perturbation (FEP), and a Markov model of the entire folding reaction was constructed from massively parallel molecular simulations, which predicts folding pathways involving the late folding of helix α3. Although FEP can qualitatively predict the destabilization from L183 mutations, we find that a simple hydrophobic transfer model, combined with estimates of unfolded-state solvent-accessible surface areas from molecular simulations, is able to more accurately predict changes in folding free energies due to mutations. These results suggest that the atomic detail provided by simulations is important for the accurate prediction of mutational effects on folding stability. Corresponding disease-associated mutations in other FOX family members support further experimental and computational studies of the folding mechanism of FOX domains.