Native Topology Research Articles

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.

Large-scale quantum approximate optimization on nonplanar graphs with machine learning noise mitigation

Quantum computers are increasing in size and quality but are still very noisy. Error mitigation extends the size of the quantum circuits that noisy devices can meaningfully execute. However, state-of-the-art error mitigation methods are hard to implement and the limited qubit connectivity in superconducting qubit devices restricts most applications to the hardware's native topology. Here we show a quantum approximate optimization algorithm (QAOA) on nonplanar random regular graphs with up to 40 nodes enabled by a machine learning-based error mitigation. We use a swap network with careful decision-variable-to-qubit mapping and a feed-forward neural network to optimize a depth-two QAOA on up to 40 qubits. We observe a meaningful parameter optimization for the largest graph which requires running quantum circuits with 958 two-qubit gates. Our paper emphasizes the need to mitigate samples, and not only expectation values, in quantum approximate optimization. These results are a step towards executing quantum approximate optimization at a scale that is not classically simulable. Reaching such system sizes is key to properly understanding the true potential of heuristic algorithms like QAOA. Published by the American Physical Society 2024

Viral capsid structural assembly governs the reovirus binding interface to NgR1.

Understanding the mechanisms underlying viral entry is crucial for controlling viral diseases. In this study, we investigated the interactions between reovirus and Nogo-receptor 1 (NgR1), a key mediator of reovirus entry into the host central nervous system. NgR1 exhibits a unique bivalent interaction with the reovirus capsid, specifically binding at the interface between adjacent heterohexamers arranged in a precise structural pattern on the curved virus surface. Using single-molecule techniques, we explored for the first time how the capsid molecular architecture and receptor polymorphism influence virus binding. We compared the binding affinities of human and mouse NgR1 to reovirus μ1/σ3 proteins in their isolated form, self-assembled in 2D capsid patches, and within the native 3D viral topology. Our results underscore the essential role of the concave side of NgR1 and emphasize that the spatial organization and curvature of the virus are critical determinants of the stability of the reovirus-NgR1 complex. This study highlights the importance of characterizing interactions in physiologically relevant spatial configurations, providing precise insights into virus-host interactions and opening new avenues for therapeutic interventions against viral infections.

The function of the conserved “non-functional” residues in apomyoglobin is to provide and preserve the correct protein topology

In this paper the answer to O. B. Ptitsyn’s question “What is the role of conserved non-functional residues in apomyoglobin” is presented, which is based on the research results of three laboratories. The role of conserved non-functional apomyoglobin residues in formation of native topology in the molten globule state of this protein is revealed. This fact allows suggesting that the conserved non-functional residues in this protein are indispensable for fixation and maintaining main elements of the correct topology of its secondary structure in the intermediate state. The correct topology is a native element in the intermediate state of the protein.

Function of the Conserved Non-Functional Residues in Apomyoglobin - to Determine and to Preserve Correct Topology of the Protein.

In this paper the answer to O. B. Ptitsyn's question "What is the role of conserved non-functional residues in apomyoglobin" is presented, which is based on the research results of three laboratories. The role of conserved non-functional apomyoglobin residues in formation of native topology in the molten globule state of this protein is revealed. This fact allows suggesting that the conserved non-functional residues in this protein are indispensable for fixation and maintaining main elements of the correct topology of its secondary structure in the intermediate state. The correct topology is a native element in the intermediate state of the protein.

Combining Surface-Induced Dissociation and Charge Detection Mass Spectrometry to Reveal the Native Topology of Heterogeneous Protein Complexes.

Charge detection mass spectrometry (CDMS) enables the direct mass measurement of heterogeneous samples on the megadalton scale, as the charge state for a single ion is determined simultaneously with the mass-to-charge ratio (m/z). Surface-induced dissociation (SID) is an effective activation method to dissociate non-intertwined, non-covalent protein complexes without extensive gas-phase restructuring, producing various subcomplexes reflective of the native protein topology. Here, we demonstrate that using CDMS after SID on an Orbitrap platform offers subunit connectivity, topology, proteoform information, and relative interfacial strengths of the intact macromolecular assemblies. SID dissects the capsids (∼3.7 MDa) of adeno-associated viruses (AAVs) into trimer-containing fragments (3mer, 6mer, 9mer, 15mer, etc.) that can be detected by the individual ion mass spectrometry (I2MS) approach on Orbitrap instruments. SID coupled to CDMS provides unique structural insights into heterogeneous assemblies that are not readily obtained by traditional MS measurements.

