Folding Landscape Research Articles

Non-averaged single-molecule tertiary structures reveal RNA self-folding through individual-particle cryo-electron tomography

Large-scale and continuous conformational changes in the RNA self-folding process present significant challenges for structural studies, often requiring trade-offs between resolution and observational scope. Here, we utilize individual-particle cryo-electron tomography (IPET) to examine the post-transcriptional self-folding process of designed RNA origami 6-helix bundle with a clasp helix (6HBC). By avoiding selection, classification, averaging, or chemical fixation and optimizing cryo-ET data acquisition parameters, we reconstruct 120 three-dimensional (3D) density maps from 120 individual particles at an electron dose of no more than 168 e–Å−2, achieving averaged resolutions ranging from 23 to 35 Å, as estimated by Fourier shell correlation (FSC) at 0.5. Each map allows us to identify distinct RNA helices and determine a unique tertiary structure. Statistical analysis of these 120 structures confirms two reported conformations and reveals a range of kinetically trapped, intermediate, and highly compacted states, demonstrating a maturation folding landscape likely driven by helix-helix compaction interactions.

Folds from fold: Exploring topological isoforms of a single-domain protein

Expanding the protein fold space beyond linear chains is of fundamental significance, yet remains largely unexplored. Herein, we report the creation of seven topological isoforms (i.e., linear, cyclic, knot, lasso, pseudorotaxane, and catenane) from a single protein fold precursor by rewiring the connectivity of secondary structure elements of the SpyTag-SpyCatcher complex and mutating the reactive residue on SpyTag to abolish the isopeptide bonding. These topological isoforms can be directly expressed in cells. Their topologies were confirmed by combined techniques of proteolytic digestion, fluorescence correlation spectroscopy (FCS), size-exclusion chromatography (SEC), and topological transformation. To study the effects of topology on their structures and properties, their biophysical properties were characterized by differential scanning calorimetry (DSC), heteronuclear single quantum coherence nuclear magnetic resonance spectroscopy (HSQC-NMR), and circular dichroism (CD) spectroscopy. Molecular dynamics (MD) simulations were further performed to reveal the atomic details of structural changes upon unfolding. Both experimental and simulation results suggest that they share a similar, well-folded hydrophobic core but exhibit distinct folding/unfolding dynamic behaviors. These results shed light onto the folding landscape of topological isoforms derived from the same protein fold. As a model system, this work improves our understanding of protein structure and dynamics beyond linear chains and suggests that protein folds are highly amenable to topological variation.

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop.

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. We also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

A structural rationale for reversible vs irreversible amyloid fibril formation from a single protein.

Reversible and irreversible amyloids are two diverging cases of protein (mis)folding associated with the cross-β motif in the protein folding and aggregation energy landscape. Yet, the molecular origins responsible for the formation of reversible vs irreversible amyloids have remained unknown. Here we provide evidence at the atomic level of distinct folding motifs for irreversible and reversible amyloids derived from a single protein sequence: human lysozyme. We compare the 2.8 Å structure of irreversible amyloid fibrils determined by cryo-electron microscopy helical reconstructions with molecular insights gained by solid-state NMR spectroscopy on reversible amyloids. We observe a canonical cross-β-sheet structure in irreversible amyloids, whereas in reversible amyloids, there is a less-ordered coexistence of β-sheet and helical secondary structures that originate from a partially unfolded lysozyme, thus carrying a "memory" of the original folded protein precursor. We also report the structure of hen egg-white lysozyme irreversible amyloids at 3.2 Å resolution, revealing another canonical amyloid fold, and reaffirming that irreversible amyloids undergo a complete conversion of the native protein into the cross-β structure. By combining atomic force microscopy, cryo-electron microscopy and solid-state NMR, we show that a full unfolding of the native protein precursor is a requirement for establishing irreversible amyloid fibrils.

Universal cold RNA phase transitions

RNA's diversity of structures and functions impacts all life forms since primordia. We use calorimetric force spectroscopy to investigate RNA folding landscapes in previously unexplored low-temperature conditions. We find that Watson-Crick RNA hairpins, the most basic secondary structure elements, undergo a glass-like transition below [Formula: see text]C where the heat capacity abruptly changes and the RNA folds into a diversity of misfolded structures. We hypothesize that an altered RNA biochemistry, determined by sequence-independent ribose-water interactions, outweighs sequence-dependent base pairing. The ubiquitous ribose-water interactions lead to universal RNA phase transitions below TG, such as maximum stability at [Formula: see text]C where water density is maximum, and cold denaturation at [Formula: see text]C. RNA cold biochemistry may have a profound impact on RNA function and evolution.

