[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125378-en":3,"doc-seo-125378-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},125378,13056703019662,"Evangeline","https://ap-avatar.wpscdn.com/avatar/be000253a8e92610077?_k=1778726343310543188",8,"Research & Report","Molecular Insights into α‑Synuclein Fibrillation - A Raman Spectroscopy and Machine Learning Approach","α-synuclein aggregation is pivotal in Lewy body diseases, including Parkinson’s disease and dementia with Lewy bodies. Aggregation proceeds through nucleation, elongation, and secondary nucleation with prion-like spreading. Raman spectroscopy combined with machine learning was used to characterize biomolecular changes during fibrillation of purified recombinant wild-type α-synuclein. Monomeric protein was incubated in a 7-day fibrillation assay, with stage-specific analysis and confirmation by negative staining TEM, mass spectrometry, and light scattering. PCA and UMAP-based modeling differentiated D1–D7 groups and linked evolving Raman peaks to shifts from α-helical structures to stabilized β-sheets and fibrillar stabilization, involving key amino-acid residues.","This article is licensed under CC-BY 4.0   \n[pubs.acs.org/chemneuro](pubs.acs.org/chemneuro)  Research Article   \nMolecular Insights into α‑Synuclein Fibrillation: A Raman Spectroscopy and Machine Learning Approach  \nNathan P. Coles, Suzan Elsheikh, Agathe Quesnel, Lucy Butler, Claire Jennings, Chaimaa Tarzi, Ojodomo J. Achadu, Meez Islam, Karunakaran Kalesh, Annalisa Occhipinti, Claudio Angione, Jon Marles-Wright, David J. Koss, Alan J. Thomas, Tiago F. Outeiro, Panagiota S. Filippou, and Ahmad A. Khundakar *  \nDownloaded via MPI MULTIDISCIPLINARY SCIENCES on February 24, 2025 at 10:04:48 (UTC) . See [https://pubs.acs.org/sharingguidelines](https://pubs.acs.org/sharingguidelines) for options on how to legitimately share published articles.  \n Cite This: ACS Chem. Neurosci. 2025, 16, 687−698  \nRead Online  \n\n|  |  |  |  |\n| --- | --- | --- | --- |\n| ACCESS   | Metrics & More |  |  Article Recommendations |\n\nABSTRACT: The aggregation of α-synuclein is crucial to the development of Lewy body diseases, including Parkinson’s disease and dementia with Lewy bodies. The aggregation pathway of α -synuclein typically involves a defined sequence of nucleation, elongation, and secondary nucleation, exhibiting prion-like spreading. This study employed Raman spectroscopy and machine learning analysis, alongside complementary techniques, to characterize the biomolecular changes during the fibrillation of purified recombinant wild-type α-synuclein protein. Monomeric α-synuclein was produced, purified, and subjected to a 7-day fibrillation assay to generate preformed fibrils. Stages of α-synuclein fibrillation were analyzed using Raman spectroscopy, with aggregation  \nconfirmed through negative staining transmission electron microscopy, mass spectrometry, and light scattering analyses. A machine learning pipeline incorporating principal component analysis and uniform manifold approximation and projection was used to analyze the Raman spectral data and identify significant peaks, resulting in differentiation between sample groups. Notable spectral shifts in α-synuclein were found in various stages of aggregation. Early changes (D1) included increases in α-helical structures (1303, 1330 cm−1) and β-sheet formation (1045 cm−1), with reductions in COO − and CH2 bond regions (1406, 1445 cm−1). By D4, these structural shifts persist with additional β-sheet features. At D7, a decrease in β-sheet H-bonding (1625 cm−1) and tyrosine ring breathing (830 cm−1) indicates further structural stabilization, suggesting a shift from initial helical structures to stabilized β-sheets and aggregated fibrils. Additionally, alterations in peaks related to tyrosine, alanine, proline, and glutamic acid were identified, emphasizing the role of these amino acids in intramolecular interactions during the transition from α-helical to β-sheet conformational states in α-synuclein fibrillation. This approach offers insight into α-synuclein aggregation, enhancing the understanding of its role in Lewy body disease pathophysiology and potential diagnostic relevance.  \nKEYWORDS: α-synuclein aggregation, Lewy body diseases, Raman spectroscopy, machine learning analysis, β-sheet formation, fibrillation pathway  \n■ INTRODUCTION sheet formation10, 11 and implicated in protein aggregation; 12  \nThe aberrant accumulation of α-synuclein is the key defining pathological feature of Lewy body diseases, such as Parkinson’s disease (PD) and dementia with Lewy bodies (DLB). 1−3 This culminates in the formation of Lewy bodies and neurites, disrupting cellular function and driving neurodegeneration asthe protein transitions from a soluble monomer to insoluble fibrils, a hallmark of disease progression.4−6 In its native form,α-synuclein is a soluble, monomeric protein with a molecular weight of 14,460.16 Da, composed of 140 amino acids.7 Its structure includes three distinct regions: the N-terminal domain (amino acids 1−60), which contains several repeat motifs (KTKEGV) critical for tetramer f","cbCaijOCnojmof8C","https://ap.wps.com/l/cbCaijOCnojmof8C","pdf",3836199,1,12,"English","en",105,"# Abstract\n# Introduction\n## α-synuclein structure and role in Lewy body diseases\n## Aggregation pathway overview\n# Raman spectroscopy and machine learning approach\n## Sample preparation and fibrillation assay design\n## Raman spectral analysis and multivariate modeling","[{\"question\":\"Why is α-synuclein aggregation important for Lewy body diseases?\",\"answer\":\"α-synuclein aggregation is a defining pathological feature of Lewy body diseases, driving formation of Lewy bodies and related neurodegeneration.\"},{\"question\":\"How were different stages of α-synuclein fibrillation analyzed?\",\"answer\":\"Purified recombinant α-synuclein was incubated for 7 days, generating fibrils at stages (e.g., D1–D7), which were analyzed using Raman spectroscopy and corroborated with TEM, mass spectrometry, and light scattering.\"},{\"question\":\"What role did machine learning play in the Raman spectroscopy results?\",\"answer\":\"A machine learning pipeline using principal component analysis and UMAP enabled identification of significant Raman peaks and differentiation between fibrillation sample groups.\"}]","Molecular Insights into α‑Synuclein Fibrillation - A Raman Spectroscopy and Machine Learning Approach | PDF",1785898561,30,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"molecular-insights-into-synuclein-fibrillation-a-raman-spectroscopy-and-machine-learning-approach-125378","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/molecular-insights-into-synuclein-fibrillation-a-raman-spectroscopy-and-machine-learning-approach-125378/125378/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is α-synuclein aggregation important for Lewy body diseases?","Question",{"text":75,"@type":76},"α-synuclein aggregation is a defining pathological feature of Lewy body diseases, driving formation of Lewy bodies and related neurodegeneration.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How were different stages of α-synuclein fibrillation analyzed?",{"text":80,"@type":76},"Purified recombinant α-synuclein was incubated for 7 days, generating fibrils at stages (e.g., D1–D7), which were analyzed using Raman spectroscopy and corroborated with TEM, mass spectrometry, and light scattering.",{"name":82,"@type":73,"acceptedAnswer":83},"What role did machine learning play in the Raman spectroscopy results?",{"text":84,"@type":76},"A machine learning pipeline using principal component analysis and UMAP enabled identification of significant Raman peaks and differentiation between fibrillation sample groups.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":29,"slug":121},"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]