Comparative analysis of the structural dynamics of the Doppel protein and the C-terminus of the cellular prion protein.

The Doppel protein is the closest related protein on the phylogenetic tree to the prion protein. While the misfolding and aggregation of the prion protein is the hallmark of prion diseases, there is no reported evidence of an equivalent pathological process for the Doppel protein. Although the two proteins share only 25% sequence similarity, the folded C-terminus of the prion protein demonstrates a consistent topology with the Doppel protein. Despite the resemblance in topology, previous studies suggest that the Doppel protein has a higher energy barrier against misfolding than prion protein. However, the factors that mold the energy barrier remain unknown. Our goal is to decipher the role of structural dynamics and primary residue sequence of the native fold in shaping the misfolding energy barrier of each protein. Understanding the driving forces that stabilize similar native topologies will provide insight into subtle interactions that potentially trigger pathological prion protein misfolding. To perform a comparative analysis of the structural dynamics of the proteins, we used structural bioinformatics techniques. Our preliminary results indicate that the pattern of backbone local mobility of both proteins is similar: a flexible α-helix 1, and a somewhat rigid cluster that includes the β-sheets and α-helices 2 and 3. We also observed that the main modes of deformations are qualitatively similar between the two proteins. We will discuss the key features of the residue connectivity that determine the common topology despite differences in primary structure and propose target druggable residue interactions that may prevent prion protein misfolding.

Graph identification of proteins in tomograms (GRIP-Tomo).

In this study, we present a method of pattern mining based on network theory that enables the identification of protein structures or complexes from synthetic volume densities, without the knowledge of predefined templates or human biases for refinement. We hypothesized that the topological connectivity of protein structures is invariant, and they are distinctive for the purpose of protein identification from distorted data presented in volume densities. Three-dimensional densities of a protein or a complex from simulated tomographic volumes were transformed into mathematical graphs as observables. We systematically introduced data distortion or defects such as missing fullness of data, the tumbling effect, and the missing wedge effect into the simulated volumes, and varied the distance cutoffs in pixels to capture the varying connectivity between the density cluster centroids in the presence of defects. A similarity score between the graphs from the simulated volumes and the graphs transformed from the physical protein structures in point data was calculated by comparing their network theory order parameters including node degrees, betweenness centrality, and graph densities. By capturing the essential topological features defining the heterogeneous morphologies of a network, we were able to accurately identify proteins and homo-multimeric complexes from 10 topologically distinctive samples without realistic noise added. Our approach empowers future developments of tomogram processing by providing pattern mining with interpretability, to enable the classification of single-domain protein native topologies as well as distinct single-domain proteins from multimeric complexes within noisy volumes.

Metal-binding and circular permutation-dependent thermodynamic and kinetic stability of azurin.

Native topology is known to determine the folding kinetics and the energy landscape of proteins. Furthermore, the circular permutation (CP) of proteins alters the order of the secondary structure connectivity while retaining the three-dimensional structure, making it an elegant and powerful approach to altering native topology. Previous studies elucidated the influence of CP in proteins with different folds such as Greek key β-barrel, β-sandwich, β-α-β, and all α-Greek key. CP mainly affects the protein stability and unfolding kinetics, while folding kinetics remains mostly unaltered. However, the effect of CP on metalloproteins is yet to be elaborately studied. The active site of metalloproteins poses an additional complexity in studying protein folding. Here, we investigate a CP variant (cpN42) of azurin-in both metal-free and metal-bound (holo) forms. As observed earlier in other proteins, apo-forms of wild-type (WT) and cpN42 fold with similar rates. In contrast, zinc-binding accelerates the folding of WT but decelerates the folding of cpN42. On zinc-binding, the spontaneous folding rate of WT increases by >250 times that of cpN42, which is unprecedented and the highest for any CP to date. On the other hand, zinc-binding reduces the spontaneous unfolding rate of cpN42 by ~100 times, making the WT and CP azurins unfold at similar rates. Our study demonstrates metal binding as a novel way to modulate the unfolding and folding rates of CPs compared to their WT counterparts. We hope our study increases the understanding of the effect of CP on the folding mechanism and energy landscape of metalloproteins.

