Effects of Mutations and Post-Translational Modifications on α-Synuclein In Vitro Aggregation

Post-translational modification sites are present in hydrophilic cavities of alpha-synuclein, tau, FUS, and TDP-43 fibrils: A molecular dynamics study

Hydration plays a crucial role in the refolding of intrinsically disordered proteins into amyloid fibrils; however, the specific interactions between water and protein that may contribute to this process are still unknown. In our previous studies of alpha-synuclein (aSyn), we have shown that waters confined in fibril cavities are stabilizing features of this pathological fold; and that amino acids that hydrogen bond with these confined waters modulate primary and seeded aggregation. Here, we extend our aSyn molecular dynamics (MD) simulations with three new polymorphs and correlate MD trajectory information with known post-translational modifications (PTMs) and experimental data. We show that cavity residues are more evolutionarily conserved than non-cavity residues and are enriched with PTM sites. As expected, the confinement within hydrophilic cavities results in more stably hydrated amino acids. Interestingly, cavity PTM sites display the longest protein-water hydrogen bond lifetimes, three-fold greater than non-PTM cavity sites. Utilizing the deep mutational screen dataset by Newberry et al. and the Thioflavin T aggregation review by Pancoe et al. parsed using a fibril cavity/non-cavity definition, we show that hydrophobic changes to amino acids in cavities have a larger effect on fitness and aggregation rate than residues outside cavities, supporting our hypothesis that these sites are involved in the inhibition of aSyn toxic fibrillization. Finally, we expand our study to include analysis of fibril structures of tau, FUS, TDP-43, prion, and hnRNPA1; all of which contained hydrated cavities, with tau, FUS, and TDP-43 recapitulating our PTM results in aSyn fibril cavities.

Protein Oxidative Modifications in Neurodegenerative Diseases: From Advances in Detection and Modelling to Their Use as Disease Biomarkers

Oxidation-reduction post-translational modifications (redox-PTMs) are chemical alterations to amino acids of proteins. Redox-PTMs participate in the regulation of protein conformation, localization and function, acting as signalling effectors that impact many essential biochemical processes in the cells. Crucially, the dysregulation of redox-PTMs of proteins has been implicated in the pathophysiology of numerous human diseases, including neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease. This review aims to highlight the current gaps in knowledge in the field of redox-PTMs biology and to explore new methodological advances in proteomics and computational modelling that will pave the way for a better understanding of the role and therapeutic potential of redox-PTMs of proteins in neurodegenerative diseases. Here, we summarize the main types of redox-PTMs of proteins while providing examples of their occurrence in neurodegenerative diseases and an overview of the state-of-the-art methods used for their detection. We explore the potential of novel computational modelling approaches as essential tools to obtain insights into the precise role of redox-PTMs in regulating protein structure and function. We also discuss the complex crosstalk between various PTMs that occur in living cells. Finally, we argue that redox-PTMs of proteins could be used in the future as diagnosis and prognosis biomarkers for neurodegenerative diseases.

Post-translational Modification of α-Synuclein Modifies Monomer Dynamics and Aggregation Kinetics

The intrinsically disordered protein α-Synuclein is identified as a major toxic aggregate in Parkinson's as well as several other neurodegenerative diseases. Recent work on this protein has focused on the effects of posttranslational modifications on aggregation kinetics. Among these, O-GlcNAcylation of α-Synuclein has been observed to inhibit the aggregation propensity of the protein. Here we investigate the monomer dynamics of two O-GlcNAcylated α-Synucleins, α-Syn(gT72) and α-Syn(gS87) and correlate them with the aggregation kinetics. We find that, compared to the unmodified protein, glycosylation at T72 makes the protein less compact and more diffusive while glycosylation at S87 makes the protein more compact and less diffusive. Based on a model of the earliest steps in aggregation, we predict that T72 should aggregate slower than unmodified protein, which is confirmed by ThT fluorescence measurements. In contrast, S87 should aggregate faster, which is not mirrored in ThT kinetics of later fibril formation but does not rule out a higher rate of formation of small oligomers. Together, these results show that posttranslational modifications do not uniformly affect aggregation propensity.

