蛋白质组学与生物信息学在创伤性脑损伤生物标志物发现中的结合。

Biotechnologia Pub Date : 2025-06-30 eCollection Date: 2025-01-01 DOI:10.5114/bta/202470
Mohamed M Mohamed, El-Sayed A El-Absawy, Hala M Ahmed, Mohamed E Hasan
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引用次数: 0

摘要

背景:创伤性脑损伤(TBI)是一个重大的医学危机,没有fda批准的治疗方法来改善功能结局。关键的生物标志物,如胶质纤维酸性蛋白(GFAP)、S-100钙结合蛋白B (S-100B)和泛素c端水解酶L1 (UCH-L1),对理解脑外伤病理至关重要。材料和方法:本研究结合蛋白质组学和生物信息学方法,探索已建立的TBI生物标志物GFAP、S-100B和UCH-L1的结构和功能复杂性。结果:我们利用PredictProtein进行的综合二级结构和溶剂可及性评估证实了GFAP和S-100B中α -螺旋的优势,而ch - l1则显示了螺旋(65.00、67.39和40.81%)、β链(6.20、0和17.94%)和线圈(40.81、17.94和41.26%)的平衡混合。基于均方根偏差(RMSD)、TM-score和C-score评估,AlphaFold和I-TASSER被认为是预测三种靶蛋白全长三级结构的最佳服务器。蛋白质基序数据库扫描分别预测了GFAP、S-100B和UCH-L1的4个、8个和1个蛋白质结合基序和2个、3个和1个翻译后修饰。结论:GFAP在轴突转运和突触可塑性中的作用通过灯丝和DUF1664等基序得到强调。S-100/ icabp型钙结合结构域支持S-100B与脑损伤后神经炎症和氧化应激的关联。UCH-L1对TBI的双重影响被Peptidase_C12基序进一步阐明。这种方法加深了我们对这些生物标志物的理解,为TBI的靶向诊断铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Integration of proteomics and bioinformatics in traumatic brain injury biomarker discovery.

Integration of proteomics and bioinformatics in traumatic brain injury biomarker discovery.

Integration of proteomics and bioinformatics in traumatic brain injury biomarker discovery.

Integration of proteomics and bioinformatics in traumatic brain injury biomarker discovery.

Background: Traumatic brain injury (TBI) is a significant medical crisis with no FDA-approved therapies to improve functional outcomes. Key biomarkers, such as glial fibrillary acidic protein (GFAP), S-100 calcium-binding protein B (S-100B), and ubiquitin C-terminal hydrolase L1 (UCH-L1), are crucial for understanding TBI pathology.

Materials and methods: This study integrates proteomic and bioinformatic approaches to explore established TBI biomarkers' structural and functional complexities: GFAP, S-100B, and UCH-L1.

Results: Our comprehensive secondary structure and solvent accessibility assessment, conducted with PredictProtein, confirmed the predominance of alpha-helices in GFAP and S-100B, while UCH-L1 displayed a balanced mix of helices (65.00, 67.39, and 40.81%), beta strands (6.20, 0, and 17.94%), and coils (40.81, 17.94, and 41.26%). AlphaFold and I-TASSER were identified as the best servers for full-length tertiary structure prediction for the three target proteins, based on root-mean-square deviation (RMSD), TM-score, and C-score assessments. Protein motif database scans predicted four, eight, and one protein-binding motifs and two, three, and one post-translational modifications for GFAP, S-100B, and UCH-L1, respectively.

Conclusions: GFAP's role in axonal transport and synaptic plasticity was emphasized through motifs such as Filament and DUF1664. S-100B's association with neuroinflammation and oxidative stress post-TBI was supported by the S-100/ICaBP-type calcium-binding domain. UCH-L1's dualistic impact on TBI was further clarified by the Peptidase_C12 motif. This approach deepens our comprehension of these biomarkers and paves the way for targeted diagnostics in TBI.

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