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结构系统生物学方法阐明了外显子结合复合体相互作用网络中 SNP 的功能意义。

Structural systems biology approach delineate the functional implications of SNPs in exon junction complex interaction network.

机构信息

Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Anantapur, Andhra Pradesh, India.

Department of Physiology and Biophysics, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.

出版信息

J Biomol Struct Dyn. 2023;41(21):11969-11986. doi: 10.1080/07391102.2022.2164355. Epub 2023 Jan 8.

Abstract

In eukaryotes, transcripts that carry premature termination codons (PTC) leading to truncated proteins are degraded by the Nonsense Mediated Decay (NMD) machinery. Missense and nonsense Single Nucleotide Polymorphisms (SNPs) in proteins belonging to Exon junction complex (EJC) and up-frameshift protein (UPF) will compromise NMD leading to the accumulation of truncated proteins in various diseases. The EJC and UPF which are involved in NMD is a good model system to study the effect of SNPs at a system level. Despite the availability of crystal structures, computational tools, and data on mutational and deletion studies, with functional implications, an integrated effort to understand the impact of SNPs at the systems level is lacking. To study the functional consequences of missense SNPs, sequence-based techniques like SIFT and PolyPhen which classify SNPs as deleterious or non-deleterious and structure-based methods like FoldX which calculate the Delta Delta G, (ddGs, ∆∆G) are used. Using FoldX, the ddG for mutations with experimentally validated functional effects is calculated and compared with those calculated for SNPs in the same protein-protein interaction interface. Further, a model is conceived to explain the functional implications of SNPs based on the effects observed for known mutants. The results are visualized in a network format. The effects of nonsense mutations are discerned by comparing with deletion mutation studies and loss of interaction in the crystal structure. The present work not only integrates genomics, proteomics, and classical genetics with 'Structural Biology' but also helps to integrate it into a 'systems-level functional network'.Communicated by Ramaswamy H. Sarma.

摘要

在真核生物中,携带导致截短蛋白的提前终止密码子(PTC)的转录本被无意义介导的衰变(NMD)机制降解。属于外显子结合复合物(EJC)和上移框移蛋白(UPF)的蛋白质中的错义和无义单核苷酸多态性(SNP)将损害 NMD,导致各种疾病中截短蛋白的积累。参与 NMD 的 EJC 和 UPF 是研究 SNP 系统水平影响的良好模型系统。尽管有晶体结构、计算工具和关于突变和缺失研究的数据,但具有功能意义的 SNP 系统水平综合研究仍然缺乏。为了研究错义 SNP 的功能后果,使用了基于序列的技术,如 SIFT 和 PolyPhen,它们将 SNP 分类为有害或非有害,以及基于结构的方法,如 FoldX,它计算 Delta Delta G(ddGs,∆∆G)。使用 FoldX,计算了具有实验验证的功能影响的突变的 ddG,并将其与同一蛋白质-蛋白质相互作用界面中的 SNP 计算的 ddG 进行比较。此外,根据已知突变体观察到的效果,提出了一个模型来解释 SNP 的功能意义。结果以网络格式可视化。通过与缺失突变研究和晶体结构中相互作用的丧失进行比较,可以辨别无意义突变的影响。这项工作不仅将基因组学、蛋白质组学和经典遗传学与“结构生物学”集成在一起,而且还有助于将其集成到“系统级功能网络”中。由 Ramaswamy H. Sarma 传达。

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