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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. 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引用次数: 0
摘要
了解基因突变对蛋白质结构的功能影响对于推动癌症研究和开发靶向疗法至关重要。主要的挑战在于如何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/) 是一个综合计算管道,旨在将癌症中的体细胞突变目录数据库中的突变数据与蛋白质数据库和 AlphaFold 模型中的蛋白质结构数据整合在一起。该管道首先获取一个 UniProt ID,然后映射相应的蛋白质数据库结构、重新编号残基并评估紊乱百分比。然后叠加突变数据,根据结构背景对突变进行分类,并使用 MolStar 等先进工具对突变进行可视化处理。这种方法可以详细分析突变如何通过影响 DNA 界面、配体结合位点和二聚体相互作用等关键区域来破坏蛋白质的功能。为了验证该管道,我们对 TP53 基因进行了案例研究,该基因是一种在癌症中经常发生突变的关键肿瘤抑制因子。该分析突出显示了 DNA 结合界面上最常见的突变,为深入了解其在癌症进展中的潜在作用提供了线索。Mut-Map 为阐明癌症相关突变的结构影响提供了强大的资源,为制定更有针对性的治疗策略铺平了道路,并加深了我们对蛋白质结构与功能关系的理解。
Mut-Map: Comprehensive Computational Pipeline for Structural Mapping and Analysis of Cancer-Associated Mutations.
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.
期刊介绍:
Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data.
The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.