Pharmacological inhibition of α-synuclein aggregation within liquid condensates.

Aggregated forms of α-synuclein constitute the major component of Lewy bodies, the proteinaceous aggregates characteristic of Parkinson's disease. Emerging evidence suggests that α-synuclein aggregation may occur within liquid condensates formed through phase separation. This mechanism of aggregation creates new challenges and opportunities for drug discovery for Parkinson's disease, which is otherwise still incurable. Here we show that the condensation-driven aggregation pathway of α-synuclein can be inhibited using small molecules. We report that the aminosterol claramine stabilizes α-synuclein condensates and inhibits α-synuclein aggregation within the condensates both in vitro and in a Caenorhabditis elegans model of Parkinson's disease. By using a chemical kinetics approach, we show that the mechanism of action of claramine is to inhibit primary nucleation within the condensates. These results illustrate a possible therapeutic route based on the inhibition of protein aggregation within condensates, a phenomenon likely to be relevant in other neurodegenerative disorders.

RASP: Optimal Single Puncta Detection in Complex Cellular Backgrounds.

Super-resolution and single-molecule microscopies have been increasingly applied to complex biological systems. A major challenge of these approaches is that fluorescent puncta must be detected in the low signal, high noise, heterogeneous background environments of cells and tissue. We present RASP, Radiality Analysis of Single Puncta, a bioimaging-segmentation method that solves this problem. RASP removes false-positive puncta that other analysis methods detect and detects features over a broad range of spatial scales: from single proteins to complex cell phenotypes. RASP outperforms the state-of-the-art methods in precision and speed using image gradients to separate Gaussian-shaped objects from the background. We demonstrate RASP's power by showing that it can extract spatial correlations between microglia, neurons, and α-synuclein oligomers in the human brain. This sensitive, computationally efficient approach enables fluorescent puncta and cellular features to be distinguished in cellular and tissue environments, with sensitivity down to the level of the single protein. Python and MATLAB codes, enabling users to perform this RASP analysis on their own data, are provided as Supporting Information and links to third-party repositories.

Discovery of potent inhibitors of α-synuclein aggregation using structure-based iterative learning.

Machine learning methods hold the promise to reduce the costs and the failure rates of conventional drug discovery pipelines. This issue is especially pressing for neurodegenerative diseases, where the development of disease-modifying drugs has been particularly challenging. To address this problem, we describe here a machine learning approach to identify small molecule inhibitors of α-synuclein aggregation, a process implicated in Parkinson's disease and other synucleinopathies. Because the proliferation of α-synuclein aggregates takes place through autocatalytic secondary nucleation, we aim to identify compounds that bind the catalytic sites on the surface of the aggregates. To achieve this goal, we use structure-based machine learning in an iterative manner to first identify and then progressively optimize secondary nucleation inhibitors. Our results demonstrate that this approach leads to the facile identification of compounds two orders of magnitude more potent than previously reported ones.

A Relationship between the Structures and Neurotoxic Effects of Aß Oligomers Stabilized by Different Metal Ions.

Oligomeric assemblies of the amyloid ß peptide (Aß) have been investigated for over two decades as possible neurotoxic agents in Alzheimer's disease. However, due to their heterogeneous and transient nature, it is not yet fully established which of the structural features of these oligomers may generate cellular damage. Here, we study distinct oligomer species formed by Aß40 (the 40-residue form of Aß) in the presence of four different metal ions (Al3+, Cu2+, Fe2+, and Zn2+) and show that they differ in their structure and toxicity in human neuroblastoma cells. We then describe a correlation between the size of the oligomers and their neurotoxic activity, which provides a type of structure-toxicity relationship for these Aß40 oligomer species. These results provide insight into the possible role of metal ions in Alzheimer's disease by the stabilization of Aß oligomers.

Maturation-dependent changes in the size, structure and seeding capacity of Aß42 amyloid fibrils.

