Molecular Insights into the Misfolding and Dimerization Dynamics of the Full-Length α-Synuclein from Atomistic Discrete Molecular Dynamics Simulations

Structures prediction and replica exchange molecular dynamics simulations of α-synuclein: A case study for intrinsically disordered proteins

In recent years, a variety of three-dimensional structure prediction tools, including AlphaFold2, AlphaFold3, I-TASSER, C-I-TASSER, Phyre2, ESMFold, and RoseTTAFold, have been employed in the investigation of intrinsically disordered proteins. However, a comprehensive validation of these tools specifically for intrinsically disordered proteins has yet to be conducted. In this study, we utilize AlphaFold2, AlphaFold3, I-TASSER, C-I-TASSER, Phyre2, ESMFold, and RoseTTAFold to predict the structure of a model intrinsically disordered α-synuclein protein. Additionally, extensive replica exchange molecular dynamics simulations of the intrinsically disordered protein are conducted. The resulting structures from both structure prediction tools and replica exchange molecular dynamics simulations are analyzed for radius of gyration, secondary and tertiary structure properties, as well as Cα and Hα chemical shift values. A comparison of the obtained results with experimental data reveals that replica exchange molecular dynamics simulations provide results in excellent agreement with experimental observations. However, none of the structure prediction tools utilized in this study can fully capture the structural characteristics of the model intrinsically disordered protein. This study shows that a cluster of ensembles are required for intrinsically disordered proteins. Artificial-intelligence based structure prediction tools such as AlphaFold3 and C-I-TASSER could benefit from stochastic sampling or Monte Carlo simulations for generating an ensemble of structures for intrinsically disordered proteins.

Wild-Type α-Synuclein Structure and Aggregation: A Comprehensive Coarse-Grained and All-Atom Molecular Dynamics Study

α-Synuclein (α-syn) is a 140 amino acid intrinsically disordered protein (IDP) and the primary component of cytotoxic oligomers implicated in the etiology of Parkinson's disease (PD). While IDPs lack a stable three-dimensional structure, they sample a heterogeneous ensemble of conformations that can, in principle, be assessed through molecular dynamics simulations. However, describing the structure and aggregation of large IDPs is challenging due to force field (FF) accuracy and sampling limitations. To cope with the latter, coarse-grained (CG) FFs emerge as a potential alternative at the expense of atomic detail loss. Whereas CG models can accurately describe the structure of the monomer, less is known about aggregation. The latter is key for assessing aggregation pathways and designing aggregation inhibitor drugs. Herein, we investigate the structure and dynamics of α-syn using different resolution CG (Martini3 and Sirah2) and all-atom (Amber99sb and Charmm36m) FFs to gain insight into the differences and resemblances between these models. The dependence of the magnitude of protein-water interactions and the putative need for enhanced sampling (replica exchange) methods in CG simulations are analyzed to distinguish between force field accuracy and sampling limitations. The stability of the CG models of an α-syn fibril was also investigated. Additionally, α-syn aggregation was studied through umbrella sampling for the CG models and CG/all-atom models for an 11-mer peptide (NACore) from an amyloidogenic domain of α-syn. Our results show that despite the α-syn structures of Martini3 and Sirah2 with enhanced protein-water interactions being similar, major differences exist concerning aggregation. The Martini3 fibril is not stable, and the binding free energy of α-syn and NACore is positive, opposite to Sirah2. Sirah2 peptides in a zwitterionic form, in turn, display termini interactions that are too strong, resulting in end-to-end orientation. Sirah2, with enhanced protein-water interactions and neutral termini, provides, however, a peptide aggregation free energy profile similar to that found with all-atom models. Overall, we find that Sirah2 with enhanced protein-water interactions is suitable for studying protein-protein and protein-drug aggregation.

