Spontaneous nucleation and fast aggregate-dependent proliferation of α-synuclein aggregates within liquid condensates at neutral pH

The aggregation of α-synuclein into amyloid fibrils has been under scrutiny in recent years because of its association with Parkinson’s disease. This process can be triggered by a lipid-dependent nucleation process, and the resulting aggregates can proliferate through secondary nucleation under acidic pH conditions. It has also been recently reported that the aggregation of α-synuclein may follow an alternative pathway, which takes place within dense liquid condensates formed through phase separation. The microscopic mechanism of this process, however, remains to be clarified. Here, we used fluorescence-based assays to enable a kinetic analysis of the microscopic steps underlying the aggregation process of α-synuclein within liquid condensates. Our analysis shows that at pH 7.4, this process starts with spontaneous primary nucleation followed by rapid aggregate-dependent proliferation. Our results thus reveal the microscopic mechanism of α-synuclein aggregation within condensates through the accurate quantification of the kinetic rate constants for the appearance and proliferation of α-synuclein aggregates at physiological pH.

Parkinson’s disease is the most common neurodegenerative movement disorder (1, 2). A distinctive pathophysiological signature of this disease is the presence of abnormal intraneuronal protein deposits known as Lewy bodies (3, 4). One of the main components of Lewy bodies is α-synuclein (5), a peripheral membrane protein highly abundant at neuronal synapses (6, 7) and genetically linked with Parkinson’s disease (8, 9). This 140-residue disordered protein can be subdivided into three domains, an amphipathic N-terminal region (amino acids 1 to 60), a central hydrophobic region (non-amyloid-β component, or NAC, amino acids 61 to 95), and an acidic proline-rich C-terminal tail (amino acids 96 to 140) (7). Although α-synuclein aggregation is characteristic of Parkinson’s disease and related synucleinopathies, the corresponding mechanism and its possible pathological role in disease are not yet fully understood.Generally, the aggregation process of proteins proceeds through a series of interconnected microscopic steps, including primary nucleation, elongation, and secondary nucleation (10, 11). During primary nucleation, the self-assembly of proteins from their native, monomeric form leads to the formation of oligomeric species, an event that may occur in solution or on surfaces including biological membranes (12, 13). The formation of these oligomers is typically a slow event governed by high kinetic barriers (10, 11). Once formed, the oligomers may convert into ordered assemblies rich in β structure, which are capable of further growth into fibrillar aggregates (14). In many cases, the surfaces of existing fibrillar aggregates then further catalyze the formation of new oligomers (15, 16). This secondary nucleation process is typically characterized by the assembly of protein monomers on the surface of fibrils that eventually nucleate into new oligomeric species (15, 16). This autocatalytic mechanism generates rapid fibril proliferation (15).In the case of the aggregation process of α-synuclein, several key questions are still open, including two that we are addressing in this study. The first concerns whether there are cellular conditions under which α-synuclein can undergo spontaneous aggregation, and the second whether the proliferation of α-synuclein fibrils by aggregate-dependent feedback processes can take place at physiological pH. These questions are relevant because according to our current knowledge, α-synuclein aggregation does not readily take place spontaneously in the absence of contributing factors such as lipid membranes. Furthermore, secondary nucleation contributes significantly to the aggregation process only at acidic pH (13, 17). It thus remains challenging to rationalize the links between α-synuclein aggregation and Parkinson’s disease.To address this problem, we investigated whether it is possible to leverage the recent finding that α-synuclein can undergo a phase separation process resulting in the formation of dense liquid condensates (18–21). Phase separation has recently emerged as a general phenomenon associated with a wide variety of cellular functions (22–25) and closely linked with human disease (23, 26–29). This process has been reported for a wide range of proteins implicated in neurodegenerative conditions, including tau, fused in sarcoma (FUS), and TAR DNA binding protein 43 (TDP-43) (30–32). Since it has also been shown that protein aggregation can take place within liquid condensates (19, 26, 32–36), we asked whether it is possible to characterize at the microscopic level the condensate-induced aggregation mechanism of α-synuclein by determining the kinetic rate constants of the corresponding microscopic processes.To enable the accurate determination of the rate constants for the microscopic steps in α-synuclein aggregation within condensates, we developed fluorescence-based aggregation assays to monitor both the spontaneous aggregation of α-synuclein and the aggregation in the presence of aggregate seeds. Using these assays within the framework of a kinetic theory of protein aggregation (10, 11, 37), we show that α-synuclein can undergo spontaneous homogenous primary nucleation and fast aggregate-dependent proliferation within condensates at physiological pH.     

Inhibition of RAS-driven signaling and tumorigenesis with a pan-RAS monobody targeting the Switch I/II pocket

RAS mutants are major therapeutic targets in oncology with few efficacious direct inhibitors available. The identification of a shallow pocket near the Switch II region on RAS has led to the development of small-molecule drugs that target this site and inhibit KRAS(G12C) and KRAS(G12D). To discover other regions on RAS that may be targeted for inhibition, we have employed small synthetic binding proteins termed monobodies that have a strong propensity to bind to functional sites on a target protein. Here, we report a pan-RAS monobody, termed JAM20, that bound to all RAS isoforms with nanomolar affinity and demonstrated limited nucleotide-state specificity. Upon intracellular expression, JAM20 potently inhibited signaling mediated by all RAS isoforms and reduced oncogenic RAS-mediated tumorigenesis in vivo. NMR and mutation analysis determined that JAM20 bound to a pocket between Switch I and II, which is similarly targeted by low-affinity, small-molecule inhibitors, such as BI-2852, whose in vivo efficacy has not been demonstrated. Furthermore, JAM20 directly competed with both the RAF(RBD) and BI-2852. These results provide direct validation of targeting the Switch I/II pocket for inhibiting RAS-driven tumorigenesis. More generally, these results demonstrate the utility of tool biologics as probes for discovering and validating druggable sites on challenging targets.

Mutated in almost 20% of human cancers, the RAS GTPase is a major drug target in oncology (1). Its isoforms (K, H, and NRAS) are responsible for regulating cell growth and other critical cellular processes through their function as GTPases. To regulate signal activation, wild-type (WT) RAS is converted to the active (GTP-bound) state via a Guanine Nucleotide Exchange Factor and then converted to the inactive (GDP-bound) state with the help of a GTPase Accelerating Protein (GAP) (2–5). Active, GTP-bound RAS interacts with diverse proteins termed effectors to promote signaling (6–10). Although this activation mechanism is properly regulated under normal circumstances, oncogenic RAS tends to exhibit reduced sensitivity to GAP-mediated GTP hydrolysis, leading to extended signal activation (11, 12).Because of its prevalence in human cancers, there have been many attempts to inhibit oncogenic RAS-mediated signaling. Whereas attempts to directly inhibit RAS have been largely unsuccessful, the recent discovery of a pocket near the Switch II region (SII) and advancements in small-molecule chemistry have led to the successful development of mutant-specific RAS inhibitors that target this pocket. The SII pocket was only discovered when the RAS structure was determined with a tethered tool compound (13). Because of its dynamic nature, this pocket had remained undetected until this approach was used. This and other studies underscore the importance of developing tool ligands to discover new druggable sites on targets of interest (14).Since the discovery of the SII pocket, the development of small-molecule inhibitors, such as sotorasib, adagrasib, and MRTX1133, have demonstrated that it is possible to engage the Switch region and achieve high selectivity for mutant over WT RAS (13, 15–17). Although these breakthroughs demonstrate the efficacy of targeting the RAS SII pocket for inhibition, it is unclear whether these molecules can be further derivatized for targeting other RAS mutants (18–20). Thus, there remains a substantial need to identify additional sites on RAS that can be targeted for direct inhibition.Unlike small-molecule inhibitors, protein-based ligands are less reliant on deep pockets and can target relatively flat surfaces. Therefore, the development of peptides and synthetic proteins against RAS is generally less challenging than developing small molecules. Such reagents can be used as functional probes to identify sites on a target for inhibition. For example, synthetic proteins, such as monobodies, have been successfully developed against a diverse array of targets, including RAS, and tend to bind to underappreciated functional sites (21–28). Whereas inhibitors like sotorasib, adagrasib, and MRTX1133 bind near the Switch region of RAS, the monobody (Mb) NS1 marked the first inhibitor to bind to RAS outside of the Switch region (27). NS1 binds to the α4–β6–α5 region and inhibits signaling mediated by both KRAS and HRAS, demonstrating the feasibility of effectively inhibiting RAS-mediated signaling without targeting the Switch region. In addition to Mbs, other synthetic binding proteins, such as Designed Ankyrin Repeat Proteins (DARPins), have also been developed to identify regions on RAS for inhibition. KRAS-selective DARPins K13 and K19 have established the α3–loop 7–α4 region of KRAS as another site for RAS inhibition (29). These results demonstrate the utility of synthetic binding proteins to identify new sites on RAS that may be directly targeted for inhibition, ultimately with small molecules or via intracellular delivery of proteins.In this study, we set out to address whether other regions exist on RAS that may be targeted for inhibition. We report a pan-RAS Mb termed JAM20 that bound to RAS in both nucleotide states. Furthermore, it robustly inhibited RAS-mediated signaling and cell transformation both in vitro and in vivo. Despite its low sensitivity to the bound nucleotide, JAM20 targeted an epitope within the Switch I (SI)/SII region of RAS and inhibited RAS–RAF(RBD) interaction. JAM20 bound to a similar region as low-affinity, small-molecule inhibitors as well as other synthetic binding proteins, whose efficacy in vivo has not been established (30, 31), making intracellularly expressed JAM20 a surrogate for these molecules. Our findings offer additional support for targeting the SI/SII pocket and its vicinity for future therapeutic development.     

