{"title":"Chiral Carbon Nanodots Modulate α-Synuclein Homeostasis to Combat Parkinson's Disease.","authors":"Yurong Han, Yuqi Zhang, Jiahao Huang, Xiaodan Jia, Taka-Aki Ishibashi, Xiue Jiang","doi":"10.1002/smtd.202500557","DOIUrl":null,"url":null,"abstract":"<p><p>Inhibiting α-synuclein (α-syn) aggregation is an effective treatment for Parkinson's disease (PD), and chiral recognition of proteins offers a novel strategy for designing efficient inhibitors. However, the impact of chiral selectivity on α-syn aggregation and its regulatory mechanisms remain ambiguous. In this work, it is synthesized chiral carbon nanodots (CNDs), including L-CNDs, D-CNDs, and DL-CNDs, and found that D-CNDs exhibited the most potent inhibitory effect on α-syn aggregation. ¹H-¹⁵N heteronuclear single quantum coherence nuclear magnetic resonance spectroscopy revealed that CNDs primarily interact with α-syn through electrostatic interactions, with D-CNDs specifically targeting key aggregation-prone residues, thereby disrupting β-sheet formation and reducing fibril assembly. In contrast, L-CNDs and DL-CNDs exhibited limited inhibitory effects, attributed to their weak affinity for the non-amyloid-β component region. Moreover, CNDs efficiently crossed the blood-brain barrier, and D-CNDs significantly reduced α-syn accumulation, alleviated neuronal damage, and ameliorated cognitive function. This work underlines the critical role of chirality in modulating α-syn aggregation and provides a novel strategy for developing enantiomer-selective inhibitors for PD therapy.</p>","PeriodicalId":229,"journal":{"name":"Small Methods","volume":" ","pages":"e2500557"},"PeriodicalIF":10.7000,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Small Methods","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1002/smtd.202500557","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Inhibiting α-synuclein (α-syn) aggregation is an effective treatment for Parkinson's disease (PD), and chiral recognition of proteins offers a novel strategy for designing efficient inhibitors. However, the impact of chiral selectivity on α-syn aggregation and its regulatory mechanisms remain ambiguous. In this work, it is synthesized chiral carbon nanodots (CNDs), including L-CNDs, D-CNDs, and DL-CNDs, and found that D-CNDs exhibited the most potent inhibitory effect on α-syn aggregation. ¹H-¹⁵N heteronuclear single quantum coherence nuclear magnetic resonance spectroscopy revealed that CNDs primarily interact with α-syn through electrostatic interactions, with D-CNDs specifically targeting key aggregation-prone residues, thereby disrupting β-sheet formation and reducing fibril assembly. In contrast, L-CNDs and DL-CNDs exhibited limited inhibitory effects, attributed to their weak affinity for the non-amyloid-β component region. Moreover, CNDs efficiently crossed the blood-brain barrier, and D-CNDs significantly reduced α-syn accumulation, alleviated neuronal damage, and ameliorated cognitive function. This work underlines the critical role of chirality in modulating α-syn aggregation and provides a novel strategy for developing enantiomer-selective inhibitors for PD therapy.
Small MethodsMaterials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍:
Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques.
With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community.
The online ISSN for Small Methods is 2366-9608.