Structural basis of NEAT1 lncRNA maturation and menRNA instability.

NEAT1 long noncoding RNA orchestrates paraspeckle assembly and impacts tumorigenesis, fertility and immunity. Its maturation requires RNase P cleavage yielding an unstable transfer RNA-like multiple endocrine neoplasia-β tRNA-like transcript (menRNA) due to CCACCA addition. Here we report the crystal structure of human menRNA, which partially mimics tRNAs to drive RNase P and ELAC2 processing. Biophysical analyses uncover an RNA-centric, riboswitch-like mechanism whereby the nascent CCA reshapes the RNA folding landscape and propels a spontaneous conformational isomerization that directs repeat CCA addition, marking the menRNA and defective tRNAs for degradation.

Gene regulatory landscape of cerebral cortex folding.

Folding of the cerebral cortex is a key aspect of mammalian brain development and evolution, and defects are linked to severe neurological disorders. Primary folding occurs in highly stereotyped patterns that are predefined in the cortical germinal zones by a transcriptomic protomap. The gene regulatory landscape governing the emergence of this folding protomap remains unknown. We characterized the spatiotemporal dynamics of gene expression and active epigenetic landscape (H3K27ac) across prospective folds and fissures in ferret. Our results show that the transcriptomic protomap begins to emerge at early embryonic stages, and it involves cell-fate signaling pathways. The H3K27ac landscape reveals developmental cell-fate restriction and engages known developmental regulators, including the transcription factor Cux2. Manipulating Cux2 expression in cortical progenitors changed their proliferation and the folding pattern in ferret, caused by selective transcriptional changes as revealed by single-cell RNA sequencing analyses. Our findings highlight the key relevance of epigenetic mechanisms in defining the patterns of cerebral cortex folding.

The physical and evolutionary energy landscapes of devolved protein sequences corresponding to pseudogenes

Protein evolution is guided by structural, functional, and dynamical constraints ensuring organismal viability. Pseudogenes are genomic sequences identified in many eukaryotes that lack translational activity due to sequence degradation and thus over time have undergone "devolution." Previously pseudogenized genes sometimes regain their protein-coding function, suggesting they may still encode robust folding energy landscapes despite multiple mutations. We study both the physical folding landscapes of protein sequences corresponding to human pseudogenes using the Associative Memory, Water Mediated, Structure and Energy Model, and the evolutionary energy landscapes obtained using direct coupling analysis (DCA) on their parent protein families. We found that generally mutations that have occurred in pseudogene sequences have disrupted their native global network of stabilizing residue interactions, making it harder for them to fold if they were translated. In some cases, however, energetic frustration has apparently decreased when the functional constraints were removed. We analyzed this unexpected situation for Cyclophilin A, Profilin-1, and Small Ubiquitin-like Modifier 2 Protein. Our analysis reveals that when such mutations in the pseudogene ultimately stabilize folding, at the same time, they likely alter the pseudogenes' former biological activity, as estimated by DCA. We localize most of these stabilizing mutations generally to normally frustrated regions required for binding to other partners.

Bilinear optimization of protein structure prediction: An exact approach via AB off-lattice model

Protein structure prediction (PSP) remains a central challenge in computational biology due to its inherent complexity and high dimensionality. While numerous heuristic approaches have appeared in the literature, their success varies. The AB off-lattice model, which characterizes proteins as sequences of A (hydrophobic) and B (hydrophilic) beads, presents a simplified perspective on PSP. This work presents a mathematical optimization-based methodology capitalizing on the off-lattice AB model. Dissecting the inherent non-linearities of the energy landscape of protein folding allowed for formulating the PSP as a bilinear optimization problem. This formulation was achieved by introducing auxiliary variables and constraints that encapsulate the nuanced relationship between the protein’s conformational space and its energy landscape. The proposed bilinear model exhibited notable accuracy in pinpointing the global minimum energy conformations on a benchmark dataset presented by the Protein Data Bank (PDB). Compared to traditional heuristic-based methods, this bilinear approach yielded exact solutions, reducing the likelihood of local minima entrapment. This research highlights the potential of reframing the traditionally non-linear protein structure prediction problem into a bilinear optimization problem through the off-lattice AB model. Such a transformation offers a route toward methodologies that can determine the global solution, challenging current PSP paradigms. Exploration into hybrid models, merging bilinear optimization and heuristic components, might present an avenue for balancing accuracy with computational efficiency.