Many proteins self-assemble to form amyloid fibrils, which are highly organized structures stabilized by a characteristic cross-ß network of hydrogen bonds. This process underlies a variety of human diseases and can be exploited to develop versatile functional biomaterials. Thus, protein self-assembly has been widely studied to shed light on the properties of fibrils and their intermediates. A still open question in the field concerns the microscopic processes that underlie the long-time behaviour and properties of amyloid fibrillar assemblies. Here, we use atomic force microscopy with angstrom-sensitivity to observe that amyloid fibrils undergo a maturation process, associated with an increase in both fibril length and thickness, leading to a decrease of their density, and to a change in their cross-ß sheet content. These changes affect the ability of the fibrils to catalyse the formation of new aggregates. The identification of these changes helps us understand the fibril maturation processes, facilitate the targeting of amyloid fibrils in drug discovery, and offer insight into the development of biocompatible and sustainable protein-based materials.

Modulation of α-synuclein in vitro aggregation kinetics by its alternative splice isoforms.

The misfolding and aggregation of α-synuclein is linked to a family of neurodegenerative disorders known as synucleinopathies, the most prominent of which is Parkinson's disease (PD). Understanding the aggregation process of α-synuclein from a mechanistic point of view is thus of key importance. SNCA, the gene encoding α-synuclein, comprises six exons and produces various isoforms through alternative splicing. The most abundant isoform is expressed as a 140-amino acid protein (αSyn-140), while three other isoforms, αSyn-126, αSyn-112, and αSyn-98, are generated by skipping exon 3, exon 5, or both exons, respectively. In this study, we performed a detailed biophysical characterization of the aggregation of these four isoforms. We found that αSyn-112 and αSyn-98 exhibit accelerated aggregation kinetics compared to αSyn-140 and form distinct aggregate morphologies, as observed by transmission electron microscopy. Moreover, we observed that the presence of relatively small amounts of αSyn-112 accelerates the aggregation of αSyn-140, significantly reducing the aggregation half-time. These results indicate a potential role of alternative splicing in the pathological aggregation of α-synuclein and provide insights into how this process could be associated with the development of synucleinopathies.

Misfolded protein oligomers: mechanisms of formation, cytotoxic effects, and pharmacological approaches against protein misfolding diseases.

The conversion of native peptides and proteins into amyloid aggregates is a hallmark of over 50 human disorders, including Alzheimer's and Parkinson's diseases. Increasing evidence implicates misfolded protein oligomers produced during the amyloid formation process as the primary cytotoxic agents in many of these devastating conditions. In this review, we analyze the processes by which oligomers are formed, their structures, physicochemical properties, population dynamics, and the mechanisms of their cytotoxicity. We then focus on drug discovery strategies that target the formation of oligomers and their ability to disrupt cell physiology and trigger degenerative processes.

Using Generative Modeling to Endow with Potency Initially Inert Compounds with Good Bioavailability and Low Toxicity.

In the early stages of drug development, large chemical libraries are typically screened to identify compounds of promising potency against the chosen targets. Often, however, the resulting hit compounds tend to have poor drug metabolism and pharmacokinetics (DMPK), with negative developability features that may be difficult to eliminate. Therefore, starting the drug discovery process with a "null library", compounds that have highly desirable DMPK properties but no potency against the chosen targets, could be advantageous. Here, we explore the opportunities offered by machine learning to realize this strategy in the case of the inhibition of α-synuclein aggregation, a process associated with Parkinson's disease. We apply MolDQN, a generative machine learning method, to build an inhibitory activity against α-synuclein aggregation into an initial inactive compound with good DMPK properties. Our results illustrate how generative modeling can be used to endow initially inert compounds with desirable developability properties.

Bayesian Optimization in the Latent Space of a Variational Autoencoder for the Generation of Selective FLT3 Inhibitors.

The process of drug design requires the initial identification of compounds that bind their targets with high affinity and selectivity. Advances in generative modeling of small molecules based on deep learning are offering novel opportunities for making this process faster and cheaper. Here, we propose an approach to achieve this goal, where predictions of binding affinity are used in conjunction with the Junction Tree Variational Autoencoder (JTVAE) whose latent space is used to facilitate the efficient exploration of the chemical space using a Bayesian optimization strategy. The exploration identifies small molecules predicted to have both high affinity and high selectivity by using an objective function that optimizes the binding to the target while penalizing the binding to off-targets. The framework is demonstrated for FMS-like tyrosine kinase 3 (FLT3) and shown to predict small molecules with predicted affinity and selectivity comparable to those of clinically approved drugs for this target.