De novo designed protein inhibitors of amyloid aggregation and seeding

Neurodegenerative diseases are characterized by the pathologic accumulation of aggregated proteins. Known as amyloid, these fibrillar aggregates include proteins such as tau and amyloid-β (Aβ) in Alzheimer’s disease (AD) and alpha-synuclein (αSyn) in Parkinson’s disease (PD). The development and spread of amyloid fibrils within the brain correlates with disease onset and progression, and inhibiting amyloid formation is a possible route toward therapeutic development. Recent advances have enabled the determination of amyloid fibril structures to atomic-level resolution, improving the possibility of structure-based inhibitor design. In this work, we use these amyloid structures to design inhibitors that bind to the ends of fibrils, “capping” them so as to prevent further growth. Using de novo protein design, we develop a library of miniprotein inhibitors of 35 to 48 residues that target the amyloid structures of tau, Aβ, and αSyn. Biophysical characterization of top in silico designed inhibitors shows they form stable folds, have no sequence similarity to naturally occurring proteins, and specifically prevent the aggregation of their targeted amyloid-prone proteins in vitro. The inhibitors also prevent the seeded aggregation and toxicity of fibrils in cells. In vivo evaluation reveals their ability to reduce aggregation and rescue motor deficits in Caenorhabditis elegans models of PD and AD.

The aberrant aggregation of proteins into amyloid fibrils is a hallmark of many neurodegenerative diseases, including Alzheimer’s disease (AD) and Parkinson’s disease (PD) (1). In AD, amyloid-β (Aβ) and tau amyloid fibrils comprise the extracellular amyloid plaques and intracellular neurofibrillary tangles, respectively, characteristic of disease progression (2). Likewise, intracellular Lewy bodies found in the neurons of patients with PD and dementia with Lewy bodies (DLB) are primarily composed of αSyn fibrils (3). There are currently no therapies capable of significantly slowing or stopping the progression of any of these diseases, and inhibition of fibril formation has become a major target for therapeutic development (4, 5). Amyloid fibrils are composed of repeating layers of β-strand–rich protein monomers stacked upon each other, forming β-sheets. The β-sheets interdigitate to form a stable fibril core through interactions known as steric zippers (6). Antiamyloid therapies have typically focused on small molecules that prevent aggregation or dissociate preexisting aggregates and antibodies that promote fibril clearance (7–9). An alternative approach is the design of molecules that bind to the ends of the growing fibrils, capping their growth and preventing the further addition of more protein monomers. This approach has been successfully used to design peptide-based inhibitors of tau, Aβ, and αSyn aggregation (10–14). This design strategy considers the atomic structures of fibrils, employing rational and computational design techniques to derive a peptide sequence complementary to the growing fibril surface.Since the initial designs of structure-based capping inhibitor peptides, many advances have been made in both the determination of amyloid protein structure, as well as in methods of protein design. The first atomic-resolution structures of amyloid fibrils determined by X-ray crystallography were restricted to small peptide segments ∼6 to 11 amino acids in length (15). The recent advent of cryoelectron microscopy (cryo-EM), microelectron diffraction (MicroED), and solid-state NMR (ssNMR) spectroscopy have enabled the determination of amyloid protein structures that were previously unsolvable (16–18). These techniques have been used to solve an ever-growing list of structures of both recombinantly derived fibrils (19–21) as well as fibrils directly extracted from patient tissue (22–29). These structures have provided key insights into fibril architecture and polymorphism in relation to disease.Like the structural knowledge of amyloid fibrils, the toolbox of protein structure prediction and design has been rapidly expanding in recent years (30, 31). Significant advances in algorithms and computing power have facilitated the de novo design of proteins with a variety of properties and functions, ranging from stability, pH sensitivity, to even logic operations, with vast potential for use in therapeutics, diagnostics, etc (32–36). While the underlying design principles of de novo generated proteins are becoming well established, examples of their direct application into biological systems are still limited. In this work, we use de novo protein design to create 35 to 50 residue miniproteins that bind to the growing ends of tau, αSyn, and Aβ fibrils. We target recently determined full-length atomic structures of each amyloid protein in our designs to generate miniproteins capable of inhibiting aggregation, seeding, and toxicity both in vitro and in vivo.     

Peptide dimer structure in an Aβ(1–42) fibril visualized with cryo-EM

Alzheimer’s disease (AD) is a fatal neurodegenerative disorder in humans and the main cause of dementia in aging societies. The disease is characterized by the aberrant formation of β-amyloid (Aβ) peptide oligomers and fibrils. These structures may damage the brain and give rise to cerebral amyloid angiopathy, neuronal dysfunction, and cellular toxicity. Although the connection between AD and Aβ fibrillation is extensively documented, much is still unknown about the formation of these Aβ aggregates and their structures at the molecular level. Here, we combined electron cryomicroscopy, 3D reconstruction, and integrative structural modeling methods to determine the molecular architecture of a fibril formed by Aβ(1–42), a particularly pathogenic variant of Aβ peptide. Our model reveals that the individual layers of the Aβ fibril are formed by peptide dimers with face-to-face packing. The two peptides forming the dimer possess identical tilde-shaped conformations and interact with each other by packing of their hydrophobic C-terminal β-strands. The peptide C termini are located close to the main fibril axis, where they produce a hydrophobic core and are surrounded by the structurally more flexible and charged segments of the peptide N termini. The observed molecular architecture is compatible with the general chemical properties of Aβ peptide and provides a structural basis for various biological observations that illuminate the molecular underpinnings of AD. Moreover, the structure provides direct evidence for a steric zipper within a fibril formed by full-length Aβ peptide.Amyloid fibrils are the terminal assembly states of the β-amyloid (Aβ) fibrillogenic pathway. They are responsible for the neuronal damage in cerebral amyloid angiopathy and form the core of Alzheimer’s disease (AD)-specific amyloid plaques (1, 2). These plaques can locally accumulate toxic Aβ oligomers and may be surrounded by halos of altered neuronal activity (2). Our understanding of Aβ fibril structures is limited because it is difficult to explain biochemical and biological properties of Aβ and its aggregates from current fibril models. First, why does the AD-specific extension of the Aβ C terminus from Aβ(1–40) to Aβ(1–42) yield a peptide variant that is more favorable for the aggregated state and, thus, more pathogenic (3)? Second, why do fibrils formed from these two peptides exhibit a limited capacity to form mixed fibrils in vitro (4)? Third, why do the charged residues Glu22 and Asp23 disturb the fibril state such that their genetic mutation accelerates fibril formation in vitro and leads to early onset familial AD in patients (5)? Lastly, why are fibrillation inhibitors particularly effective if they target the Aβ C terminus (6, 7), and how is oligomeric assembly of toxic intermediates reflected by the structure of the fibril (1, 3)?To address these questions, we determined the structure of an Aβ(1–42) fibril morphology by electron cryomicroscopy (cryo-EM). Cryo-EM is an established technique for visualizing the 3D structure of macromolecular assemblies at near-atomic resolution (8). The technique does not require crystals and is therefore particularly well suited for the study of polymorphic amyloid structures in solution. Cryo-EM has been applied to fibrils formed from SH3 domains (9), transthyretin fragments (10), β2-microglobulin (11), and Alzheimer’s Aβ peptide (12–14). Furthermore, recent cryo-EM reconstructions have identified a common protofilament substructure in Aβ(1–40) and Aβ(1–42) fibrils in which the cross-β repeats were formed by peptide dimers (12, 15).     