Mechanical Stability and Unfolding Pathways of Parallel Tetrameric G-Quadruplexes Probed by Pulling Simulations.

Guanine quadruplex (GQ) is a noncanonical nucleic acid structure formed by guanine-rich DNA and RNA sequences. Folding of GQs is a complex process, where several aspects remain elusive, despite being important for understanding structure formation and biological functions of GQs. Pulling experiments are a common tool for acquiring insights into the folding landscape of GQs. Herein, we applied a computational pulling strategy─steered molecular dynamics (SMD) simulations─in combination with standard molecular dynamics (MD) simulations to explore the unfolding landscapes of tetrameric parallel GQs. We identified anisotropic properties of elastic conformational changes, unfolding transitions, and GQ mechanical stabilities. Using a special set of structural parameters, we found that the vertical component of pulling force (perpendicular to the average G-quartet plane) plays a significant role in disrupting GQ structures and weakening their mechanical stabilities. We demonstrated that the magnitude of the vertical force component depends on the pulling anchor positions and the number of G-quartets. Typical unfolding transitions for tetrameric parallel GQs involve base unzipping, opening of the G-stem, strand slippage, and rotation to cross-like structures. The unzipping was detected as the first and dominant unfolding event, and it usually started at the 3'-end. Furthermore, results from both SMD and standard MD simulations indicate that partial spiral conformations serve as a transient ensemble during the (un)folding of GQs.

The Mechanism of Folding of Human Frataxin in Comparison to the Yeast Homologue – Broad Energy Barriers and the General Properties of the Transition State

The funneled energy landscape theory suggests that the folding pathway of homologous proteins should converge at the late stages of folding. In this respect, proteins displaying a broad energy landscape for folding are particularly instructive, allowing inferring both the early, intermediate and late stages of folding. In this paper we explore the folding mechanisms of human frataxin, an essential mitochondrial protein linked to the neurodegenerative disorder Friedreich's ataxia. Building upon previous studies on the yeast homologue, the folding pathway of human frataxin is thoroughly examined, revealing a mechanism implying the presence of a broad energy barrier, reminiscent of the yeast counterpart. Through an extensive site-directed mutagenesis, we employed a Φ -value analysis to map native-like contacts in the folding transition state. The presence of a broad energy barrier facilitated the exploration of such contacts in both early and late folding events. We compared results from yeast and human frataxin providing insights into the impact of native topology on the folding mechanism and elucidating the properties of the underlying free energy landscape. The findings are discussed in the context of the funneled energy landscape theory of protein folding.

ELViM: Exploring Biomolecular Energy Landscapes through Multidimensional Visualization.

Molecular dynamics (MD) simulations provide a powerful means of exploring the dynamic behavior of biomolecular systems at the atomic level. However, analyzing the vast data sets generated by MD simulations poses significant challenges. This article discusses the energy landscape visualization method (ELViM), a multidimensional reduction technique inspired by the energy landscape theory. ELViM transcends one-dimensional representations, offering a comprehensive analysis of the effective conformational phase space without the need for predefined reaction coordinates. We apply the ELViM to study the folding landscape of the antimicrobial peptide Polybia-MP1, showcasing its versatility in capturing complex biomolecular dynamics. Using dissimilarity matrices and a force-scheme approach, the ELViM provides intuitive visualizations, revealing structural correlations and local conformational signatures. The method is demonstrated to be adaptable, robust, and applicable to various biomolecular systems.

Comprehensive perspective towards the management of proteinopathies by elucidating protein misfolding and aggregation.

Protein misfolding and aggregation is the phenomenon of the generic propensity of proteins, considered as a dark side of the protein world, and its exact mechanism is still not deciphered. Understanding the complexity of protein aggregation is currently the primary apprehension and challenge in biology and medicine due to their association with various debilitating human proteinopathies and neurodegenerative diseases. The mechanism of protein aggregation, associated diseases, and the development of efficient therapeutic strategies against these diseases are very challenging. These diseases are caused by different proteins, each protein with different mechanisms and consisting of various microscopic phases or events. These microscopic steps are functioning on different timescales during aggregation. Here, we highlighted the different features and current trends in protein aggregation. The study thoroughly recapitulates the various factors influencing, possible causes, types of aggregates and aggregation, their different proposed mechanisms, and the methods used to study the aggregation. Additionally, the formation and elimination of misfolded or aggregated proteins in the cell, the role of the ruggedness of the protein folding landscape in protein aggregation, proteinopathies, and the challenges for their prevention are comprehensively elucidated. A holistic understanding of different aspects of aggregation, molecular steps governing the various features of protein quality control, and crucial queries about the modulation of these processes and their interactions with other systems in cellular protein quality control can be considered conducive to comprehending the mechanism, designing effective approaches towards prevention of protein aggregation, rationalizing the etiology and development of novel strategies against therapy and management of the proteinopathies.