Elucidating the Molecular Basis of 14-3-3 Interaction with α-Synuclein: Insights from Molecular Dynamics Simulations and the Design of a Novel Protein-Protein Interaction Inhibitor

Parkinson's disease is a widespread age-related neurodegenerative disorder characterized by the loss of dopaminergic neurons in the midbrain along with the appearance of protein aggregates, termed as "Lewy bodies" in the surviving neuronal cells. The components of Lewy bodies include proteins such as α-synuclein, 14-3-3, Parkin, and LRRK2, along with other cellular organelles, which, in their native state, perform a plethora of vital biological functions within the human biome. Formation of these aggregates renders these components inactive, thereby interfering with homeostasis. In this regard, the current study attempts to investigate the complexation behavior of all human-based 14-3-3 isoforms with α-synuclein via a combination of classical and enhanced sampling techniques and thereby determine the causality of these protein-protein interactions. The study indicated that upon complexation, the aggregation propensity of both 14-3-3 and α-synuclein increases, and this increment is propelled by the interfacial residues on either protein. Furthermore, mutagenesis studies revealed that Lys214 of 14-3-3 (henceforth termed K214A) is crucial for the formation of this binary complex. Principal component analysis combined with clustering studies unveiled the stability of these complexes in terms of their conformational distribution across the entire MD trajectory. For K214A, these clustered states were sparsely located, thereby making the transitions between them slightly difficult. Dynamic cross-correlation maps (DCCM) revealed the role of residues in the range 80-130 of 14-3-3 having a potential allosteric role in driving this complexation process. Finally, a novel peptide-based supramolecular inhibitor was designed, which exhibited higher proficiency in limiting the 14-3-3/α-synuclein interaction compared to the previous inhibitor model. It was also revealed that the presence of this inhibitor induces structural rigidity in α-synuclein, making changes in its conformations extremely difficult, as observed through Umbrella Sampling studies. Based on available information, the current study provides an insight into the molecular-level understanding of protein-protein interactions underlying Parkinson's disease and adds on to the methods of devising novel therapeutic approaches to treat the same.

Advanced computational approaches to understand protein aggregation

Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.

Exploring Structural Insights of Aβ42 and α-Synuclein Monomers and Heterodimer: A Comparative Study Using Implicit and Explicit Solvent Simulations

Protein misfolding, aggregation, and fibril formation play a central role in the development of severe neurological disorders, including Alzheimer's and Parkinson's diseases. The structural stability of mature fibrils in these diseases is of great importance, as organisms struggle to effectively eliminate amyloid plaques. To address this issue, it is crucial to investigate the early stages of fibril formation when monomers aggregate into small, toxic, and soluble oligomers. However, these structures are inherently disordered, making them challenging to study through experimental approaches. Recently, it has been shown experimentally that amyloid-β 42 (Aβ42) and α-synuclein (α-Syn) can coassemble. This has motivated us to investigate the interaction between their monomers as a first step toward exploring the possibility of forming heterodimeric complexes. In particular, our study involves the utilization of various Amber and CHARMM force-fields, employing both implicit and explicit solvent models in replica exchange and conventional simulation modes. This comprehensive approach allowed us to assess the strengths and weaknesses of these solvent models and force fields in comparison to experimental and theoretical findings, ensuring the highest level of robustness. Our investigations revealed that Aβ42 and α-Syn monomers can indeed form stable heterodimers, and the resulting heterodimeric model exhibits stronger interactions compared to the Aβ42 dimer. The binding of α-Syn to Aβ42 reduces the propensity of Aβ42 to adopt fibril-prone conformations and induces significant changes in its conformational properties. Notably, in AMBER-FB15 and CHARMM36m force fields with the use of explicit solvent, the presence of Aβ42 significantly increases the β-content of α-Syn, consistent with the experiments showing that Aβ42 triggers α-Syn aggregation. Our analysis clearly shows that although the use of implicit solvent resulted in too large compactness of monomeric α-Syn, structural properties of monomeric Aβ42 and the heterodimer were preserved in explicit-solvent simulations. We anticipate that our study sheds light on the interaction between α-Syn and Aβ42 proteins, thus providing the atom-level model required to assess the initial stage of aggregation mechanisms related to Alzheimer's and Parkinson's diseases.

