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Mut-Map:用于癌症相关突变的结构映射和分析的综合计算流程。

Mut-Map: Comprehensive Computational Pipeline for Structural Mapping and Analysis of Cancer-Associated Mutations.

机构信息

Department of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.

出版信息

Brief Bioinform. 2024 Sep 23;25(6). doi: 10.1093/bib/bbae514.

DOI:10.1093/bib/bbae514
PMID:39413799
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11483132/
Abstract

Understanding the functional impact of genetic mutations on protein structures is essential for advancing cancer research and developing targeted therapies. The main challenge lies in accurately mapping these mutations to protein structures and analysing their effects on protein function. To address this, Mut-Map (https://genemutation.org/) is a comprehensive computational pipeline designed to integrate mutation data from the Catalogue Of Somatic Mutations In Cancer database with protein structural data from the Protein Data Bank and AlphaFold models. The pipeline begins by taking a UniProt ID and proceeds through mapping corresponding Protein Data Bank structures, renumbering residues, and assessing disorder percentages. It then overlays mutation data, categorizes mutations based on structural context, and visualizes them using advanced tools like MolStar. This approach allows for a detailed analysis of how mutations may disrupt protein function by affecting key regions such as DNA interfaces, ligand-binding sites, and dimer interactions. To validate the pipeline, a case study on the TP53 gene, a critical tumour suppressor often mutated in cancers, was conducted. The analysis highlighted the most frequent mutations occurring at the DNA-binding interface, providing insights into their potential role in cancer progression. Mut-Map offers a powerful resource for elucidating the structural implications of cancer-associated mutations, paving the way for more targeted therapeutic strategies and advancing our understanding of protein structure-function relationships.

摘要

理解基因突变对蛋白质结构的功能影响对于推进癌症研究和开发靶向疗法至关重要。主要的挑战在于准确地将这些突变映射到蛋白质结构上,并分析它们对蛋白质功能的影响。为了解决这个问题,Mut-Map(https://genemutation.org/)是一个全面的计算管道,旨在将来自癌症体细胞突变目录数据库的突变数据与来自蛋白质数据库和 AlphaFold 模型的蛋白质结构数据进行整合。该管道从 UniProt ID 开始,然后进行映射对应的蛋白质数据库结构、重新编号残基,并评估无序百分比。然后,它会叠加突变数据,根据结构上下文对突变进行分类,并使用 MolStar 等高级工具进行可视化。这种方法可以通过分析突变如何影响 DNA 接口、配体结合位点和二聚体相互作用等关键区域来详细了解它们如何破坏蛋白质功能。为了验证该管道,对 TP53 基因进行了案例研究,该基因是癌症中经常发生突变的关键肿瘤抑制基因。分析突出了在 DNA 结合界面发生的最常见突变,为它们在癌症进展中的潜在作用提供了一些见解。Mut-Map 提供了一个强大的资源,用于阐明癌症相关突变的结构影响,为更具针对性的治疗策略铺平了道路,并推进了我们对蛋白质结构-功能关系的理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfd1/11483132/5816284e236a/bbae514f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfd1/11483132/0abd697cda83/bbae514f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfd1/11483132/f1d8cfe8256f/bbae514f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfd1/11483132/5816284e236a/bbae514f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfd1/11483132/0abd697cda83/bbae514f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfd1/11483132/f1d8cfe8256f/bbae514f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfd1/11483132/5816284e236a/bbae514f3.jpg

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本文引用的文献

1
Mechanisms of action and resistance in histone methylation-targeted therapy.组蛋白甲基化靶向治疗的作用机制和耐药性。
Nature. 2024 Mar;627(8002):221-228. doi: 10.1038/s41586-024-07103-x. Epub 2024 Feb 21.
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How synonymous mutations alter enzyme structure and function over long timescales.同义突变如何在长时间尺度上改变酶的结构和功能。
Nat Chem. 2023 Mar;15(3):308-318. doi: 10.1038/s41557-022-01091-z. Epub 2022 Dec 5.
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RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning.
RCSB 蛋白质数据库(RCSB.org):提供实验测定的 PDB 结构以及来自人工智能/机器学习的 100 万个蛋白质计算结构模型。
Nucleic Acids Res. 2023 Jan 6;51(D1):D488-D508. doi: 10.1093/nar/gkac1077.
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Mutant p53 in cancer: from molecular mechanism to therapeutic modulation.癌症中的突变型 p53:从分子机制到治疗调节。
Cell Death Dis. 2022 Nov 18;13(11):974. doi: 10.1038/s41419-022-05408-1.
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PARP inhibition in breast cancer: progress made and future hopes.PARP抑制剂在乳腺癌中的应用:取得的进展与未来展望
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Highly accurate protein structure prediction with AlphaFold.利用 AlphaFold 进行高精度蛋白质结构预测。
Nature. 2021 Aug;596(7873):583-589. doi: 10.1038/s41586-021-03819-2. Epub 2021 Jul 15.
7
PDBrenum: A webserver and program providing Protein Data Bank files renumbered according to their UniProt sequences.PDBrenum:一个提供根据 UniProt 序列重新编号的蛋白质数据库文件的网络服务器和程序。
PLoS One. 2021 Jul 6;16(7):e0253411. doi: 10.1371/journal.pone.0253411. eCollection 2021.
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Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures.Mol* Viewer:用于大型生物分子结构的 3D 可视化和分析的现代 Web 应用程序。
Nucleic Acids Res. 2021 Jul 2;49(W1):W431-W437. doi: 10.1093/nar/gkab314.
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COSMIC: the Catalogue Of Somatic Mutations In Cancer.COSMIC:癌症体细胞突变目录。
Nucleic Acids Res. 2019 Jan 8;47(D1):D941-D947. doi: 10.1093/nar/gky1015.
10
Mutational processes shape the landscape of TP53 mutations in human cancer.突变过程塑造了人类癌症中 TP53 突变的景观。
Nat Genet. 2018 Oct;50(10):1381-1387. doi: 10.1038/s41588-018-0204-y. Epub 2018 Sep 17.