A TeZla micromixer for interrogating the early and broad folding landscape of G-quadruplex via multistage velocity descending

Biomacromolecular folding kinetics involves fast folding events and broad timescales. Current techniques face limitations in either the required time resolution or the observation window. In this study, we developed the TeZla micromixer, integrating Tesla and Zigzag microstructures with a multistage velocity descending strategy. TeZla achieves a significant short mixing dead time (40 µs) and a wide time window covering four orders of magnitude (up to 300 ms). Using this unique micromixer, we explored the folding landscape of c-Myc G4 and its noncanonical-G4 derivatives with different loop lengths or G-vacancy sites. Our findings revealed that c-Myc can bypass folding intermediates and directly adopt a G4 structure in the cation-deficient buffer. Moreover, we found that the loop length and specific G-vacancy site could affect the folding pathway and significantly slow down the folding rates. These results were also cross-validated with real-time NMR and circular dichroism. In conclusion, TeZla represents a versatile tool for studying biomolecular folding kinetics, and our findings may ultimately contribute to the design of drugs targeting G4 structures.

Exploring the folding landscape of leptin: Insights into threading pathways

The discovery of new protein topologies with entanglements and loop-crossings have shown the impact of local amino acid arrangement and global three-dimensional structures. This phenomenon plays a crucial role in understanding how protein structure relates to folding and function, affecting the global stability, and biological activity. Protein entanglements encompassing knots and non-trivial topologies add complexity to their folding free energy landscapes. However, the initial native contacts driving the threading event for entangled proteins remains elusive. The Pierced Lasso Topology (PLT) represents an entangled topology where a covalent linker creates a loop in which the polypeptide backbone is threaded through. Compared to true knotted topologies, PLTs are simpler topologies where the covalent-loop persists in all conformations. In this work, the PLT protein leptin, is used to visualize and differentiate the preference for slipknotting over plugging transition pathways along the folding route. We utilize the Energy Landscape Visualization Method (ELViM), a multidimensional projection technique, to visualize and distinguish early threaded conformations that cannot be observed in an in vitro experiment. Critical contacts for the leptin threading mechanisms were identified where the competing pathways are determined by the formation of a hairpin loop in the unfolded basin. Thus, prohibiting the dominant slipknotting pathway. Furthermore, ELViM offers insights into distinct folding pathways associated with slipknotting and plugging providing a novel tool for de novo design and in vitro experiments with residue specific information of threading events in silico.

A General Framework to Interpret Hydrogen-Deuterium Exchange Native Mass Spectrometry of G-Quadruplex DNA.

G-quadruplexes (G4s) are secondary structures formed by guanine-rich oligonucleotides involved in various biological processes. However, characterizing G4s is challenging, because of their structural polymorphism. Here, we establish how hydrogen-deuterium exchange native mass spectrometry (HDX/MS) can help to characterize the G4 structures and dynamics in solution. We correlated the time range of G4 exchange to the number of guanines involved in the inner and outer tetrads. We also established relationships among exchange rates, numbers of tetrads and bound cations, and stability. The use of HDX/native MS allows for the determination of tetrads formed and assessment of G4 stability at a constant temperature. A key finding is that stable G4s exchange through local fluctuations (EX2 exchange), whereas less stable G4s also undergo exchange through partial or complete unfolding (EX1 exchange). Deconvolution of the bimodal isotope distributions resulting from EX1 exchange provides valuable insight into the kinetics of folding and unfolding processes and allows one to detect and characterize transiently unfolded intermediates, even if scarcely populated. HDX/native MS thus represents a powerful tool for a more comprehensive exploration of the folding landscapes of G4s.

Small-molecule correctors divert CFTR-F508del from ERAD by stabilizing sequential folding states.