Structural visualization of the tubulin folding pathway directed by human chaperonin TRiC/CCT

The ATP-dependent ring-shaped chaperonin TRiC/CCT is essential for cellular proteostasis. To uncover why some eukaryotic proteins can only fold with TRiC assistance, we reconstituted the folding of β-tubulin using human prefoldin and TRiC. We find unstructured β-tubulin is delivered by prefoldin to the open TRiC chamber followed by ATP-dependent chamber closure. Cryo-EM resolves four near-atomic-resolution structures containing progressively folded β-tubulin intermediates within the closed TRiC chamber, culminating in native tubulin. This substrate folding pathway appears closely guided by site-specific interactions with conserved regions in the TRiC chamber. Initial electrostatic interactions between the TRiC interior wall and both the folded tubulin N domain and its C-terminal E-hook tail establish the native substrate topology, thus enabling C-domain folding. Intrinsically disordered CCT C termini within the chamber promote subsequent folding of tubulin's core and middle domains and GTP-binding. Thus, TRiC's chamber provides chemical and topological directives that shape the folding landscape of its obligate substrates.

Molecular landscape of BoNT/B bound to a membrane-inserted synaptotagmin/ganglioside complex.

Botulinum neurotoxin serotype B (BoNT/B) uses two separate protein and polysialoglycolipid-binding pockets to interact with synaptotagmin 1/2 and gangliosides. However, an integrated model of BoNT/B bound to its neuronal receptors in a native membrane topology is still lacking. Using a panel of in silico and experimental approaches, we present here a new model for BoNT/B binding to neuronal membranes, in which the toxin binds to a preassembled synaptotagmin-ganglioside GT1b complex and a free ganglioside allowing a lipid-binding loop of BoNT/B to interact with the glycone part of the synaptotagmin-associated GT1b. Furthermore, our data provide molecular support for the decrease in BoNT/B sensitivity in Felidae that harbor the natural variant synaptotagmin2-N59Q. These results reveal multiple interactions of BoNT/B with gangliosides and support a novel paradigm in which a toxin recognizes a protein/ganglioside complex.

Molecular Insight into the High Thermal Stability of Metalloprotein Azurin.

We investigate the events characterizing the steps of the unfolding pathway of blue copper metalloprotein azurin using replica exchange molecular dynamics (REMD). Our studies show that the unfolding of azurin begins with the melting of α-helix and β-sheets II and V. This is followed by the melting of other β-sheets and the exposure of hydrophobic protein core to the solvent, resulting in disruptions of its tertiary structure. Free energy surfaces constructed at different temperatures portray different basins that signify the stability of different melted structures in the unfolding process. The contact maps at different temperatures reveal that the strong hydrophobic interaction within the core of the protein is the vital force that renders high stability to this protein. Analysis of the individual β-sheets by looking into their amino acid sequence shows that β-sheets with charged side chains on the surface melt fast compared to others. The β-barrel of azurin is able to dynamically rearrange, and it helps the protein to preserve its hydrophobic core, holding back the native topology from melting fast. B-factor analysis shows that residues of β-sheets III, IV, and VII deviate less from their initial structure at the transition temperature.

LPTD: a novel linear programming-based topology determination method for cryo-EM maps.

Topology determination is one of the most important intermediate steps toward building the atomic structure of proteins from their medium-resolution cryo-electron microscopy (cryo-EM) map. The main goal in the topology determination is to identify correct matches (i.e. assignment and direction) between secondary structure elements (SSEs) (α-helices and β-sheets) detected in a protein sequence and cryo-EM density map. Despite many recent advances in molecular biology technologies, the problem remains a challenging issue. To overcome the problem, this article proposes a linear programming-based topology determination (LPTD) method to solve the secondary structure topology problem in three-dimensional geometrical space. Through modeling of the protein's sequence with the aid of extracting highly reliable features and a distance-based scoring function, the secondary structure matching problem is transformed into a complete weighted bipartite graph matching problem. Subsequently, an algorithm based on linear programming is developed as a decision-making strategy to extract the true topology (native topology) between all possible topologies. The proposed automatic framework is verified using 12 experimental and 15 simulated α-β proteins. Results demonstrate that LPTD is highly efficient and extremely fast in such a way that for 77% of cases in the dataset, the native topology has been detected in the first rank topology in <2 s. Besides, this method is able to successfully handle large complex proteins with as many as 65 SSEs. Such a large number of SSEs have never been solved with current tools/methods. The LPTD package (source code and data) is publicly available at https://github.com/B-Behkamal/LPTD. Moreover, two test samples as well as the instruction of utilizing the graphical user interface have been provided in the shared readme file. Supplementary data are available at Bioinformatics online.