Multiplexed Digital Characterization of Misfolded Protein Oligomers via Solid-State Nanopores.

Misfolded protein oligomers are of central importance in both the diagnosis and treatment of Alzheimer's and Parkinson's diseases. However, accurate high-throughput methods to detect and quantify oligomer populations are still needed. We present here a single-molecule approach for the detection and quantification of oligomeric species. The approach is based on the use of solid-state nanopores and multiplexed DNA barcoding to identify and characterize oligomers from multiple samples. We study α-synuclein oligomers in the presence of several small-molecule inhibitors of α-synuclein aggregation as an illustration of the potential applicability of this method to the development of diagnostic and therapeutic methods for Parkinson's disease.

Sequence-based prediction of the intrinsic solubility of peptides containing non-natural amino acids.

Non-natural amino acids are increasingly used as building blocks in the development of peptide-based drugs as they expand the available chemical space to tailor function, half-life and other key properties. However, while the chemical space of modified amino acids (mAAs) such as residues containing post-translational modifications (PTMs) is potentially vast, experimental methods for measuring the developability properties of mAA-containing peptides are expensive and time consuming. To facilitate developability programs through computational methods, we present CamSol-PTM, a method that enables the fast and reliable sequence-based prediction of the intrinsic solubility of mAA-containing peptides in aqueous solution at room temperature. From a computational screening of 50,000 mAA-containing variants of three peptides, we selected five different small-size mAAs for a total number of 37 peptide variants for experimental validation. We demonstrate the accuracy of the predictions by comparing the calculated and experimental solubility values. Our results indicate that the computational screening of mAA-containing peptides can extend by over four orders of magnitude the ability to explore the solubility chemical space of peptides and confirm that our method can accurately assess the solubility of peptides containing mAAs. This method is available as a web server at https://www-cohsoftware.ch.cam.ac.uk/index.php/camsolptm .

The αC-ß4 loop controls the allosteric cooperativity between nucleotide and substrate in the catalytic subunit of protein kinase A.

Allosteric cooperativity between ATP and substrates is a prominent characteristic of the cAMP-dependent catalytic (C) subunit of protein kinase A (PKA). Not only this long-range synergistic action is involved in substrate recognition and fidelity, but it is likely to regulate PKA association with regulatory subunits and other binding partners. To date, a complete understanding of the molecular determinants for this intramolecular mechanism is still lacking. Here, we used an integrated NMR-restrained molecular dynamics simulations and a Markov Model to characterize the free energy landscape and conformational transitions of the catalytic subunit of protein kinase A (PKA-C). We found that the apo-enzyme populates a broad free energy basin featuring a conformational ensemble of the active state of PKA-C (ground state) and other basins with lower populations (excited states). The first excited state corresponds to a previously characterized inactive state of PKA-C with the αC helix swinging outward. The second excited state displays a disrupted hydrophobic packing around the regulatory (R) spine, with a flipped configuration of the F100 and F102 residues at the tip of the αC-ß4 loop. To experimentally validate the second excited state, we mutated F100 into alanine and used NMR spectroscopy to characterize the binding thermodynamics and structural response of ATP and a prototypical peptide substrate. While the activity of PKA-CF100A toward a prototypical peptide substrate is unaltered and the enzyme retains its affinity for ATP and substrate, this mutation rearranges the αC-ß4 loop conformation interrupting the allosteric coupling between nucleotide and substrate. The highly conserved αC-ß4 loop emerges as a pivotal element able to modulate the synergistic binding between nucleotide and substrate and may affect PKA signalosome. These results may explain how insertion mutations within this motif affect drug sensitivity in other homologous kinases.

Multiomic prediction of therapeutic targets for human diseases associated with protein phase separation.

