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利用 Machaon 识别和分析 SARS-CoV-2 的 Spike 蛋白与其他病毒或宿主蛋白之间的结构相似性。

Identifying and profiling structural similarities between Spike of SARS-CoV-2 and other viral or host proteins with Machaon.

机构信息

Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, Ilisia, 157 84, Athens, Greece.

Biomedical Research Foundation of the Academy of Athens, 4 Soranou Ephessiou St., 115 27, Athens, Greece.

出版信息

Commun Biol. 2023 Jul 19;6(1):752. doi: 10.1038/s42003-023-05076-7.

Abstract

Using protein structure to predict function, interactions, and evolutionary history is still an open challenge, with existing approaches relying extensively on protein homology and families. Here, we present Machaon, a data-driven method combining orientation invariant metrics on phi-psi angles, inter-residue contacts and surface complexity. It can be readily applied on whole structures or segments-such as domains and binding sites. Machaon was applied on SARS-CoV-2 Spike monomers of native, Delta and Omicron variants and identified correlations with a wide range of viral proteins from close to distant taxonomy ranks, as well as host proteins, such as ACE2 receptor. Machaon's meta-analysis of the results highlights structural, chemical and transcriptional similarities between the Spike monomer and human proteins, indicating a multi-level viral mimicry. This extended analysis also revealed relationships of the Spike protein with biological processes such as ubiquitination and angiogenesis and highlighted different patterns in virus attachment among the studied variants. Available at: https://machaonweb.com .

摘要

利用蛋白质结构预测功能、相互作用和进化历史仍然是一个开放性的挑战,现有的方法广泛依赖于蛋白质同源性和家族。在这里,我们介绍了 Machaon,这是一种数据驱动的方法,结合了 phi-psi 角、残基间接触和表面复杂度的不变量测度。它可以很容易地应用于整个结构或片段,如结构域和结合位点。Machaon 应用于 SARS-CoV-2 刺突单体的天然、Delta 和奥密克戎变体,并确定了与从密切到遥远分类等级的各种病毒蛋白以及宿主蛋白(如 ACE2 受体)的相关性。Machaon 对结果的元分析突出了 Spike 单体与人类蛋白之间的结构、化学和转录相似性,表明存在多层次的病毒模拟。这种扩展分析还揭示了 Spike 蛋白与泛素化和血管生成等生物过程的关系,并强调了研究变体中病毒附着的不同模式。可在:https://machaonweb.com 获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b6b/10356814/eb706f6ff0a1/42003_2023_5076_Fig1_HTML.jpg

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