The guanine nucleotide exchange factor Ric-8A induces domain separation and Ras domain plasticity in Gαi1

Heterotrimeric G proteins are activated by exchange of GDP for GTP at the G protein alpha subunit (Gα), most notably by G protein-coupled transmembrane receptors. Ric-8A is a soluble cytoplasmic protein essential for embryonic development that acts as both a guanine nucleotide exchange factor (GEF) and a chaperone for Gα subunits of the i, q, and 12/13 classes. Previous studies demonstrated that Ric-8A stabilizes a dynamically disordered state of nucleotide-free Gα as the catalytic intermediate for nucleotide exchange, but no information was obtained on the structures involved or the magnitude of the structural fluctuations. In the present study, site-directed spin labeling (SDSL) together with double electron-electron resonance (DEER) spectroscopy is used to provide global distance constraints that identify discrete members of a conformational ensemble in the Gαi1:Ric-8A complex and the magnitude of structural differences between them. In the complex, the helical and Ras-like nucleotide-binding domains of Gαi1 pivot apart to occupy multiple resolved states with displacements as large as 25 Å. The domain displacement appears to be distinct from that observed in Gαs upon binding of Gs to the β₂ adrenergic receptor. Moreover, the Ras-like domain exhibits structural plasticity within and around the nucleotide-binding cavity, and the switch I and switch II regions, which are known to adopt different conformations in the GDP- and GTP-bound states of Gα, undergo structural rearrangements. Collectively, the data show that Ric-8A induces a conformationally heterogeneous state of Gαi and provide insight into the mechanism of action of a nonreceptor Gα GEF.Heterotrimeric G proteins are activated by exchange of GDP for GTP at the alpha subunit (Gα), a reaction with a high-activation energy barrier (1). Guanine dinucleotides and trinucleotides bind tightly to Gα with affinities in the low nanomolar range (2, 3), and contribute substantially to the overall stability of Gα tertiary structure. Indeed, nucleotide-free Gα exhibits properties characteristic of a molten globule (4). In cells, agonist-stimulated 7-transmembrane helical G protein-coupled receptors (GPCRs) catalyze nucleotide exchange from G protein heterotrimers, in which Gα•GDP is bound to a heterodimer of Gβ and Gγ subunits (5). The cytosolic proteins Ric-8A and Ric-8B, which are structurally unrelated to GPCRs, have been shown to have guanine nucleotide exchange (GEF) activity toward Gα•GDP subunits in the absence of Gβγ (6, 7), thus functionally activating the subunit. In Caenorhabditis elegans, Drosophila, and mouse, Ric-8 homologs have been shown to be essential for asymmetric cell division, where they are assumed to function as GEFs (8–12). Ric-8 proteins also promote efficient folding and membrane localization of certain Gα subunits (13, 14), and inhibit their ubiquitination and degradation (15, 16). With respect to these activities, Ric-8A acts specifically on Gα subunits of the i, q, and 12/13 classes, whereas Ric-8B is active toward Gαs (17).Gα subunits are composed of two structural domains (3). The Ras-like domain is homologous to guanine nucleotide-binding domains of the Ras superfamily. Within the Ras-like domain are three so-called switch segments that integrate catalytic (guanine nucleotide-binding and GTP hydrolysis) with regulatory function (effector regulation). The conformations of these peptide segments differ between the GTP and GDP-bound states of Gα (3). In crystals of Gαi1–nucleotide complexes, switch I and switch II are well-ordered in the GTP-bound state, but partially (switch I) or fully (switch II) disordered when GDP is bound (18, 19). Inserted into switch I of the Ras domain is a helical domain that is unique to the family of heterotrimeric G proteins. The helical domain flanks the guanine nucleotide-binding site and, while it makes few direct contacts with the nucleotide, shields it from solvent and may affect the rate of its dissociation (20, 21).We have shown that in the complex of nucleotide-free Gαi1 and Ric-8A, an intermediate in the nucleotide exchange reaction (6, 22), Gαi1 is conformationally heterogeneous and dynamic, but the structures involved and the magnitude of the structural fluctuations were not determined (4). The nucleotide-free Gαi1:Ric-8A complex is stable and can be readily isolated. In the present study, we used site-directed spin labeling (SDSL) and both continuous wave (CW) and double electron-electron resonance (DEER) (23, 24) spectroscopy to map sequence-specific structural and dynamical changes in Gαi1 upon complex formation with Ric-8A. The data reveal that binding of Ric-8A to Gαi1 induces structural heterogeneity due to new conformations in which the helical domain has pivoted away from the Ras-like domain, exposing the nucleotide-binding site to solvent, thus providing an escape (and entry) pathway for the nucleotide. A similar change is induced in Gαi1 upon formation of the nucleotide-free complex with the activated GPCR rhodopsin (20), but is distinctly different from that in the crystal structure of Gαs in the complex with β₂ adrenergic receptor (β2R) (25). In addition to the global changes in tertiary structure, binding of Ric-8A also triggers deformation within the Ras-like domain, particularly of structural elements that surround the nucleotide-binding pocket. Together, these changes reveal salient features of a mechanism underlying the GEF activity of Ric-8A.     

Threading single proteins through pores to compare their energy landscapes

Translocation of proteins is correlated with structural fluctuations that access conformational states higher in free energy than the folded state. We use electric fields at the solid-state nanopore to control the relative free energy and occupancy of different protein conformational states at the single-molecule level. The change in occupancy of different protein conformations as a function of electric field gives rise to shifts in the measured distributions of ionic current blockades and residence times. We probe the statistics of the ionic current blockades and residence times for three mutants of the λ-repressor family in order to determine the number of accessible conformational states of each mutant and evaluate the ruggedness of their free energy landscapes. Translocation becomes faster at higher electric fields when additional flexible conformations are available for threading through the pore. At the same time, folding rates are not correlated with ease of translocation; a slow-folding mutant with a low-lying intermediate state translocates faster than a faster-folding two-state mutant. Such behavior allows us to distinguish among protein mutants by selecting for the degree of current blockade and residence time at the pore. Based on these findings, we present a simple free energy model that explains the complementary relationship between folding equilibrium constants and translocation rates.