Protein sequence design with a learned potential

The task of protein sequence design is central to nearly all rational protein engineering problems, and enormous effort has gone into the development of energy functions to guide design. Here, we investigate the capability of a deep neural network model to automate design of sequences onto protein backbones, having learned directly from crystal structure data and without any human-specified priors. The model generalizes to native topologies not seen during training, producing experimentally stable designs. We evaluate the generalizability of our method to a de novo TIM-barrel scaffold. The model produces novel sequences, and high-resolution crystal structures of two designs show excellent agreement with in silico models. Our findings demonstrate the tractability of an entirely learned method for protein sequence design.

3D TOPOLOGICAL SUPPORT IN SPATIAL DATABASES: AN OVERVIEW

Abstract. The storage of spatial data that consists of spatial and non-spatial properties requires a database management system that possesses spatial functions that can cater to the spatial characteristics of data. These characteristics include the geometrical shape, topological and positional information. Parallel to how geometries describe the shape of an object, topological information is also an important spatial property which describes how the geometries in a space are related to each other. This information describes the connectivity, containment and adjacencies of spatial objects which are the foundation for more complex analysis such as navigation, data reconstruction, spatial queries and others. However, the topological support provided by spatial databases varies. This paper provided an overview on the current implementations of topological support in spatial databases such as ArcGIS, QGIS, PostgreSQL and others. The native topology in most spatial databases was found to be 2D topology maintained by 2D topology rules with limited representation of 3D topological relationships. Consequently, 3D objects represented by 2D topology had to be decomposed into objects of lower dimensions. Approaches to implement additional topological support for spatial databases included the use of topological data models, data structures, operators, and rules. 3D applications such as 3D cadastre required more detailed representations of topological information which required a more comprehensive 3D topological data model. Nonetheless, comprehensive preservation of topological information also mandates voluminous storage and higher computational efficiency. Thus, the appropriate 3D topological support should be provided in spatial databases to accurately represent 3D objects and meet 3D analysis requirements.

Structure-Based Epitope Design: Toward a Greater Antibody-SARS-CoV-2 RBD Affinity.

Efficient COVID-19 vaccines are widely acknowledged as the best way to end the global pandemic. SARS-CoV-2 receptor-binding domain (RBD) plays fundamental roles related to cell infection. Antibodies could be developed to target RBD and represent a potential approach for the neutralization of the virus. Epitopes used to produce antibodies are generally linear peptides and thus possess multiple confirmations that do not reflect the actual topology of the targeted part in the native protein. On the other hand, macrocyclic epitopes could constitute closer mimics of the native protein topology and, as such, could generate superior antibodies. In this study, we demonstrated the vital effect of the size and the three-dimensional shape of epitopes on the activity of the developed antibodies against the RBD of SARS-CoV-2. The molecular dynamics studies showed the greater stability of the cyclic epitopes compared with the linear counterparts, which was reflected in the affinity of the produced antibodies. The antibodies developed using macrocyclic epitopes showed superiority with respect to binding to RBD compared to antibodies formed from linear peptides. This study constitutes a roadmap for developing superior antibodies that could be used to inhibit the activity of SARS-CoV-2.

Variational Circuit Compiler for Quantum Error Correction

Quantum error correction is vital for implementing universal quantum computing. A key component is the encoding circuit that maps a product state of physical qubits into the encoded multipartite entangled logical state. Known methods are typically not 'optimal' either in terms of the circuit depth (and therefore the error burden) or the specifics of the target platform, i.e. the native gates and topology of a system. This work introduces a variational compiler for efficiently finding the encoding circuit of general quantum error correcting codes with given quantum hardware. Focusing on the noisy intermediate scale quantum regime, we show how to systematically compile the circuit following an optimising process seeking to minimise the number of noisy operations that are allowed by the noisy quantum hardware or to obtain the highest fidelity of the encoded state with noisy gates. We demonstrate our method by deriving novel encoders for logic states of the five qubit code and the seven qubit Steane code. We describe ways to augment the discovered circuits with error detection. Our method is applicable quite generally for compiling the encoding circuits of quantum error correcting codes.

Cell-extracellular matrix interactions in the fluidic phase direct the topology and polarity of self-organized epithelial structures.