The phenomenon of protein phase separation (PPS) underlies a wide range of cellular functions. Correspondingly, the dysregulation of the PPS process has been associated with numerous human diseases. To enable therapeutic interventions based on the regulation of this association, possible targets should be identified. For this purpose, we present an approach that combines the multiomic PandaOmics platform with the FuzDrop method to identify PPS-prone disease-associated proteins. Using this approach, we prioritize candidates with high PandaOmics and FuzDrop scores using a profiling method that accounts for a wide range of parameters relevant for disease mechanism and pharmacological intervention. We validate the differential phase separation behaviors of three predicted Alzheimer's disease targets (MARCKS, CAMKK2, and p62) in two cell models of this disease. Overall, the approach that we present generates a list of possible therapeutic targets for human diseases associated with the dysregulation of the PPS process.

Optimization of a small molecule inhibitor of secondary nucleation in α-synuclein aggregation.

Parkinson's disease is characterised by the deposition in the brain of amyloid aggregates of α-synuclein. The surfaces of these amyloid aggregates can catalyse the formation of new aggregates, giving rise to a positive feedback mechanism responsible for the rapid proliferation of α-synuclein deposits. We report a procedure to enhance the potency of a small molecule to inhibit the aggregate proliferation process using a combination of in silico and in vitro methods. The optimized small molecule shows potency already at a compound:protein stoichiometry of 1:20. These results illustrate a strategy to accelerate the optimisation of small molecules against α-synuclein aggregation by targeting secondary nucleation.

Probing the effects of N-terminal acetylation on α-synuclein structure, aggregation and cytotoxicity.

Parkinson's disease is associated with the aberrant aggregation of α-synuclein within brain cells. Although the causes of this process are still unclear, post-translational modifications of α-synuclein are likely to play a modulatory role. Since α-synuclein is constitutively N-terminally acetylated, we previously investigated how this protein modification affects the aggregation behavior of the protein using a variety of methods in vitro and in cell systems. This chapter describes the production of N-terminally acetylated (NTA) α-synuclein, the preparation of different seeds of NTA α-synuclein for aggregation assays and the experimental methods for the kinetic analysis of the aggregation process of NTA α-synuclein. We also detail our protocol to evaluate the effects of preformed protofibrils of NTA α-synuclein in cell-based assays. These methods can be applied to study other post-translational modifications of α-synuclein, or adapted for the study of N-acetylation of other aggregation-prone proteins.

Secondary Processes Dominate the Quiescent, Spontaneous Aggregation of α-Synuclein at Physiological pH with Sodium Salts.

The accurate recapitulation in an in vitro assay of the aggregation process of α-synuclein in Parkinson's disease has been a significant challenge. As α-synuclein does not aggregate spontaneously in most currently used in vitro assays, primary nucleation is triggered by the presence of surfaces such as lipid membranes or interfaces created by shaking, to achieve aggregation on accessible time scales. In addition, secondary nucleation is typically only observed by lowering the pH below 5.8. Here we investigated assay conditions that enables spontaneous primary nucleation and secondary nucleation at pH 7.4. Using 400 mM sodium phosphate, we observed quiescent spontaneous aggregation of α-synuclein and established that this aggregation is dominated by secondary processes. Furthermore, the presence of potassium ions enhanced the reproducibility of quiescent α-synuclein aggregation. This work provides a framework for the study of spontaneous α-synuclein aggregation at physiological pH.

Determination of the Structure and Dynamics of the Fuzzy Coat of an Amyloid Fibril of IAPP Using Cryo-Electron Microscopy.

In recent years, major advances in cryo-electron microscopy (cryo-EM) have enabled the routine determination of complex biomolecular structures at atomistic resolution. An open challenge for this approach, however, concerns large systems that exhibit continuous dynamics. To address this problem, we developed the metadynamic electron microscopy metainference (MEMMI) method, which incorporates metadynamics, an enhanced conformational sampling approach, into the metainference method of integrative structural biology. MEMMI enables the simultaneous determination of the structure and dynamics of large heterogeneous systems by combining cryo-EM density maps with prior information through molecular dynamics, while at the same time modeling the different sources of error. To illustrate the method, we apply it to elucidate the dynamics of an amyloid fibril of the islet amyloid polypeptide (IAPP). The resulting conformational ensemble provides an accurate description of the structural variability of the disordered region of the amyloid fibril, known as fuzzy coat. The conformational ensemble also reveals that in nearly half of the structural core of this amyloid fibril, the side chains exhibit liquid-like dynamics despite the presence of the highly ordered network backbone of hydrogen bonds characteristic of the cross-ß structure of amyloid fibrils.