Computational investigation of copper-mediated conformational changes in α-synuclein dimer

We report molecular dynamics simulation of dimers of α-synuclein, the peptide closely associated with onset of Parkinson's disease, both as metal-free dimer and with inter-chain bridging provided by Cu(II) ions. Our investigation reveals that the presence of copper-induced inter-chain bridging not only stabilizes α-synuclein dimers, but also leads to enhanced β-sheet formation at critical regions within the N-terminal and NAC regions of the protein. These contacts are larger and longer-lived in the presence of copper, and as a result each peptide chain is more extended and less flexible than in the metal-free dimer. The persistence of these inter-peptide contacts underscores their significance in stabilising the dimers, potentially influencing the aggregation pathway. Moreover, the increased flexibility in the two termini, as well as the absence of persistent contacts in the metal-free dimer, correlates with the presence of amorphous aggregates. This phenomenon is known to mitigate fibrillation, while their absence in the metal-bound dimer suggests an increased propensity to form fibrils in the presence of copper ions.

Deciphering the influence of Y12L and N17H substitutions on the conformation and oligomerization of human calcitonin

The abnormal aggregation of human calcitonin (hCT) hormone peptides impairs their physiological function, leading to harmful immune responses and cytotoxicity, which limits their clinical utility. Interestingly, a representative hCT analog incorporating Y12L and N17H substitutions (DM-hCT) has shown reduced aggregation tendencies while maintaining bioactivity. But the molecular mechanism of Y12L and N17H substitutions on the conformational dynamics of hCT remains unclear. Here, we systematically investigated the folding and self-assembly dynamics of hCT and DM-hCT using atomistic discrete molecular dynamics (DMD) simulations. Our findings revealed that hCT monomers predominantly adopted unstructured conformations with dynamic helices. Oligomerization of hCT resulted in the formation of β-sheet-rich aggregates and β-barrel intermediates. The Y12L and N17H substitutions enhanced helical conformations and suppressed β-sheet formation in both monomers and oligomers. These substitutions stabilized the dynamic helices and disrupted aromatic interactions responsible for β-sheet formation at residue 12. Notably, DM-hCT assemblies still exhibited β-sheets in phenylalanine-rich and C-terminal hydrophobic regions, suggesting that future optimizations should focus on these areas. Our simulations provide insights into the molecular mechanisms underlying hCT aggregation and the amyloid-resistant effects of Y12L and N17H substitutions. These findings have valuable implications for the development of clinical hCT analogs.

UiO-66-NH2 Metal-Organic Framework for the Detection of Alzheimer's Biomarker Aβ (1-42)

Neurodegenerative disorders pose a significant challenge to global healthcare, with Alzheimer's disease (AD) being one of the most prevalent forms. Early and accurate detection of amyloid-β (Aβ) (1-42) monomers, a key biomarker of AD pathology, is crucial for effective diagnosis and intervention of the disease. Current gold standard detection techniques for Aβ include enzyme-linked immunosorbent assay and surface plasmon resonance. Although reliable, they are limited by their cost and time-consuming nature, thus restricting their point-of-care applicability. Here we present a sensitive and rapid colorimetric sensor for the detection of Aβ (1-42) monomers within 5 min. This was achieved by harnessing the peroxidase-like activity of metal-loaded metal-organic frameworks (MOFs), specifically UiO-66-NH2, coupled with the strong affinity of Aβ (1-42) to the MOFs. Various metal-loaded MOFs were synthesized and investigated, and platinum-loaded UiO-66-NH2 was identified as the optimal candidate for our purpose. The Pt-loaded UiO-66-NH2 sensor demonstrated detection limits of 2.76 and 4.65 nM Aβ (1-42) monomers in water and cerebrospinal fluid, respectively, with a linear range from 0.75 to 25 nM (R2 = 0.9712), outperforming traditional detection techniques in terms of both detection time and complexity. Moreover, the assay was specific toward Aβ (1-42) monomers when evaluated against interfering compounds. The rapid and cost-effective sensor may help circumvent the limitations of conventional detection methods, thus providing a promising avenue for early AD diagnosis and facilitating improved clinical outcomes.