Cellular proteins perform their function through a variety of pathways that have been fine-tuned over millions of years of evolution. While remarkable progress in studying protein structure at atomic resolution has been made through X-ray diffraction, NMR, and cryoelectron microscopy, more recently a new challenge has been identified: studying the dynamics of protein molecules while they interact with a complex environment, especially inside the cell (1–5). Observing such protein dynamics provides insight into the structural alterations a protein can undergo as a function of time and environmental perturbations. It is well known that proteins can undergo drastic structural changes in cells, one extreme example being protein translocation across biological compartments (6). In these cases, translocation and unfolding are intrinsically linked because the size of the pore through which a protein translocates can be comparable to or smaller than the protein itself (7). A protein typically has to deform prior to passing through the pore, which requires accessing higher free energy conformations. Various chemical changes to the protein (mutations, posttranslational modifications) can change the translocation dynamics by stabilizing/destabilizing the rate-limiting transition-state free energy (8, 9) or by optimizing the number of intermediate states (10, 11).One way to interrogate the conformation–translocation coupling is to measure different protein conformational states at a nanopore. Nanopores in artificial lipid bilayers or in solid-state membranes have been used to analyze a wide range of macromolecules at the single-molecule level (12, 13). In these studies, interaction of a single molecule with the nanopore alters the ion flux, resulting in measurable current signals that provide information on the protein’s conformation as it transits through the pore. In pioneering experiments by Kasianowicz et al. (14), it was demonstrated that ionic current blockades of single-stranded RNA oligonucleotides through the protein pore α-hemolysin were due to RNA translocation, where the mean residence time scaled linearly with the oligomer length and was inversely proportional to the applied potential. In nanopore studies of the neutral polymer polyethylene glycol, the residence time distribution was found to be single exponential, and the mean polymer residence time was inversely proportional to the voltage, indicating polymer binding/unbinding to/from the pore (15). In another pioneering work, multistep protein unfolding of the short protein thioredoxin and its unidirectional threading were demonstrated by tagging the terminus of the protein chain with an oligonucleotide (9).Inspired by these studies, we recently demonstrated that an electric field across a solid-state nanopore can induce excited-state conformational dynamics up to complete protein unfolding (16). In this approach, a nanoscale pore is blocked transiently by a protein molecule in its native state, and field-induced conformational fluctuations allow the protein to traverse the pore. The electric field at the nanopore constriction is used to tune the driving force, thereby allowing partially and fully unfolded conformations of cytochrome c to be observed by their residence time and current blockade signals. Motivated by theoretical studies (17), this approach has been further leveraged to measure fast (<1µs) transition-state passage times between protein conformational states (18).Here, we use this approach to differentiate the energy landscape of three fast-folding mutants of λ-repressor fragment λ_6–85 (19–21) by monitoring the characteristic ionic current blockades induced during protein translocation. Unlike cytochrome c (q = +8e), λ_6–85 is more weakly charged (q = +2e), and yet, we still observed electric field–driven protein unfolding and translocation. Protein mutants can have different folding rates due to shifts in their transition-state free energies (8, 9), although mutation can also change the number of accessible (low free energy) conformational states, as predicted by the theory of minimal frustration (22). On rugged energy landscapes, downhill or two-state folding gives way to intermediates that appear during the late stages of the folding process (11). Like more conventional denaturants, temperature, or pressure (23), an electric field at the pore can bias protein molecules toward intermediate or unfolded states, and we can count individual protein conformational states as they pass through the pore.Our measurements reveal various outcomes that depend on the applied field, including native protein dissociation from the pore and back to the bulk solution (no translocation), trapping or translocation of partially unfolded states, and complete unfolding accompanied by translocation. Measurement of translocation rates of mutants reveals protein folding/unfolding equilibria via intermediates for some mutants or simply two state for others. These single-molecule observations allow us to count the number of conformational states for each of the three λ_6–85 mutants accessible on the timescale of our experiments, thus enabling a comparison of their energy landscapes. We find that a mutant with a greater number of low free energy intermediate states can translocate faster than a mutant with a smaller number of such states, suggesting a coupling of conformational dynamics and translocation. The unfolding energetics we observe agree with ensemble laser T-jump (19, 20) and P-jump experiments (24, 25). Regardless of the weak electrical charges of all three mutants employed in this study, we found that they can pass through a pore of diameter <3 nm without requiring chemical denaturants, a motor-driven mechanism (26, 27), or conjugation to an oligonucleotide tag (9). Finally, we demonstrate that the individual mutants in a mixture produce distinct features that allow their detection in a mixture.     

α-Synuclein assembles into higher-order multimers upon membrane binding to promote SNARE complex formation

Physiologically, α-synuclein chaperones soluble NSF attachment protein receptor (SNARE) complex assembly and may also perform other functions; pathologically, in contrast, α-synuclein misfolds into neurotoxic aggregates that mediate neurodegeneration and propagate between neurons. In neurons, α-synuclein exists in an equilibrium between cytosolic and membrane-bound states. Cytosolic α-synuclein appears to be natively unfolded, whereas membrane-bound α-synuclein adopts an α-helical conformation. Although the majority of studies showed that cytosolic α-synuclein is monomeric, it is unknown whether membrane-bound α-synuclein is also monomeric, and whether chaperoning of SNARE complex assembly by α-synuclein involves its cytosolic or membrane-bound state. Here, we show using chemical cross-linking and fluorescence resonance energy transfer (FRET) that α-synuclein multimerizes into large homomeric complexes upon membrane binding. The FRET experiments indicated that the multimers of membrane-bound α-synuclein exhibit defined intermolecular contacts, suggesting an ordered array. Moreover, we demonstrate that α-synuclein promotes SNARE complex assembly at the presynaptic plasma membrane in its multimeric membrane-bound state, but not in its monomeric cytosolic state. Our data delineate a folding pathway for α-synuclein that ranges from a monomeric, natively unfolded form in cytosol to a physiologically functional, multimeric form upon membrane binding, and show that only the latter but not the former acts as a SNARE complex chaperone at the presynaptic terminal, and may protect against neurodegeneration.α-Synuclein is an abundant presynaptic protein that physiologically acts to promote soluble NSF attachment protein receptor (SNARE) complex assembly in vitro and in vivo (1–3). Point mutations in α-synuclein (A30P, E46K, H50Q, G51D, and A53T) as well as α-synuclein gene duplications and triplications produce early-onset Parkinson''s disease (PD) (4–10). Moreover, α-synuclein is a major component of intracellular protein aggregates called Lewy bodies, which are pathological hallmarks of neurodegenerative disorders such as PD, Lewy body dementia, and multiple system atrophy (11–14). Strikingly, neurotoxic α-synuclein aggregates propagate between neurons during neurodegeneration, suggesting that such α-synuclein aggregates are not only intrinsically neurotoxic but also nucleate additional fibrillization (15–18).α-Synuclein is highly concentrated in presynaptic terminals where α-synuclein exists in an equilibrium between a soluble and a membrane-bound state, and is associated with synaptic vesicles (19–22). The labile association of α-synuclein with membranes (23, 24) suggests that binding of α-synuclein to synaptic vesicles, and its dissociation from these vesicles, may regulate its physiological function. Membrane-bound α-synuclein assumes an α-helical conformation (25–32), whereas cytosolic α-synuclein is natively unfolded and monomeric (refs. 25, 26, 31, and 32; however, see refs. 33 and 34 and Discussion for a divergent view). Membrane binding by α-synuclein is likely physiologically important because in in vitro experiments, α-synuclein remodels membranes (35, 36), influences lipid packing (37, 38), and induces vesicle clustering (39). Moreover, membranes were found to be important for the neuropathological effects of α-synuclein (40–44).However, the relation of membrane binding to the in vivo function of α-synuclein remains unexplored, and it is unknown whether α-synuclein binds to membranes as a monomer or oligomer. Thus, in the present study we have investigated the nature of the membrane-bound state of α-synuclein and its relation to its physiological function in SNARE complex assembly. We found that soluble monomeric α-synuclein assembles into higher-order multimers upon membrane binding and that membrane binding of α-synuclein is required for its physiological activity in promoting SNARE complex assembly at the synapse.     