Quantitative Attribution of the Protective Effects of Aminosterols against Protein Aggregates to Their Chemical Structures and Ability to Modulate Biological Membranes.

Natural aminosterols are promising drug candidates against neurodegenerative diseases, like Alzheimer and Parkinson, and one relevant protective mechanism occurs via their binding to biological membranes and displacement or binding inhibition of amyloidogenic proteins and their cytotoxic oligomers. We compared three chemically different aminosterols, finding that they exhibited different (i) binding affinities, (ii) charge neutralizations, (iii) mechanical reinforcements, and (iv) key lipid redistributions within membranes of reconstituted liposomes. They also had different potencies (EC50) in protecting cultured cell membranes against amyloid-ß oligomers. A global fitting analysis led to an analytical equation describing quantitatively the protective effects of aminosterols as a function of their concentration and relevant membrane effects. The analysis correlates aminosterol-mediated protection with well-defined chemical moieties, including the polyamine group inducing a partial membrane-neutralizing effect (79 ± 7%) and the cholestane-like tail causing lipid redistribution and bilayer mechanical resistance (21 ± 7%), linking quantitatively their chemistry to their protective effects on biological membranes.

Thermodynamic and kinetic approaches for drug discovery to target protein misfolding and aggregation.

INTRODUCTION: Protein misfolding diseases, including Alzheimer's and Parkinson's diseases, are characterized by the aberrant aggregation of proteins. These conditions are still largely untreatable, despite having a major impact on our healthcare systems and societies. AREAS COVERED: We describe drug discovery strategies to target protein misfolding and aggregation. We compare thermodynamic approaches, which are based on the stabilization of the native states of proteins, with kinetic approaches, which are based on the slowing down of the aggregation process. This comparison is carried out in terms of the current knowledge of the process of protein misfolding and aggregation, the mechanisms of disease and the therapeutic targets. EXPERT OPINION: There is an unmet need for disease-modifying treatments that target protein misfolding and aggregation for the over 50 human disorders known to be associated with this phenomenon. With the approval of the first drugs that can prevent misfolding or inhibit aggregation, future efforts will be focused on the discovery of effective compounds with these mechanisms of action for a wide range of conditions.

Case report of a patient with unclassified tauopathy with molecular and neuropathological features of both progressive supranuclear palsy and corticobasal degeneration.

Progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD) are distinct clinicopathological subtypes of frontotemporal lobar degeneration. They both have atypical parkinsonism, and they usually have distinct clinical features. The most common clinical presentation of PSP is Richardson syndrome, and the most common presentation of CBD is corticobasal syndrome. In this report, we describe a patient with a five-year history of Richardson syndrome and a family history of PSP in her mother and sister. A tau PET scan (18F-APN-1607) revealed low-to-moderate uptake in the substantia nigra, globus pallidus, thalamus and posterior cortical areas, including temporal, parietal and occipital cortices. Neuropathological evaluation revealed widespread neuronal and glial tau pathology in cortical and subcortical structures, including tufted astrocytes in the motor cortex, striatum and midbrain tegmentum. The subthalamic nucleus had mild-to-moderate neuronal loss with globose neurofibrillary tangles, consistent with PSP. On the other hand, there were also astrocytic plaques, a pathological hallmark of CBD, in the neocortex and striatum. To further characterize the mixed pathology, we applied two machine learning-based diagnostic pipelines. These models suggested diagnoses of PSP and CBD depending on the brain region - PSP in the motor cortex and superior frontal gyrus and CBD in caudate nucleus. Western blots of insoluble tau from motor cortex showed a banding pattern consistent with mixed features of PSP and CBD, whereas tau from the superior frontal gyrus showed a pattern consistent with CBD. Real-time quaking-induced conversion (RT-QuIC) using brain homogenates from the motor cortex and superior frontal gyrus showed ThT maxima consistent with PSP, while reaction kinetics were consistent with CBD. There were no pathogenic variants in MAPT with whole genome sequencing. We conclude that this patient had an unclassified tauopathy and features of both PSP and CBD. The different pathologies in specific brain regions suggests caution in diagnosis of tauopathies with limited sampling.