Co-aggregation of α-synuclein with amyloid-β stabilizes β-sheet-rich oligomers and enhances the formation of β-barrels

Alzheimer's disease (AD) and Parkinson's disease (PD) are the two most common neurodegenerative diseases with markedly different pathological features of β-amyloid (Aβ) plaques and α-synuclein (αS) Lewy bodies (LBs), respectively. However, clinical overlaps in symptoms and pathologies between AD and PD are commonly observed caused by the cross-interaction between Aβ and αS. To uncover the molecular mechanisms behind their overlapping symptoms and pathologies, we computationally investigated the impact of αS on an Aβ monomer and dimerization using atomistic discrete molecular dynamics simulations (DMD). Our results revealed that αS could directly interact with Aβ monomers and dimers, thus forming β-sheet-rich oligomers, including potentially toxic β-barrel intermediates. The binding hotspot involved the second half of the N-terminal domain and NAC region in αS, along with residues 10-21 and 31-42 in Aβ. In their hetero-complex, the binding hotspot primarily assumed a β-sheet core buried inside, which was dynamically shielded by the highly charged, amyloid-resistant C-terminus of αS. Because the amyloid prion region was the same as the binding hotspot being buried, their fibrillization may be delayed, causing the toxic oligomers to increase. This study sheds light on the intricate relationship between Aβ and αS and provides insights into the overlapping pathology of AD and PD.

Unveiling Medin Folding and Dimerization Dynamics and Conformations via Atomistic Discrete Molecular Dynamics Simulations

Medin is a principal component of localized amyloid found in the vasculature of individuals over 50 years old. Its amyloid aggregation has been linked to endothelial dysfunction and vascular inflammation, contributing to the pathogenesis of various vascular diseases. Despite its significance, the structures of the medin monomer, oligomer, and fibril remain elusive, and the dynamic processes of medin aggregation are not fully understood. In this study, we comprehensively investigated the medin folding and dimerization dynamics and conformations using atomistic discrete molecular dynamics simulations. Our simulation results suggested that the folding initiation of the medin involved the formation of β-sheets around medin30-41 and medin42-50, with subsequent capping of other segments to their β-sheet edges. Medin monomers typically consisted of three or four β-strands, along with a dynamic N-terminal helix. Two isolated medin peptides readily aggregated into a β-sheet-rich dimer, displaying a strong aggregation propensity. Dimerization of medin not only enhanced the β-sheet conformations but also led to the formation of β-barrel oligomers. The aggregation tendencies of medin1-18 and medin19-29 were relatively weak. However, the segments of medin30-41 and medin42-50 played a crucial role as they primarily formed a β-sheet core and facilitated medin1-18 and medin19-29 to form intra- and interpeptide β-sheets. The findings highlight the critical role of the medin30-41 and medin42-50 regions in stabilizing the monomer structure and driving the medin amyloid aggregation. These regions could potentially serve as promising targets for designing antiamyloid inhibitors against amyloid aggregation of medin. Additionally, our study provides a full picture of the monomer conformations and dimerization dynamics for medin, which will help better understand the pathology of medin aggregation.