O-GlcNAc forces an α-synuclein amyloid strain with notably diminished seeding and pathology

Amyloid-forming proteins such α-synuclein and tau, which are implicated in Alzheimer's and Parkinson's disease, can form different fibril structures or strains with distinct toxic properties, seeding activities and pathology. Understanding the determinants contributing to the formation of different amyloid features could open new avenues for developing disease-specific diagnostics and therapies. Here we report that O-GlcNAc modification of α-synuclein monomers results in the formation of amyloid fibril with distinct core structure, as revealed by cryogenic electron microscopy, and diminished seeding activity in seeding-based neuronal and rodent models of Parkinson's disease. Although the mechanisms underpinning the seeding neutralization activity of the O-GlcNAc-modified fibrils remain unclear, our in vitro mechanistic studies indicate that heat shock proteins interactions with O-GlcNAc fibril inhibit their seeding activity, suggesting that the O-GlcNAc modification may alter the interactome of the α-synuclein fibrils in ways that lead to reduce seeding activity in vivo. Our results show that posttranslational modifications, such as O-GlcNAc modification, of α-synuclein are key determinants of α-synuclein amyloid strains and pathogenicity.

Highly tunable bimane-based fluorescent probes: design, synthesis, and application as a selective amyloid binding dye

Small molecule fluorescent probes are indispensable tools for a broad range of biological applications. Despite many probes being available, there is still a need for probes where photophysical properties and biological selectivity can be tuned as desired. Here, we report the rational design and synthesis of a palette of fluorescent probes based on the underexplored bimane scaffold. The newly developed probes with varied electronic properties show tunable absorption and emission in the visible region with large Stokes shifts. Probes featuring electron-donating groups exhibit rotor effects that are sensitive to polarity and viscosity by "intramolecular charge transfer" (ICT) and twisted intramolecular charge transfer (TICT) mechanisms, respectively. These properties enable their application as "turn-on" fluorescent probes to detect fibrillar aggregates of the α-synuclein (αS) protein that are a hallmark of Parkinson's disease (PD). One probe shows selective binding to αS fibrils relative to soluble proteins in cell lysates and amyloid fibrils of tau and amyloid-β. Finally, we demonstrate the diagnostic potential of the probe in selectively detecting αS fibrils amplified from PD with dementia (PDD) patient samples.

Post-translational modifications of proteins in cardiovascular diseases examined by proteomic approaches

Over 400 different types of post-translational modifications (PTMs) have been reported and over 200 various types of PTMs have been discovered using mass spectrometry (MS)-based proteomics. MS-based proteomics has proven to be a powerful method capable of global PTM mapping with the identification of modified proteins/peptides, the localization of PTM sites and PTM quantitation. PTMs play regulatory roles in protein functions, activities and interactions in various heart related diseases, such as ischemia/reperfusion injury, cardiomyopathy and heart failure. The recognition of PTMs that are specific to cardiovascular pathology and the clarification of the mechanisms underlying these PTMs at molecular levels are crucial for discovery of novel biomarkers and application in a clinical setting. With sensitive MS instrumentation and novel biostatistical methods for precise processing of the data, low-abundance PTMs can be successfully detected and the beneficial or unfavorable effects of specific PTMs on cardiac function can be determined. Moreover, computational proteomic strategies that can predict PTM sites based on MS data have gained an increasing interest and can contribute to characterization of PTM profiles in cardiovascular disorders. More recently, machine learning- and deep learning-based methods have been employed to predict the locations of PTMs and explore PTM crosstalk. In this review article, the types of PTMs are briefly overviewed, approaches for PTM identification/quantitation in MS-based proteomics are discussed and recently published proteomic studies on PTMs associated with cardiovascular diseases are included.

RNA sequestration driven by amyloid formation: the alpha synuclein case

Nucleic acids can act as potent modulators of protein aggregation, and RNA has the ability to either hinder or facilitate protein assembly, depending on the molecular context. In this study, we utilized a computational approach to characterize the physico-chemical properties of regions involved in amyloid aggregation. In various experimental datasets, we observed that while the core is hydrophobic and highly ordered, external regions, which are more disordered, display a distinct tendency to interact with nucleic acids. To validate our predictions, we performed aggregation assays with alpha-synuclein (aS140), a non-nucleic acid-binding amyloidogenic protein, and a mutant truncated at the acidic C-terminus (aS103), which is predicted to have a higher tendency to interact with RNA. For both aS140 and aS103, we observed an acceleration of aggregation upon RNA addition, with a significantly stronger effect for aS103. Due to favorable electrostatics, we noted an enhanced nucleic acid sequestration ability for the aggregated aS103, allowing it to entrap a larger amount of RNA compared to the aggregated wild-type counterpart. Overall, our research suggests that RNA sequestration might be a common phenomenon linked to protein aggregation, constituting a gain-of-function mechanism that warrants further investigation.