Oncogenic activity of the regulatory subunit p85β of phosphatidylinositol 3-kinase (PI3K)

Expression of the regulatory subunit p85β of PI3K induces oncogenic transformation of primary avian fibroblasts. The transformed cells proliferate at an increased rate compared with nontransformed controls and show elevated levels of PI3K signaling. The oncogenic activity of p85β requires an active PI3K-TOR signaling cascade and is mediated by the p110α and p110β isoforms of the PI3K catalytic subunit. The data suggest that p85β is a less effective inhibitor of the PI3K catalytic subunit than p85α and that this reduced level of p110 inhibition accounts for the oncogenic activity of p85β.Class IA PI3Ks (phosphatidylinositol 3-kinase) are dimeric enzymes consisting of a catalytic subunit and a regulatory subunit. The two major regulatory subunits are p85α and p85β (1). They stabilize and inhibit the catalytic subunit p110 by domain-specific interactions (2–6). The p85α and p85β proteins share core functions, but also display unique activities (7–10). Both p85α and p85β are found mutated in several cancers. These mutants show oncogenic activity; most of the p85α mutations disrupt inhibitory interactions between p85 and p110 or destabilize PTEN (phosphatase and tensin homolog) and result in increased PI3K signaling (5, 11–14). The molecular mechanisms by which p85β mutations activate PI3K signaling have not been fully explored. Elevated expression of wild-type p85β is found in several cancers, and in an experimental setting drives tumor progression (15). A recent study has revealed a role of p85β in the formation of invadopodia with possible effects on metastatic cellular behavior (16). Here we show that expression of p85β induces cellular transformation of primary fibroblasts, increased cell proliferation and elevated PI3K signaling. The oncogenic activity of p85β depends on active PI3K and TOR (target of rapamycin) signaling and is mediated by two PI3K catalytic isoforms, p110α and p110β. Our data are compatible with the conclusion that p85β exerts a reduced inhibitory activity on p110 compared with p85α.     

Structural insights into the interaction of IL-33 with its receptors

Interleukin (IL)-33 is an important member of the IL-1 family that has pleiotropic activities in innate and adaptive immune responses in host defense and disease. It signals through its ligand-binding primary receptor ST2 and IL-1 receptor accessory protein (IL-1RAcP), both of which are members of the IL-1 receptor family. To clarify the interaction of IL-33 with its receptors, we determined the crystal structure of IL-33 in complex with the ectodomain of ST2 at a resolution of 3.27 Å. Coupled with structure-based mutagenesis and binding assay, the structural results define the molecular mechanism by which ST2 specifically recognizes IL-33. Structural comparison with other ligand–receptor complexes in the IL-1 family indicates that surface-charge complementarity is critical in determining ligand-binding specificity of IL-1 primary receptors. Combined crystallography and small-angle X-ray–scattering studies reveal that ST2 possesses hinge flexibility between the D3 domain and D1D2 module, whereas IL-1RAcP exhibits a rigid conformation in the unbound state in solution. The molecular flexibility of ST2 provides structural insights into domain-level conformational change of IL-1 primary receptors upon ligand binding, and the rigidity of IL-1RAcP explains its inability to bind ligands directly. The solution architecture of IL-33–ST2–IL-1RAcP complex from small-angle X-ray–scattering analysis resembles IL-1β–IL-1RII–IL-1RAcP and IL-1β–IL-1RI–IL-1RAcP crystal structures. The collective results confer IL-33 structure–function relationships, supporting and extending a general model for ligand–receptor assembly and activation in the IL-1 family.Interleukin (IL)-33 has important roles in initiating a type 2 immune response during infectious, inflammatory, and allergic diseases (1–5). It was initially identified as a nuclear factor in endothelial cells and named NF-HEV (nuclear factor from high endothelial venules) (6, 7). In 2005, it was rediscovered as a new member of the IL-1 family and an extracellular ligand for the orphan IL-1 receptor family member ST2 (8). As an extracellular cytokine, IL-33 is involved in the polarization of Th2 cells and activation of mast cells, basophils, eosinophils, and natural killer cells (1–3). Recent studies also discovered that the type 2 innate lymphoid cells (ILC2s) are major target cells of IL-33 (9, 10). ILC2s express a high level of ST2 and secrete large amounts of Th2 cytokines, most notably IL-5 and IL-13, when stimulated with IL-33 (11–13). Activation of ILC2s is essential in the initiation of the type 2 immune response against helminth infection and during allergic diseases such as asthma (9, 10).IL-33 does not have a signal peptide and is synthesized with an N-terminal propeptide upstream of the IL-1–like cytokine domain. It is preferentially and constitutively expressed in the nuclei of structural and lining cells, particularly in epithelial and endothelial cells (14, 15). Tissue damage caused by pathogen invasion or allergen exposure may lead to the release of IL-33 into extracellular environment from necrotic cells, which functions as an endogenous danger signal or alarmin (14, 16). Full-length human IL-33 consists of 270 residues and is biologically active (17, 18). It is also a substrate of serine proteases released by inflammatory cells recruited to the site of injury (18, 19). The proteases elastase, cathespin G, and proteinase 3 cleave full-length IL-33 to release N-terminal–truncated mature forms containing the IL-1–like cytokine domain: IL-33_95–270, l-33_99–270, and IL-33_109–270 (18). These mature IL-33 forms process a 10-fold greater potency to activate ST2 than full-length IL-33 (18). Caspase-1 was also suggested to cleave IL-33 to generate an active IL-33_112–270 that is the commercially available mature IL-33 form (8). However, it was later demonstrated that this cleavage site does not exist and cleavage by caspases at other sites actually inactivates IL-33 (17, 20, 21).The signaling of IL-33 depends on its binding to the primary receptor ST2 and subsequent recruitment of accessory receptor IL-1RAcP (8, 22, 23). The ligand-binding–induced receptor heterodimerization results in the juxtaposition of the intracellular toll/interleukin-1 receptor (TIR) domains of both receptors, which is necessary and sufficient to activate NF-κB and MAPK pathways in the target cells (24). Previously, we determined the complex structure of IL-1β with its decoy receptor IL-1RII and accessory receptor IL-1RAcP (25). Based on this structure and other previous studies, we proposed a general structural model for the assembly and activation of IL-1 family of cytokines with their receptors (25). In this model, ligand recognition relies on interaction of IL-1 cytokine with its primary receptor: IL-1α and IL-1β with IL-1RI; IL-33 with ST2; IL-18 with IL-18Rα; and IL-36α, IL-36β, and IL-36γ with IL-1Rrp2 (26–28). The binding forms a composite surface to recruit accessory receptor IL-1RAcP shared by IL-1α, IL-1β, IL-33, IL-36α, IL-36β, and IL-36γ and IL-18Rβ by IL-18 (26, 27). This general structural model is further supported by the subsequent structural determination of IL-1β with IL-1RI and IL-1RAcP (29). However, there are still many key missing parts in the general structural model of ligand–receptor interaction in the IL-1 family. For example, the structural basis for specific recognition of IL-33 by ST2 and IL-18 by IL-18Rα, and promiscuous recognition of IL-36α, IL-36β, and IL-36γ by IL-1Rrp2 remains elusive. The proposed general model also needs further confirmation from structural studies of other signaling complexes in the IL-1 family. To address these issues, we studied the interaction of IL-33 with its receptors by a combination of X-ray crystallography and small-angle X-ray–scattering (SAXS) methods.     

Molecular mechanism for strengthening E-cadherin adhesion using a monoclonal antibody

E-cadherin (Ecad) is an essential cell–cell adhesion protein with tumor suppression properties. The adhesive state of Ecad can be modified by the monoclonal antibody 19A11, which has potential applications in reducing cancer metastasis. Using X-ray crystallography, we determine the structure of 19A11 Fab bound to Ecad and show that the antibody binds to the first extracellular domain of Ecad near its primary adhesive motif: the strand–swap dimer interface. Molecular dynamics simulations and single-molecule atomic force microscopy demonstrate that 19A11 interacts with Ecad in two distinct modes: one that strengthens the strand–swap dimer and one that does not alter adhesion. We show that adhesion is strengthened by the formation of a salt bridge between 19A11 and Ecad, which in turn stabilizes the swapped β-strand and its complementary binding pocket. Our results identify mechanistic principles for engineering antibodies to enhance Ecad adhesion.