Entropy driven cooperativity effect in multi-site drug optimization targeting SARS-CoV-2 papain-like protease

Papain-like protease (PLpro), a non-structural protein encoded by SARS-CoV-2, is an important therapeutic target. Regions 1 and 5 of an existing drug, GRL0617, can be optimized to produce cooperativity with PLpro binding, resulting in stronger binding affinity. This work investigated the origin of the cooperativity using molecular dynamics simulations combined with the interaction entropy (IE) method. The regions' improvement exhibits cooperativity by calculating the binding free energies between the complex of PLpro-inhibitor. The thermodynamic integration method further verified the cooperativity generated in the drug improvement. To further determine the specific source of cooperativity, enthalpy and entropy in the complexes were calculated using molecular mechanics/generalized Born surface area and IE. The results show that the entropic change is an important contributor to the cooperativity. Our study also identified residues P248, Q269, and T301 that play a significant role in cooperativity. The optimization of the inhibitor stabilizes these residues and minimizes the entropic loss, and the cooperativity observed in the binding free energy can be attributed to the change in the entropic contribution of these residues. Based on our research, the application of cooperativity can facilitate drug optimization, and provide theoretical ideas for drug development that leverage cooperativity by reducing the contribution of entropy through multi-locus binding.

In Silico Evaluation of the Potential Association of the Pathogenic Mutations of Alpha Synuclein Protein with Induction of Synucleinopathies

Alpha synuclein (α-Syn) is a neuronal protein encoded by the SNCA gene and is involved in the development of Parkinson's disease (PD). The objective of this study was to examine in silico the functional implications of non-synonymous single nucleotide polymorphisms (nsSNPs) in the SNCA gene. We used a range of computational algorithms such as sequence conservation, structural analysis, physicochemical properties, and machine learning. The sequence of the SNCA gene was analyzed, resulting in the mapping of 42,272 SNPs that are classified into different functional categories. A total of 177 nsSNPs were identified within the coding region; there were 20 variants that may influence the α-Syn protein structure and function. This identification was made by employing different analytical tools including SIFT, PolyPhen2, Mut-pred, SNAP2, PANTHER, PhD-SNP, SNP&Go, MUpro, Cosurf, I-Mut, and HOPE. Three mutations, V82A, K80E, and E46K, were selected for further examinations due to their spatial positioning within the α-Syn as determined by PyMol. Results indicated that these mutations may affect the stability and function of α-Syn. Then, a molecular dynamics simulation was conducted for the SNCA wildtype and the four mutant variants (p.A18G, p.V82A, p.K80E, and p.E46K). The simulation examined temperature, pressure, density, root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), and radius of gyration (Rg). The data indicate that the mutations p.V82A, p.K80E, and p.E46K reduce the stability and functionality of α-Syn. These findings highlight the importance of understanding the impact of nsSNPs on α-syn structure and function. Our results required verifications in further protein functional and case-control studies. After being verified these findings can be used in genetic testing for the early diagnosis of PD, the evaluation of the risk factors, and therapeutic approaches.

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.

Exploring Intra- and Inter-Regional Interactions in the IDP α-Synuclein Using smFRET and MD Simulations

Theoretical concepts from polymer physics are often used to describe intrinsically disordered proteins (IDPs). However, amino acid interactions within and between regions of the protein can lead to deviations from typical polymer scaling behavior and even to short-lived secondary structures. To investigate the key interactions in the dynamic IDP α-synuclein (αS) at the amino acid level, we conducted single-molecule fluorescence resonance energy transfer (smFRET) experiments and coarse-grained molecular dynamics (CG-MD) simulations. We find excellent agreement between experiments and simulations. Our results show that a physiological salt solution is a good solvent for αS and that the protein is highly dynamic throughout its entire chain, with local intra- and inter-regional interactions leading to deviations from global scaling. Specifically, we observe expansion in the C-terminal region, compaction in the NAC region, and a slightly smaller distance between the C- and N-termini than expected. Our simulations indicate that the compaction in the NAC region results from hydrophobic aliphatic contacts, mostly between valine and alanine residues, and cation-π interactions between lysine and tyrosine. In addition, hydrogen bonds also seem to contribute to the compaction of the NAC region. The expansion of the C-terminal region is due to intraregional electrostatic repulsion and increased chain stiffness from several prolines. Overall, our study demonstrates the effectiveness of combining smFRET experiments with CG-MD simulations to investigate the key interactions in highly dynamic IDPs at the amino acid level.