The Effects of Lipids on α-Synuclein Aggregation In Vitro

The small neuronal protein α-synuclein (αS) is found in pre-synaptic terminals and plays a role in vesicle recycling and neurotransmission. Fibrillar aggregates of αS are the hallmark of Parkinson's disease and related neurodegenerative disorders. In both health and disease, interactions with lipids influence αS's structure and function, prompting much study of the effects of lipids on αS aggregation. A comprehensive collection (126 examples) of aggregation rate data for various αS/lipid combinations was presented, including combinations of lipid variations and mutations or post-translational modifications of αS. These data were interpreted in terms of lipid structure to identify general trends. These tabulated data serve as a resource for the community to help in the interpretation of aggregation experiments with lipids and to be potentially used as inputs for computational models of lipid effects on aggregation.

Combining non-canonical amino acid mutagenesis and native chemical ligation for multiply modifying proteins: A case study of α-synuclein post-translational modifications

The Parkinson's disease associated protein α-synuclein (αS) has been found to contain numerous post-translational modifications (PTMs), in both physiological and pathological states. One PTM site of particular interest is serine 87, which is subject to both O-linked β-N-acetylglucosamine (gS) modification and phosphorylation (pS), with αS-pS87 enriched in Parkinson's disease. An often-overlooked aspect of these PTMs is their effect on the membrane-binding properties of αS, which are important to its role in regulating neurotransmitter release. Here, we show how one can study these effects by synthesizing αS constructs containing authentic PTMs and labels for single molecule fluorescence correlation spectroscopy measurements. We synthesize αS-gS87 and αS-pS87 by combining native chemical ligation with genetic code expansion approaches. We introduce the fluorophore by a click reaction with a non-canonical amino acid. Beyond the specific problem of PTM effects on αS, our studies highlight the value of this combination of methods for multiply modifying proteins.

AggBERT: Best in Class Prediction of Hexapeptide Amyloidogenesis with a Semi-Supervised ProtBERT Model

The prediction of peptide amyloidogenesis is a challenging problem in the field of protein folding. Large language models, such as the ProtBERT model, have recently emerged as powerful tools in analyzing protein sequences for applications, such as predicting protein structure and function. In this article, we describe the use of a semisupervised and fine-tuned ProtBERT model to predict peptide amyloidogenesis from sequences alone. Our approach, which we call AggBERT, achieved state-of-the-art performance, demonstrating the potential for large language models to improve the accuracy and speed of amyloid fibril prediction over simple heuristics or structure-based approaches. This work highlights the transformative potential of machine learning and large language models in the fields of chemical biology and biomedicine.

A Novel Brain PET Radiotracer for Imaging Alpha Synuclein Fibrils in Multiple System Atrophy

Abnormal α-synuclein (α-syn) aggregation characterizes α-synucleinopathies, including Parkinson's disease (PD) and multiple system atrophy (MSA). However, no suitable positron emission tomography (PET) radiotracer for imaging α-syn in PD and MSA exists currently. Our structure-activity relationship studies identified 4-methoxy-N-(4-(3-(pyridin-2-yl)-3,8-diazabicyclo[3.2.1]octan-8-yl)phenyl)benzamide (4i) as a PET radiotracer candidate for imaging α-syn. In vitro assays revealed high binding of 4i to recombinant α-syn fibrils (inhibition constant (Ki) = 6.1 nM) and low affinity for amyloid beta (Aβ) fibrils in Alzheimer's disease (AD) homogenates. However, [3H]4i also exhibited high specific binding to AD, progressive supranuclear palsy, and corticobasal degeneration tissues as well as PD and MSA tissues, suggesting notable affinity to tau. Nevertheless, the specific binding to pathologic α-syn aggregates in MSA post-mortem brain tissues was significantly higher than in PD tissues. This finding demonstrated the potential use of [11C]4i as a PET tracer for imaging α-syn in MSA patients. Nonhuman primate PET studies confirmed good brain uptake and rapid washout for [11C]4i.

The Bidirectional Interplay of α-Synuclein with Lipids in the Central Nervous System and Its Implications for the Pathogenesis of Parkinson's Disease

The alteration and aggregation of alpha-synuclein (α-syn) play a crucial role in neurodegenerative diseases collectively termed as synucleinopathies, including Parkinson's disease (PD). The bidirectional interaction of α-syn with lipids and biomembranes impacts not only α-syn aggregation but also lipid homeostasis. Indeed, lipid composition and metabolism are severely perturbed in PD. One explanation for lipid-associated alterations may involve structural changes in α-syn, caused, for example, by missense mutations in the lipid-binding region of α-syn as well as post-translational modifications such as phosphorylation, acetylation, nitration, ubiquitination, truncation, glycosylation, and glycation. Notably, different strategies targeting the α-syn-lipid interaction have been identified and are able to reduce α-syn pathology. These approaches include the modulation of post-translational modifications aiming to reduce the aggregation of α-syn and modify its binding properties to lipid membranes. Furthermore, targeting enzymes involved in various steps of lipid metabolism and exploring the neuroprotective potential of lipids themselves have emerged as novel therapeutic approaches. Taken together, this review focuses on the bidirectional crosstalk of α-syn and lipids and how alterations of this interaction affect PD and thereby open a window for therapeutic interventions.

