MUT-MAP：用于癌症相关突变的结构映射和分析的综合计算管道
Mut-Map: Comprehensive Computational Pipeline for Structural Mapping and Analysis of Cancer-Associated Mutations
影响因子:7.70000
分区:生物学2区 / 数学与计算生物学1区 生化研究方法2区
发表日期:2024 Sep 23
作者:
Ali F Alsulami
摘要
了解遗传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。主要挑战在于将这些突变准确地映射到蛋白质结构上，并分析其对蛋白质功能的影响。为了解决这个问题，mut-map（https://genemutty.org/）是一种综合计算管道，旨在将癌症数据库中体细胞突变目录的突变数据与蛋白质数据库和alphafold模型的蛋白质结构数据相结合。管道首先采用Uniprot ID，并通过映射相应的蛋白质数据库结构，重新包含残基并评估疾病百分比。然后，它覆盖了突变数据，根据结构环境对突变进行分类，并使用Molstar等先进工具对其进行可视化。这种方法允许对突变如何通过影响诸如DNA界面，配体结合位点和二聚体相互作用之类的关键区域来破坏蛋白质功能的详细分析。为了验证管道，对TP53基因的案例研究是一种经常在癌症中突变的临界肿瘤抑制剂。该分析强调了在DNA结合界面上发生的最常见的突变，从而洞悉了它们在癌症进展中的潜在作用。 Mut-Map提供了一种强大的资源，用于阐明与癌症相关突变的结构含义，为更具针对性的治疗策略铺平了道路，并促进了我们对蛋白质结构 - 功能关系关系的理解。
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.