IntroductionIn vivo, cells are surrounded by extracellular matrix (ECM). To build organs from single cells, it is generally believed that ECM serves as scaffolds to coordinate cell positioning and differentiation. Nevertheless, how cells utilize cell‐ECM interactions for the spatiotemporal coordination to different ECM at the tissue scale is not fully understood.MethodsHere, using in vitro assay with engineered MDCK cells expressing H2B‐mCherry (nucleus) and gp135/Podocalyxin‐GFP (apical marker), we show in multi‐dimensions that such coordination for epithelial morphogenesis can be determined by cell‐soluble ECM interaction in the fluidic phase.ResultsThe coordination depends on the native topology of ECM components such as sheet‐like basement membrane (BM) and type I collagen (COL) fibres: scaffold formed by BM (COL) facilitates a close‐ended (open‐ended) coordination that leads to the formation of lobular (tubular) epithelium. Further, cells form apicobasal polarity throughout the entire lobule/tubule without a complete coverage of ECM at the basal side, and time‐lapse two‐photon scanning imaging reveals the polarization occurring early and maintained through the lobular expansion. During polarization, gp135‐GFP was converged to the apical surface collectively in the lobular/tubular structures, suggesting possible intercellular communications. Under suspension culture, the polarization was impaired with multi‐lumen formation in the tubules, implying the importance of ECM biomechanical microenvironment.ConclusionOur results suggest a biophysical mechanism for cells to form polarity and coordinate positioning at tissue scale, and in engineering epithelium through cell‐soluble ECM interaction and self‐assembly.

Mapping Bone Surface Composition Using Real-Time Surface Tracked Micro-Raman Spectroscopy

The surface of bone tells a story – one that is worth a thousand words – of how it is built and how it is repaired. Chemical (i.e., composition) and physical (i.e., morphology) characteristics of the bone surface are analogous to a historical record of osteogenesis and provide key insights into bone quality. Analysis of bone chemistry is of particular relevance to the advancement of human health, cell biology, anthropology/archaeology, and biomedical engineering. Although scanning electron microscopy remains a popular and versatile technique to image bone across multiple length scales, limited chemical information can be obtained. Micro-Raman spectroscopy is a valuable tool for nondestructive chemical/compositional analysis of bone. However, signal integrity losses occur frequently during wide-field mapping of non-planar surfaces. Samples for conventional Raman imaging are, therefore, rendered planar through polishing or sectioning to ensure uniform signal quality. Here, we demonstrate ν₁ PO₄^3- and ν₁ CO₃^2- peak intensity losses where the sample surface and the plane of focus are offset by over 1–2 μm when underfocused and 2–3 μm when overfocused at 0.5–1 s integration time (15 mW, 633 nm laser). A technique is described for mapping the composition of the inherently irregular/non-planar surface of bone. The challenge posed by the native topology characteristic of this unique biological system is circumvented via real-time focus-tracking based on laser focus optimization by continuous closed-loop feedback. At the surface of deproteinized and decellularized/defatted sheep tibial cortical bone, regions of interest up to 1 mm² were scanned at micrometer and submicrometer resolution. Despite surface height deviations exceeding 100 μm, it is possible to seamlessly probe local gradients in organic and inorganic constituents of the extracellular matrix as markers of bone metabolism and bone turnover, blood vessels and osteocyte lacunae, and the rope-like mineralized bundles that comprise the mineral phase at the bone surface.

Decellularized Human Lung Scaffolds as Complex Three-Dimensional Tissue Culture Models to Study Functional Behavior of Fibroblasts.

In vitro culturing of cells in two-dimensional (2D) environments is a widespread used methodology in biomedical research. Most commonly, cells are cultured on artificial plastic dish surfaces, which lead to abnormal functional behaviors, as plastic does not reflect the native microenvironment found in vivo or in situ. Therefore, a multitude of three-dimensional (3D) cell culture systems were developed in the past years, which aim to bridge the gap between 2D cell culture dishes and the in vivo situation. One of the more recent development in the field, the generation of viable precision-cut tissue slices from various organs emerged as an exciting approach to study complex interactions and biological processes ex vivo in 3D. Decellularization of such tissue slices leads to the removal of all functional cells, and leaves behind a scaffold of extracellular matrix (ECM), which closely recapitulates the molecular composition, mechanical properties, topology, and microarchitecture of native ECM. Subsequently, decellularized precision-cut lung slices (PCLS), also called 3D lung tissue culture (3D-LTCs), can be successfully reseeded with a variety of cell types, including fibroblasts, which attach to and engraft into the matrix. Here, we describe the generation of PCLS from resected human lung tissue and their decellularization and recellularization with primary human fibroblasts. This novel 3D tissue culture model allows for various functional studies of fibroblast behavior on native ECM composition and topology.