E46K Mutation of α-Synuclein Preorganizes the Intramolecular Interactions Crucial for Aggregation

Aggregation of α-synuclein is central to the pathogenesis of Parkinson's disease. The most toxic familial mutation E46K accelerates the aggregation process by an unknown mechanism. Herein, we provide a clue by investigating the influence of E46K on monomeric α-synuclein and its relation to aggregation with molecular dynamics simulations. The E46K mutation suppresses β-sheet structures in the N-terminus while promoting those at the key fibrillization region named NACore. Even though WT and E46K monomers share conserved intramolecular interactions with fibrils, E46K abolishes intramolecular contacts within the N-terminus which are present in the WT monomer but absent in fibrils. Network analysis identifies residues 36-53 as the interaction core of the WT monomer. Upon mutation, residues 36-46 are expelled to water due to aggravated electrostatic repulsion in the 43KTKK46 segment. Instead, NACore (residues 68-78) becomes the interaction hub and connects preceding residues 47-56 and the C-terminus. Consequently, residues 47-95 which belong to the fibril core form more compact β-sheets. Overall, the interaction network of E46K is more like fibrils than WT, stabilizing the fibril-like conformations. Our work provides mechanistic insights into the faster aggregation of the E46K mutant. It implies a close link between monomeric conformations and fibrils, which would spur the development of therapeutic strategies.

Identification of a Putative α-synuclein Radioligand Using an in silico Similarity Search

PURPOSE

Previous studies from our lab utilized an ultra-high throughput screening method to identify compound 1 as a small molecule that binds to alpha-synuclein (α-synuclein) fibrils. The goal of the current study was to conduct a similarity search of 1 to identify structural analogs having improved in vitro binding properties for this target that could be labeled with radionuclides for both in vitro and in vivo studies for measuring α-synuclein aggregates.

METHODS

Using 1 as a lead compound in a similarity search, isoxazole derivative 15 was identified to bind to α-synuclein fibrils with high affinity in competition binding assays. A photocrosslinkable version was used to confirm binding site preference. Derivative 21, the iodo-analog of 15, was synthesized, and subsequently radiolabeled isotopologs [125I]21 and [11C]21 were successfully synthesized for use in in vitro and in vivo studies, respectively. [125I]21 was used in radioligand binding studies in post-mortem Parkinson's disease (PD) and Alzheimer's disease (AD) brain homogenates. In vivo imaging of an α-synuclein mouse model and non-human primates was performed with [11C]21.

RESULTS

In silico molecular docking and molecular dynamic simulation studies for a panel of compounds identified through a similarity search, were shown to correlate with Ki values obtained from in vitro binding studies. Improved affinity of isoxazole derivative 15 for α-synuclein binding site 9 was indicated by photocrosslinking studies with CLX10. Design and successful (radio)synthesis of iodo-analog 21 of isoxazole derivative 15 enabled further in vitro and in vivo evaluation. Kd values obtained in vitro with [125I]21 for α-synuclein and Aβ42 fibrils were 0.48 ± 0.08 nM and 2.47 ± 1.30 nM, respectively. [125I]21 showed higher binding in human postmortem PD brain tissue compared with AD tissue, and low binding in control brain tissue. Lastly, in vivo preclinical PET imaging showed elevated retention of [11C]21 in PFF-injected mouse brain. However, in PBS-injected control mouse brain, slow washout of the tracer indicates high non-specific binding. [11C]21 showed high initial brain uptake in a healthy non-human primate, followed by fast washout that may be caused by rapid metabolic rate (21% intact [11C]21 in blood at 5 min p.i.).

CONCLUSION

Through a relatively simple ligand-based similarity search, we identified a new radioligand that binds with high affinity (<10 nM) to α-synuclein fibrils and PD tissue. Although the radioligand has suboptimal selectivity for α-synuclein towards Aβ and high non-specific binding, we show here that a simple in silico approach is a promising strategy to identify novel ligands for target proteins in the CNS with the potential to be radiolabeled for PET neuroimaging studies.