E-cadherin (Ecad) is an essential cell–cell adhesion protein that plays key roles in the formation of epithelial tissues and in the maintenance of tissue integrity. Adhesion is mediated by the trans binding of Ecad ectodomains (extracellular regions) from opposing cell surfaces. Deficiencies in Ecad adhesion result in the loss of contact inhibition and increased cell mobility (1) and are associated with the metastasis of gastric cancer (2), breast cancer (3), colorectal cancer (4), and lung cancer (5). Consequently, strategies that activate or strengthen Ecad adhesion may have potential applications in reducing cancer metastasis.A powerful therapeutic approach that has been successfully used in regulating the binding of cell adhesion proteins are monoclonal antibodies (mAbs). For example, mAbs targeted against integrin adhesion proteins are used in the treatment of Crohn’s disease (6–8). Similarly, we have identified activating mAbs that target Ecad ectodomains and enhance cell–cell adhesion (9). In mouse models, one of these mAbs, 19A11, prevents the metastatic invasion of mouse lung cancer cells expressing human Ecad (10, 11). In addition, we have shown that 19A11 can enhance the Ecad epithelial barrier function and limit the progression of inflammatory bowel disease (12). Here, we resolve the molecular mechanisms by which mAb 19A11 strengthens Ecad adhesion.We demonstrate that 19A11 strengthens adhesion by stabilizing strand–swap dimers, which are the predominant Ecad trans binding conformation. Strand–swap dimers are formed by the exchange of N-terminal β-strands (residues 1–12) between the outermost domains (EC1) of opposing Ecads. The exchange of β-strands results in the symmetric docking of a conserved anchor residue, tryptophan at the position 2 (W2), into a complementary pocket on the partner Ecad (13–15). Previous studies show that the two key structural and energetic determinants of Ecad strand–swap dimer formation are the stability of swapped β-strands (16) and their corresponding hydrophobic binding pockets (17). Using X-ray crystallography, molecular dynamics (MD) simulations, steered MD (SMD) simulations, and single-molecule atomic force microscopy (AFM), we show that 19A11 binding stabilizes both the β-strand and the hydrophobic pocket by forming key salt bridges. Our results identify the mechanistic principles underlying the activation of cadherin adhesion by mAbs.     

From the Cover: Structural differences in amyloid-β fibrils from brains of nondemented elderly individuals and Alzheimer's disease patients

Although amyloid plaques composed of fibrillar amyloid-β (Aβ) assemblies are a diagnostic hallmark of Alzheimer''s disease (AD), quantities of amyloid similar to those in AD patients are observed in brain tissue of some nondemented elderly individuals. The relationship between amyloid deposition and neurodegeneration in AD has, therefore, been unclear. Here, we use solid-state NMR to investigate whether molecular structures of Aβ fibrils from brain tissue of nondemented elderly individuals with high amyloid loads differ from structures of Aβ fibrils from AD tissue. Two-dimensional solid-state NMR spectra of isotopically labeled Aβ fibrils, prepared by seeded growth from frontal lobe tissue extracts, are similar in the two cases but with statistically significant differences in intensity distributions of cross-peak signals. Differences in solid-state NMR data are greater for 42-residue amyloid-β (Aβ42) fibrils than for 40-residue amyloid-β (Aβ40) fibrils. These data suggest that similar sets of fibril polymorphs develop in nondemented elderly individuals and AD patients but with different relative populations on average.

Amyloid plaques in brain tissue, containing fibrils formed by amyloid-β (Aβ) peptides, are one of the diagnostic pathological signatures of Alzheimer''s disease (AD). Clear genetic and biomarker evidence indicates that Aβ is key to AD pathogenesis (1). However, Aβ is present as a diverse population of multimeric assemblies, ranging from soluble oligomers to insoluble fibrils and plaques, and may lead to neurodegeneration by a number of possible mechanisms (2–7).One argument against a direct neurotoxic role for Aβ plaques and fibrils in AD is the fact that plaques are not uncommon in the brains of nondemented elderly people, as shown both by traditional neuropathological studies (8, 9) and by positron emission tomography (10–13). On average, the quantity of amyloid is greater in AD patients (10) and (at least in some studies) increases with decreasing cognitive ability (12, 14, 15) or increasing rate of cognitive decline (16). However, a high amyloid load does not necessarily imply a high degree of neurodegeneration and cognitive impairment (11, 13, 17).A possible counterargument comes from studies of the molecular structures of Aβ fibrils, which show that Aβ peptides form multiple distinct fibril structures, called fibril polymorphs (18–20). Polymorphism has been demonstrated for fibrils formed by both 40-residue amyloid-β (Aβ40) (19, 21–24) and 42-residue amyloid-β (Aβ42) (22, 25–29) peptides, the two main Aβ isoforms. Among people with similar total amyloid loads, variations in neurodegeneration and cognitive impairment may conceivably arise from variations in the relative populations of different fibril polymorphs. As a hypothetical example, if polymorph A was neurotoxic but polymorph B was not, then people whose Aβ peptides happened to form polymorph A would develop AD, while people whose Aβ peptides happened to form polymorph B would remain cognitively normal. In practice, brains may contain a population of different propagating and/or neurotoxic Aβ species, akin to prion quasispecies or “clouds,” and the relative proportions of these and their dynamic interplay may affect clinical phenotype and rates of progression (30).Well-established connections between molecular structural polymorphism and variations in other neurodegenerative diseases lend credence to the hypothesis that Aβ fibril polymorphism plays a role in variations in the characteristics of AD. Distinct strains of prions causing the transmissible spongiform encephalopathies have been shown to involve different molecular structural states of the mammalian prion protein PrP (30–32). Distinct tauopathies involve different polymorphs of tau protein fibrils (33–37). In the case of synucleopathies, α-synuclein has been shown to be capable of forming polymorphic fibrils (38–40) with distinct biological effects (41–43).Experimental support for connections between Aβ polymorphism and variations in characteristics of AD comes from polymorph-dependent fibril toxicities in neuronal cell cultures (19), differences in neuropathology induced in transgenic mice by injection of amyloid-containing extracts from different sources (44–46), differences in conformation and stability with respect to chemical denaturation of Aβ assemblies prepared from brain tissue of rapidly or slowly progressing AD patients (47), and differences in fluorescence emission spectra of structure-sensitive dyes bound to amyloid plaques in tissue from sporadic or familial AD patients (48, 49).Solid-state NMR spectroscopy is a powerful method for investigating fibril polymorphism because even small, localized changes in molecular conformation or structural environment produce measurable changes in ¹³C and ¹⁵N NMR chemical shifts (i.e., in NMR frequencies of individual carbon and nitrogen sites). Full molecular structural models for amyloid fibrils can be developed from large sets of measurements on structurally homogeneous samples (21, 25, 26, 29, 38, 50). Alternatively, simple two-dimensional (2D) solid-state NMR spectra can serve as structural fingerprints, allowing assessments of polymorphism and comparisons between samples from different sources (22, 51).Solid-state NMR requires isotopic labeling and milligram-scale quantities of fibrils, ruling out direct measurements on amyloid fibrils extracted from brain tissue. However, Aβ fibril structures from autopsied brain tissue can be amplified and isotopically labeled by seeded fibril growth, in which fibril fragments (i.e., seeds) in a brain tissue extract are added to a solution of isotopically labeled peptide (21, 22, 52). Labeled “daughter” fibrils that grow from the seeds retain the molecular structures of the “parent” fibrils, as demonstrated for Aβ (19, 21, 24, 53) and other (54, 55) amyloid fibrils. Solid-state NMR measurements on the brain-seeded fibrils then provide information about molecular structures of fibrils that were present in the brain tissue at the time of autopsy. Using this approach, Lu et al. (21) developed a full molecular structure for Aβ40 fibrils derived from one AD patient with an atypical clinical history (patient 1), showed that Aβ40 fibrils from a second patient with a typical AD history (patient 2) were qualitatively different in structure, and showed that the predominant brain-derived Aβ40 polymorph was the same in multiple regions of the cerebral cortex from each patient. Subsequently, Qiang et al. (22) prepared isotopically labeled Aβ40 and Aβ42 fibrils from frontal, occipital, and parietal lobe tissue of 15 patients in three categories, namely typical long-duration Alzheimer''s disease (t-AD), the posterior cortical atrophy variant of Alzheimer''s disease (PCA-AD), and rapidly progressing Alzheimer''s disease (r-AD). Quantitative analyses of 2D solid-state NMR spectra led to the conclusions that Aβ40 fibrils derived from t-AD and PCA-AD tissue were indistinguishable, with both showing the same predominant polymorph; that Aβ40 fibrils derived from r-AD tissue were more structurally heterogeneous (i.e., more polymorphic); and that Aβ42 fibrils derived from all three categories were structurally heterogeneous, with at least two prevalent Aβ42 polymorphs (22).In this paper, we address the question of whether Aβ fibrils that develop in cortical tissue of nondemented elderly individuals with high amyloid loads are structurally distinguishable from fibrils that develop in cortical tissue of AD patients. As described below, quantitative analyses of 2D solid-state NMR spectra of brain-seeded samples indicate statistically significant differences for both Aβ40 and Aβ42 fibrils. Differences in the 2D spectra are subtle, however, indicating that nondemented individuals and AD patients do not develop entirely different Aβ fibril structures. Instead, data and analyses described below suggest overlapping distributions of fibril polymorphs, with different relative populations on average.     

