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人工智能预测与结直肠癌相关的癌胚抗原结构及相互作用

Artificial intelligence prediction of carcinoembryonic antigen structure and interactions relevant for colorectal cancer.

作者信息

Shabo Ivan, Nordling Erik, Abraham-Nordling Mirna

机构信息

Endocrine and Sarcoma Surgery Unit, Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.

Swedish Orphan Biovitrum AB, Stockholm, 112 76, Sweden.

出版信息

Biochem Biophys Rep. 2025 Apr 21;42:102024. doi: 10.1016/j.bbrep.2025.102024. eCollection 2025 Jun.

DOI:10.1016/j.bbrep.2025.102024
PMID:40330074
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12051046/
Abstract

Carcinoembryonic antigen (CEA) is used as a biomarker for colorectal cancer. It is expressed during fetal development but in healthy adult cells the expression is low. Due to its size and the high degree of glycosylation, there are no structures available for mature CEA. By employing novel structure prediction methods, we aim to investigate CEA tertiary structure and interactions. Alphafold 3 server has increased the accuracy of structure predictions and allows for modelling of glycans in proteins and complexes. Models were created for a monomeric CEA, dimeric CEA and for CEA in complex with the antibody Tusamitamab. The structure of the monomeric glycosylated CEA exhibit two bends, one in the domain interface B1-A2 and one in the domain interface B2-A3. The dimer structure pairs in a parallel manner, with direct contacts in the N and the A2 domains of the two chains. The complex of CEA with Tusamitamab closely resembles the EM structure of the complex that was released after the training of Alphafold 3 was completed. Overall, the investigations give new angles to investigate for CEA. The predicted bend, primarily in the B2 and A3 domain interface, would allow for dimer formation of CEA from both the same cell as from adjacent cells and could help to explain the outstanding issue on how it can fulfil both tasks. The prediction of the antibody binding to CEA was accurate, the all-atom RMSD was 1.3 Å. This is encouraging for other antibody - protein complexes predictions as the complex structure was not part of the training set for Alphafold 3.

摘要

癌胚抗原(CEA)被用作结直肠癌的生物标志物。它在胎儿发育过程中表达,但在健康成年细胞中表达水平较低。由于其大小和高度糖基化,目前尚无成熟CEA的结构信息。通过采用新颖的结构预测方法,我们旨在研究CEA的三级结构及其相互作用。Alphafold 3服务器提高了结构预测的准确性,并能够对蛋白质和复合物中的聚糖进行建模。我们创建了单体CEA、二聚体CEA以及CEA与抗体Tusamitamab复合物的模型。单体糖基化CEA的结构呈现两个弯曲,一个在结构域界面B1 - A2,另一个在结构域界面B2 - A3。二聚体结构以平行方式配对,两条链的N结构域和A2结构域存在直接接触。CEA与Tusamitamab的复合物与Alphafold 3训练完成后发布的复合物的电子显微镜结构非常相似。总体而言,这些研究为CEA的研究提供了新的视角。预测的弯曲主要在B2和A3结构域界面,这将允许CEA在同一细胞内以及相邻细胞间形成二聚体,并有助于解释其如何同时完成两项任务这一悬而未决的问题。抗体与CEA结合的预测结果准确,全原子均方根偏差(RMSD)为1.3埃。由于该复合物结构并非Alphafold 3训练集的一部分,这对于其他抗体 - 蛋白质复合物的预测来说是令人鼓舞的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9857/12051046/8399f5d82d58/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9857/12051046/875f9be9301a/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9857/12051046/959b8e940f8b/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9857/12051046/481ed7ef1ec4/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9857/12051046/41cbeefb959c/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9857/12051046/8399f5d82d58/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9857/12051046/875f9be9301a/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9857/12051046/959b8e940f8b/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9857/12051046/481ed7ef1ec4/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9857/12051046/41cbeefb959c/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9857/12051046/8399f5d82d58/gr4.jpg

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Structural insights into epitope-paratope interactions of a monoclonal antibody targeting CEACAM5-expressing tumors.针对表达 CEACAM5 的肿瘤的单克隆抗体的表位-抗体结合位相互作用的结构见解。
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利用 AlphaFold 3 进行生物分子相互作用的精确结构预测。
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Significance of carcinoembryonic antigen detection in the early diagnosis of colorectal cancer: A systematic review and meta-analysis.癌胚抗原检测在结直肠癌早期诊断中的意义:一项系统评价与荟萃分析
World J Gastrointest Surg. 2023 Dec 27;15(12):2907-2918. doi: 10.4240/wjgs.v15.i12.2907.
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AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences.2024 年的 AlphaFold 蛋白质结构数据库:为超过 2.14 亿个蛋白质序列提供结构覆盖。
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