Over 80% of people with cystic fibrosis (CF) carry the F508del mutation in the cystic fibrosis transmembrane conductance regulator (CFTR), a chloride ion channel at the apical plasma membrane (PM) of epithelial cells. F508del impairs CFTR folding causing it to be destroyed by endoplasmic reticulum associated degradation (ERAD). Small-molecule correctors, which act as pharmacological chaperones to divert CFTR-F508del from ERAD, are the primary strategy for treating CF, yet corrector development continues with only a rudimentary understanding of how ERAD targets CFTR-F508del. We conducted genome-wide CRISPR/Cas9 knockout screens to systematically identify the molecular machinery that underlies CFTR-F508del ERAD. Although the ER-resident ubiquitin ligase, RNF5 was the top E3 hit, knocking out RNF5 only modestly reduced CFTR-F508del degradation. Sublibrary screens in an RNF5 knockout background identified RNF185 as a redundant ligase and demonstrated that CFTR-F508del ERAD is robust. Gene-drug interaction experiments illustrated that correctors tezacaftor (VX-661) and elexacaftor (VX-445) stabilize sequential, RNF5-resistant folding states. We propose that binding of correctors to nascent CFTR-F508del alters its folding landscape by stabilizing folding states that are not substrates for RNF5-mediated ubiquitylation.

Folding correctors can restore CFTR posttranslational folding landscape by allosteric domain–domain coupling

The folding/misfolding and pharmacological rescue of multidomain ATP-binding cassette (ABC) C-subfamily transporters, essential for organismal health, remain incompletely understood. The ABCC transporters core consists of two nucleotide binding domains (NBD1,2) and transmembrane domains (TMD1,2). Using molecular dynamic simulations, biochemical and hydrogen deuterium exchange approaches, we show that the mutational uncoupling or stabilization of NBD1-TMD1/2 interfaces can compromise or facilitate the CFTR(ABCC7)-, MRP1(ABCC1)-, and ABCC6-transporters posttranslational coupled domain-folding in the endoplasmic reticulum. Allosteric or orthosteric binding of VX-809 and/or VX-445 folding correctors to TMD1/2 can rescue kinetically trapped CFTR posttranslational folding intermediates of cystic fibrosis (CF) mutants of NBD1 or TMD1 by global rewiring inter-domain allosteric-networks. We propose that dynamic allosteric domain-domain communications not only regulate ABCC-transporters function but are indispensable to tune the folding landscape of their posttranslational intermediates. These allosteric networks can be compromised by CF-mutations, and reinstated by correctors, offering a framework for mechanistic understanding of ABCC-transporters (mis)folding.

Co-translational formation of disulfides guides folding of the SARS-CoV-2 receptor binding domain

Many secreted proteins, including viral proteins, contain multiple disulfide bonds. How disulfide formation is coupled to protein folding in the cell remains poorly understood at the molecular level. Here, we combine experiment and simulation to address this question as it pertains to the SARS-CoV-2 receptor binding domain (RBD). We show that the RBD can only refold reversibly if its native disulfides are present before folding. But in their absence, the RBD spontaneously misfolds into a nonnative, molten-globule-like state that is structurally incompatible with complete disulfide formation and that is highly prone to aggregation. Thus, the RBD native structure represents a metastable state on the protein’s energy landscape with reduced disulfides, indicating that nonequilibrium mechanisms are needed to ensure native disulfides form before folding. Our atomistic simulations suggest that this may be achieved via co-translational folding during RBD secretion into the endoplasmic reticulum. Namely, at intermediate translation lengths, native disulfide pairs are predicted to come together with high probability, and thus, under suitable kinetic conditions, this process may lock the protein into its native state and circumvent highly aggregation-prone nonnative intermediates. This detailed molecular picture of the RBD folding landscape may shed light on SARS-CoV-2 pathology and molecular constraints governing SARS-CoV-2 evolution.

The "Beacon" Structural Model of Protein Folding: Application for Trp-Cage in Water.

Protein folding is a process in which a polypeptide must undergo folding process to obtain its three-dimensional structure. Thermodynamically, it is a process of enthalpy to overcome the loss of conformational entropy in folding. Folding is primarily related to hydrophobic interactions and intramolecular hydrogen bondings. During folding, hydrophobic interactions are regarded to be the driving forces, especially in the initial structural collapse of a protein. Additionally, folding is guided by the strong interactions within proteins, such as intramolecular hydrogen bondings related to the α-helices and β-sheets of proteins. Therefore, a protein is divided into the folding key (FK) regions related to intramolecular hydrogen bondings and the non-folding key (non-FK) regions. Various conformations are expected for FK and non-FK regions. Different from non-FK regions, it is necessary for FK regions to form the specific conformations in folding, which are regarded as the necessary folding pathways (or "beacons"). Additionally, sequential folding is expected for the FK regions, and the intermediate state is found during folding. They are reflected on the local basins in the free energy landscape (FEL) of folding. To demonstrate the structural model, molecular dynamics (MD) simulations are conducted on the folding pathway of the TRP-cage in water.