An experimental test of the nicotinic hypothesis of COVID-19

The pathophysiological mechanisms underlying the constellation of symptoms that characterize COVID-19 are only incompletely understood. In an effort to fill these gaps, a “nicotinic hypothesis,” which posits that nicotinic acetylcholine receptors (AChRs) act as additional severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptors, has recently been put forth. A key feature of the proposal (with potential clinical ramifications) is the suggested competition between the virus’ spike protein and small-molecule cholinergic ligands for the receptor’s orthosteric binding sites. This notion is reminiscent of the well-established role of the muscle AChR during rabies virus infection. To address this hypothesis directly, we performed equilibrium-type ligand-binding competition assays using the homomeric human α7-AChR (expressed on intact cells) as the receptor, and radio-labeled α-bungarotoxin (α-BgTx) as the orthosteric-site competing ligand. We tested different SARS-CoV-2 spike protein peptides, the S1 domain, and the entire S1–S2 ectodomain, and found that none of them appreciably outcompete [¹²⁵I]-α-BgTx in a specific manner. Furthermore, patch-clamp recordings showed no clear effect of the S1 domain on α7-AChR–mediated currents. We conclude that the binding of the SARS-CoV-2 spike protein to the human α7-AChR’s orthosteric sites—and thus, its competition with ACh, choline, or nicotine—is unlikely to be a relevant aspect of this complex disease.

According to official reports, as of August 2022, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected nearly 600 million people and caused more than 6.5 million deaths worldwide (1). According to recent estimates by the World Health Organization that aim to capture deaths missed by national reporting systems, however, the pandemic’s true death toll is actually much higher: it amounts to ∼15 million (2). Despite intensive research, our understanding of the pathophysiological mechanisms underlying the broad range of respiratory, neurological, psychiatric, and cardiovascular symptoms that follow this viral infection remains limited (3–7). Although the angiotensin-converting enzyme 2 (ACE2) was identified as the main cell-entry receptor (8–10), other plasma membrane receptors (such as neuropilin-1) (11, 12) and cell-surface glycocalyx components (such as heparan sulfate) (13) were also reported to participate in the different facets of this disease.On the basis of amino acid sequence similarities between the SARS-CoV-2 spike protein and snake venom neurotoxins, it has recently been hypothesized that this coronavirus may also bind to nicotinic acetylcholine receptors (AChRs) (14–17). Moreover, it was suggested that the spike protein would bind to the receptor at a site that overlaps with the neurotransmitter-binding (“orthosteric”) sites, in such a way that neurotoxins, the spike protein, and small-molecule cholinergic ligands would all bind to the receptor in a mutually exclusive, competitive manner. On the spike protein, the regions that were hypothesized to bind to AChRs map to two separate sequences: S³⁷⁵TFKCYGVSPTKLNDL (S375–L390) (18), near the middle of the ACE2-binding domain (receptor-binding domain, RBD), and Y⁶⁷⁴QTQTNSPRRAR (Y674–R685) (14), at the furin-cleavage site between domains S1 and S2 (Fig. 1). Remarkably, this bold proposal received ample support from molecular-simulation studies that led to the identification of putative interatomic interactions bridging the AChR–spike protein-binding interface (18, 19). Importantly, these simulations also suggested that the Y674–R685 stretch of amino acids remains accessible—and thus, fully competent to bind to the AChR—in the context of the fully glycosylated, full-length spike protein. Furthermore, the interaction between the receptor and the Y674–R685 spike protein peptide was found to be highly dependent on the AChR subtype, the peptide seemingly acting as an antagonist of the α4β2-AChR and the fetal-muscle-type AChR, and probably, as an agonist of the α7-AChR (19). These differences suggest that the extrapolation of experimental results obtained with one type of AChR to another one need not be valid, despite the highly similar binding modes of neurotoxins to muscle-type and α7-AChRs (20, 21).Open in a separate windowFig. 1.Amino acid sequence of the spike protein of SARS-CoV-2 (GenBank: {"type":"entrez-protein","attrs":{"text":"QHD43416.1","term_id":"1791269090","term_text":"QHD43416.1"}}QHD43416.1). A PRRAR furin-cleavage site (a part of the Y674–R685 stretch, in cyan letters and underlined) separates the S1 domain from the S2 domain. The signal peptide is indicated with green letters; the ACE2-binding domain (RBD) is in orange; the S375–L390 stretch is in red and underlined; and the transmembrane segment is in magenta. The N terminus faces the extracellular milieu.An interaction between the spike protein and AChRs could have pathological consequences not only because it could provide an alternative pathway for the virus to attach to and enter cells, but also because it could disrupt physiological AChR-mediated signaling. Moreover, the notion that the binding of the spike protein to the AChR is competitive with that of small-molecule cholinergic ligands would suggest a novel mechanism by which nicotine consumption and smoking-cessation drugs could affect the course of the disease (15–17, 22–24), the better understood mechanisms being the direct effect of nicotine and its analogs on the α7-AChR–mediated antiinflammatory response to viral infection (25–29).However far-fetched these ideas may have seemed when first put forth, there is a well-known precedent: the rabies virus glycoprotein was reported to bind to the muscle-type (α1β1γδ) AChR in a manner that is mutually exclusive with the binding of α-bungarotoxin [a 74-amino acid neurotoxin from the Formosan banded krait; α-BgTx (30)] (31–35). This finding, along with other pieces of experimental evidence (e.g., refs. 36–38), has led to the well-established notion that the muscle AChR is one of the cell-attachment receptors for the rabies virus (39, 40). Quite notably, similar claims were made about the human-immunodeficiency virus-1 (HIV-1) glycoprotein 120 (gp120) and the muscle AChR (41, 42).Given this background, the suggestion of a binding interaction between the SARS-CoV-2 spike protein and several AChRs (α1β1γδ, α4β2, α7, and α9) (14, 18, 19) seemed most intriguing and worth investigating experimentally. To this end, we performed equilibrium-type ligand-binding competition studies using the homomeric human α7-AChR (expressed on intact cells) as the receptor, and radio-labeled α-BgTx (at a concentration that half-saturates the α7-AChR) as the competing ligand. We found that the two spike protein peptides (tested up to a concentration of ∼250 μM), the S1 domain (∼1.2 μM), and the entire S1–S2 ectodomain (∼375 nM) fail to displace bound α-BgTx from this receptor to any appreciable degree. Furthermore, we found that the S1 domain (∼20 nM) has no obvious effects on α7-AChR channel function. Thus, it seems inescapable to conclude that the binding of the SARS-CoV-2 spike protein to the human α7-AChR’s orthosteric sites—and more specifically, the competition with ACh, choline, or nicotine for so doing—is unlikely to be a relevant aspect of this complex disease.     