Dissecting the Self-assembly Dynamics of Imperfect Repeats in α-Synuclein

The pathological aggregation of α-synuclein (αS) into amyloid fibrils is the hallmark of Parkinson's disease (PD). The self-assembly and membrane interactions of αS are mainly governed by the seven imperfect 11-residue repeats of the XKTKEGVXXXX motif around residues 1-95. However, the particular role of each repeat in αS fibrillization remains unclear. To answer this question, we studied the aggregation dynamics of each repeat with up to 10 peptides in silico by conducting multiple independent micro-second atomistic discrete molecular dynamics simulations. Our simulations revealed that only repeats R3 and R6 readily self-assembled into β-sheet-rich oligomers, while the other repeats remained as unstructured monomers with weak self-assembly and β-sheet propensities. The self-assembly process of R3 featured frequent conformational changes with β-sheet formation mainly in the non-conserved hydrophobic tail, whereas R6 spontaneously self-assembled into extended and stable cross-β structures. These results of seven repeats are consistent with their structures and organization in recently solved αS fibrils. As the primary amyloidogenic core, R6 was buried inside the central cross-β core of all αS fibrils, attracting the hydrophobic tails of adjacent R4, R5, and R7 repeats forming β-sheets around R6 in the core. Further away from R6 in the sequence but with a moderate amyloid aggregation propensity, the R3 tail could serve as a secondary amyloidogenic core and form independent β-sheets in the fibril. Overall, our results demonstrate the critical role of R3 and R6 repeats in αS amyloid aggregation and suggest their potential as targets for the peptide-based and small-molecule amyloid inhibitors.

FRETing about the details: Case studies in the use of a genetically encoded fluorescent amino acid for distance-dependent energy transfer

Förster resonance energy transfer (FRET) is a valuable method for monitoring protein conformation and biomolecular interactions. Intrinsically fluorescent amino acids that can be genetically encoded, such as acridonylalanine (Acd), are particularly useful for FRET studies. However, quantitative interpretation of FRET data to derive distance information requires careful use of controls and consideration of photophysical effects. Here we present two case studies illustrating how Acd can be used in FRET experiments to study small molecule induced conformational changes and multicomponent biomolecular complexes.

O-GlcNAc modification forces the formation of an α-Synuclein amyloid-strain with notably diminished seeding activity and pathology

The process of amyloid fibril formation remains one of the primary targets for developing diagnostics and treatments for several neurodegenerative diseases (NDDs). Amyloid-forming proteins such α-Synuclein and Tau, which are implicated in the pathogenesis of Alzheimer's and Parkinson's disease, can form different types of fibril structure, or strains, that exhibit distinct structures, toxic properties, seeding activities, and pathology spreading patterns in the brain. Therefore, understanding the molecular and structural determinants contributing to the formation of different amyloid strains or their distinct features could open new avenues for developing disease-specific diagnostics and therapies. In this work, we report that O-GlcNAc modification of α-Synuclein monomers results in the formation of amyloid fibril with distinct core structure, as revealed by Cryo-EM, and diminished seeding activity in seeding-based neuronal and rodent models of Parkinson's disease. Although the mechanisms underpinning the seeding neutralization activity of the O-GlcNAc modified fibrils remain unclear, our in vitro mechanistic studies indicate that heat shock proteins interactions with O-GlcNAc fibril inhibit their seeding activity, suggesting that the O-GlcNAc modification may alter the interactome of the α-Synuclein fibrils in ways that lead to reduce seeding activity in vivo. Our results show that post-translational modifications, such as O-GlcNAc modification, of α-Synuclein are key determinants of α-Synuclein amyloid strains and pathogenicity. These findings have significant implications for how we investigate and target amyloids in the brain and could possibly explain the lack of correlation between amyloid burden and neurodegeneration or cognitive decline in some subtypes of NDDs.

Computational Chemistry for the Identification of Lead Compounds for Radiotracer Development

The use of computer-aided drug design (CADD) for the identification of lead compounds in radiotracer development is steadily increasing. Traditional CADD methods, such as structure-based and ligand-based virtual screening and optimization, have been successfully utilized in many drug discovery programs and are highlighted throughout this review. First, we discuss the use of virtual screening for hit identification at the beginning of drug discovery programs. This is followed by an analysis of how the hits derived from virtual screening can be filtered and culled to highly probable candidates to test in in vitro assays. We then illustrate how CADD can be used to optimize the potency of experimentally validated hit compounds from virtual screening for use in positron emission tomography (PET). Finally, we conclude with a survey of the newest techniques in CADD employing machine learning (ML).