Mutz Pascal, Camargo Antonio Pedro, Sahakyan Harutyun, Neri Uri, Butkovic Anamarija, Wolf Yuri I, Krupovic Mart, Dolja Valerian V, Koonin Eugene V
Division of Intramural Research, Computational Biology Branch, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.
Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, California, USA.
mBio. 2025 Feb 5;16(2):e0320024. doi: 10.1128/mbio.03200-24. Epub 2024 Dec 23.
Metatranscriptomics is uncovering more and more diverse families of viruses with RNA genomes comprising the viral kingdom Orthornavirae in the realm Riboviria. Thorough protein annotation and comparison are essential to get insights into the functions of viral proteins and virus evolution. In addition to sequence- and hmm profile‑based methods, protein structure comparison adds a powerful tool to uncover protein functions and relationships. We constructed an Orthornavirae "structurome" consisting of already annotated as well as unannotated ("dark matter") proteins and domains encoded in viral genomes. We used protein structure modeling and similarity searches to illuminate the remaining dark matter in hundreds of thousands of orthornavirus genomes. The vast majority of the dark matter domains showed either "generic" folds, such as single α-helices, or no high confidence structure predictions. Nevertheless, a variety of lineage-specific globular domains that were new either to orthornaviruses in general or to particular virus families were identified within the proteomic dark matter of orthornaviruses, including several predicted nucleic acid-binding domains and nucleases. In addition, we identified a case of exaptation of a cellular nucleoside monophosphate kinase as an RNA-binding protein in several virus families. Notwithstanding the continuing discovery of numerous orthornaviruses, it appears that all the protein domains conserved in large groups of viruses have already been identified. The rest of the viral proteome seems to be dominated by poorly structured domains including intrinsically disordered ones that likely mediate specific virus-host interactions.
Advanced methods for protein structure prediction, such as AlphaFold2, greatly expand our capability to identify protein domains and infer their likely functions and evolutionary relationships. This is particularly pertinent for proteins encoded by viruses that are known to evolve rapidly and as a result often cannot be adequately characterized by analysis of the protein sequences. We performed an exhaustive structure prediction and comparative analysis for uncharacterized proteins and domains ("dark matter") encoded by viruses with RNA genomes. The results show the dark matter of RNA virus proteome consists mostly of disordered and all-α-helical domains that cannot be readily assigned a specific function and that likely mediate various interactions between viral proteins and between viral and host proteins. The great majority of globular proteins and domains of RNA viruses are already known although we identified several unexpected domains represented in individual viral families.
宏转录组学正在揭示越来越多具有RNA基因组的病毒家族，这些病毒构成了核糖病毒域中的正核糖病毒界。全面的蛋白质注释和比较对于深入了解病毒蛋白的功能和病毒进化至关重要。除了基于序列和隐马尔可夫模型（HMM）谱的方法外，蛋白质结构比较为揭示蛋白质功能和关系增添了一个强大的工具。我们构建了一个正核糖病毒“结构组”，它由病毒基因组中已注释以及未注释（“暗物质”）的蛋白质和结构域组成。我们使用蛋白质结构建模和相似性搜索来阐明数十万个正核糖病毒基因组中剩余的暗物质。绝大多数暗物质结构域呈现出“通用”折叠，如单α螺旋，或者没有高可信度的结构预测。然而，在正核糖病毒的蛋白质组暗物质中，鉴定出了多种谱系特异性球状结构域，这些结构域对于一般的正核糖病毒或特定病毒家族来说都是新的，包括几个预测的核酸结合结构域和核酸酶。此外，我们还发现了一个例子，即在几个病毒家族中，细胞核苷单磷酸激酶被适应性用作RNA结合蛋白。尽管不断发现众多正核糖病毒，但似乎已经鉴定出了在大量病毒中保守的所有蛋白质结构域。病毒蛋白质组的其余部分似乎由结构不良的结构域主导，包括可能介导特定病毒 - 宿主相互作用的内在无序结构域。
先进的蛋白质结构预测方法，如AlphaFold2，极大地扩展了我们识别蛋白质结构域并推断其可能功能和进化关系的能力。这对于已知进化迅速的病毒编码的蛋白质尤为相关，因此通常无法通过蛋白质序列分析充分表征。我们对具有RNA基因组的病毒编码的未表征蛋白质和结构域（“暗物质”）进行了详尽的结构预测和比较分析。结果表明，RNA病毒蛋白质组的暗物质主要由无序和全α螺旋结构域组成，这些结构域难以轻易赋予特定功能，并且可能介导病毒蛋白之间以及病毒与宿主蛋白之间的各种相互作用。尽管我们在个别病毒家族中鉴定出了几个意外的结构域，但RNA病毒的绝大多数球状蛋白质和结构域已经为人所知。