Na,K-ATPase α3 is a death target of Alzheimer patient amyloid-β assembly

Neurodegeneration correlates with Alzheimer’s disease (AD) symptoms, but the molecular identities of pathogenic amyloid β-protein (Aβ) oligomers and their targets, leading to neurodegeneration, remain unclear. Amylospheroids (ASPD) are AD patient-derived 10- to 15-nm spherical Aβ oligomers that cause selective degeneration of mature neurons. Here, we show that the ASPD target is neuron-specific Na⁺/K⁺-ATPase α3 subunit (NAKα3). ASPD-binding to NAKα3 impaired NAKα3-specific activity, activated N-type voltage-gated calcium channels, and caused mitochondrial calcium dyshomeostasis, tau abnormalities, and neurodegeneration. NMR and molecular modeling studies suggested that spherical ASPD contain N-terminal-Aβ–derived “thorns” responsible for target binding, which are distinct from low molecular-weight oligomers and dodecamers. The fourth extracellular loop (Ex4) region of NAKα3 encompassing Asn⁸⁷⁹ and Trp⁸⁸⁰ is essential for ASPD–NAKα3 interaction, because tetrapeptides mimicking this Ex4 region bound to the ASPD surface and blocked ASPD neurotoxicity. Our findings open up new possibilities for knowledge-based design of peptidomimetics that inhibit neurodegeneration in AD by blocking aberrant ASPD–NAKα3 interaction.Alzheimer’s disease (AD) brains characteristically display fibrillar and nonfibrillar (oligomeric) protein assemblies composed of the amyloid β-protein (Aβ) (1–6). Aβ has been shown to bind to postsynaptic receptors, such as α7-nicotinic acetylcholine receptor (α7nAChR) (7), receptor for advanced glycation end products (RAGE) (8), receptor tyrosine kinase EPHB2 (9), and cellular prion protein PrP^C (10). These “Aβ receptors,” except for RAGE, have been reported to mediate toxicity of Aβ oligomers through modulating NMDA receptors (NMDAR) (11). Aβ oligomers, including dimers from AD brains (12, 13), dodecamers (Aβ*56) from AD model mice (14), and in vitro-generated Aβ-derived diffusible ligands (ADDLs) (15, 16), induce synaptic impairment by affecting NMDAR (11). Thus, NMDAR are a common target for synaptic impairment in AD. However, these oligomers do not cause neuronal death (12, 14). The atomic resolution structures of neurotoxic Aβ oligomers and their in vivo targets leading to neuronal death in AD remain unclear (6), even though neuronal death is the central mechanism responsible for symptomatic onset in AD (17).We previously isolated neurotoxic Aβ oligomers, termed amylospheroids (ASPD), from the brains of AD patient (18–20). ASPD appear in transmission electron microscopic (TEM) images as spheres of diameter ∼11.9 ± 1.7 nm (19). ASPD appear to be unique Aβ assemblies, as determined immunochemically. These structures are recognized strongly by ASPD-specific antibodies (K_d ∼ pM range), but not with the oligomer-specific polyclonal antiserum A11 (19). ASPD are distinct from Aβ dimers, ADDLs, dodecamers, and other A11-reactive entities (19).ASPD cause severe degeneration of mature human neurons (19). ASPD levels in the cortices of AD patients correlate well with disease severity (19). In contrast, ASPD-like oligomers were minimally detectable in the brains of transgenic mice expressing human amyloid precursor protein (APP), in which no significant neuronal loss is observed (19). These findings suggest that ASPD are an important effector of neuronal death in AD patients. We sought to elucidate mechanisms of ASPD-induced neurotoxicity. We report here that ASPD interact with the α-subunit of neuron-specific Na⁺/K⁺-ATPase (NAKα3), resulting in presynaptic calcium overload and neuronal death.     

Molecular mechanism underlying ethanol activation of G-protein–gated inwardly rectifying potassium channels

Alcohol (ethanol) produces a wide range of pharmacological effects on the nervous system through its actions on ion channels. The molecular mechanism underlying ethanol modulation of ion channels is poorly understood. Here we used a unique method of alcohol-tagging to demonstrate that alcohol activation of a G-protein–gated inwardly rectifying potassium (GIRK or Kir3) channel is mediated by a defined alcohol pocket through changes in affinity for the membrane phospholipid signaling molecule phosphatidylinositol 4,5-bisphosphate. Surprisingly, hydrophobicity and size, but not the canonical hydroxyl, were important determinants of alcohol-dependent activation. Altering levels of G protein Gβγ subunits, conversely, did not affect alcohol-dependent activation, suggesting a fundamental distinction between receptor and alcohol gating of GIRK channels. The chemical properties of the alcohol pocket revealed here might extend to other alcohol-sensitive proteins, revealing a unique protein microdomain for targeting alcohol-selective therapeutics in the treatment of alcoholism and addiction.Alcohol (ethanol) produces a wide range of pharmacological effects on the nervous system, ranging from anxiolytic effects to intoxication and alcohol addiction in certain individuals. Although the neural circuits underlying such addictive disorders are becoming better understood (1, 2), little is known about the molecular mechanisms underlying ethanol’s interaction with specific target proteins, such as ion channels. G-protein–gated inwardly rectifying K⁺(GIRK or Kir3) channels are activated by concentrations of ethanol relevant to human consumption (18 mM ethanol or 0.08% blood alcohol level) (3–5) and have been found to play a key role in alcohol-related disorders (6–9). For example, mice lacking GIRK2 (or Kir3.2) channels self-administer more ethanol and fail to develop conditioned place preference for ethanol, compared with wild-type (WT) littermates (6, 10). These results support a model in which ethanol may have lost its target in GIRK knockout mice, thus failing to elicit behaviors associated with ethanol consumption. Receptor activation of GIRK channels generates an outward, slow inhibitory postsynaptic current, which reduces neuronal activity (11). In addition to directly activating GIRKs, ethanol potentiates the slow inhibitory postsynaptic potential in midbrain dopamine neurons of the ventral tegmental area (8), which is produced by GABA_B receptor activation of GIRK channels (7, 12, 13). Together these observations implicate GIRK channels in the etiology of alcohol dependence and addiction; however, the molecular details underlying ethanol activation of GIRK channels remain unknown.A major challenge is to understand how ethanol, with its simple chemistry of only two carbons and a hydroxyl, can produce behavioral changes with rapidity and reproducibility. Ethanol has little volume or distinguishing stereochemistry. Although it was once thought to interact nonspecifically with membrane lipids, a preponderance of evidence suggests that ethanol binds directly to discrete pockets in proteins that alter their function (14, 15). However, unlike other typical drug interactions, ethanol has low potency (millimolar range) and lacks chemical specificity (more than one type of alcohol interacts with the same ion channel). Structural views of putative alcohol-binding pockets are emerging (3, 16, 17), but the molecular details and chemical rules governing the interaction of alcohol with these specific alcohol-binding pockets remain elusive.In this study, we investigated the chemical nature of the alcohol pocket by expanding the method of “alcohol-tagging” ion channels (18). Using this unique strategy, we examined the chemical diversity of ligands compatible with the alcohol pocket and investigated the role of other signaling molecules, phosphatidylinositol 4,5-bisphosphate (PIP₂) (19, 20) and G-protein Gβγ subunits (21–24), which also regulate the activity of GIRK channels. Understanding this mechanism will be critical for developing alcohol-selective therapeutics that can perhaps prevent alcohol abuse and treat addiction.