SEVI Inhibits Aβ Amyloid Aggregation by Capping the β-Sheet Elongation Edges

Inhibiting the aggregation of amyloid peptides with endogenous peptides has broad interest due to their intrinsically high biocompatibility and low immunogenicity. Here, we investigated the inhibition mechanism of the prostatic acidic phosphatase fragment SEVI (semen-derived enhancer of viral infection) against Aβ42 fibrillization using atomistic discrete molecular dynamic simulations. Our result revealed that SEVI was intrinsically disordered with dynamic formation of residual helices. With a high positive net charge, the self-aggregation tendency of SEVI was weak. Aβ42 had a strong aggregation propensity by readily self-assembling into β-sheet-rich aggregates. SEVI preferred to interact with Aβ42, rather than SEVI themselves. In the heteroaggregates, Aβ42 mainly adopted β-sheets buried inside and capped by SEVI in the outer layer. SEVI could bind to various Aβ aggregation species─including monomers, dimers, and proto-fibrils─by capping the exposed β-sheet elongation edges. The aggregation processes Aβ42 from the formation of oligomers to conformational nucleation into fibrils and fibril growth should be inhibited as their β-sheet elongation edges are being occupied by the highly charged SEVI. Overall, our computational study uncovered the molecular mechanism of experimentally observed inhibition of SEVI against Aβ42 aggregation, providing novel insights into the development of therapeutic strategies against Alzheimer's disease.

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.

Multifaceted interactions mediated by intrinsically disordered regions play key roles in alpha synuclein aggregation

The aggregation of Alpha Synuclein (α-Syn) into fibrils is associated with the pathology of several neurodegenerative diseases. Pathologic aggregates of α-Syn adopt multiple fibril topologies and are known to be transferred between cells via templated seeding. Monomeric α-Syn is an intrinsically disordered protein (IDP) with amphiphilic N-terminal, hydrophobic-central, and negatively charged C-terminal domains. Here, we review recent work elucidating the mechanism of α-Syn aggregation and identify the key and multifaceted roles played by the N- and C-terminal domains in the initiation and growth of aggregates as well as in the templated seeding involved in cell-to-cell propagation. The charge content of the C-terminal domain, which is sensitive to environmental conditions like organelle pH, is a key regulator of intermolecular interactions involved in fibril growth and templated propagation. An appreciation of the complex and multifaceted roles played by the intrinsically disordered terminal domains suggests novel opportunities for the development of potent inhibitors against synucleinopathies.

Effect of Electric Field on α-Synuclein Fibrils: Revealed by Molecular Dynamics Simulations

The self-association of amylogenic proteins to the fibril form is considered a pivotal factor in the pathogenesis of neurodegenerative diseases, including Parkinson’s disease (PD). PD causes unintended or uncontrollable movements in its common symptoms. α-synuclein is the major cause of PD development and thus has been the main target of numerous studies to suppress and sequester its expression or effectively degrade it. Nonetheless, to date, there are no efficient and proven ways to prevent pathological protein aggregation. Recent investigations proposed applying an external electric field to interrupt the fibrils. This method is a non-invasive approach that has a certain benefit over others. We performed molecular dynamics (MD) simulations by applying an electric field on highly toxic fibrils of α-synuclein to gain a molecular-level insight into fibril disruption mechanisms. The results revealed that the applied external electric field induces substantial changes in the conformation of the α-synuclein fibrils. Furthermore, we show the threshold value for electric field strength required to completely disrupt the α-synuclein fibrils by opening the hydrophobic core of the fibril. Thus, our findings might serve as a valuable foundation to better understand molecular-level mechanisms of the α-synuclein fibrils disaggregation process under an applied external electric field.