BFVD - 大型病毒蛋白质结构预测库

Martin Steinegger, Eli Levy Karin, Rachel Seongeun Kim
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摘要

AlphaFold 蛋白结构数据库(AFDB)是最大的带有分类标签的精确预测结构库。尽管 AFDB 为超过 2.14 亿个 UniProt 条目提供了预测,但它并不涵盖病毒序列,这严重限制了对病毒序列的研究。为了弥补这一差距,我们创建了大神奇病毒数据库(BFVD),这是一个通过将 ColabFold 应用于 UniRef30 聚类中的病毒序列代表而预测出的 351,242 种蛋白质结构的资源库。BFVD 拥有独特的蛋白质结构库,因为其超过 63% 的条目与现有结构库没有相似性或相似性很低。我们展示了与使用 Bakta 进行基于序列的注释相比,BFVD 如何大幅提高了噬菌体蛋白质的注释率。在这一点上,BFVD 与 AFDB 不相上下,但所保存的结构却少了近三个数量级。BFVD 是对蛋白质结构库的重要扩展,为推进病毒研究提供了新的机遇。BFVD 可在 https://bfvd.steineggerlab.workers.dev 免费获取。
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BFVD - a large repository of predicted viral protein structures
The AlphaFold Protein Structure Database (AFDB) is the largest repository of accurately predicted structures with taxonomic labels. Despite providing predictions for over 214 million UniProt entries, the AFDB does not cover viral sequences, severely limiting their study. To bridge this gap, we created the Big Fantastic Virus Database (BFVD), a repository of 351,242 protein structures predicted by applying ColabFold to the viral sequence representatives of the UniRef30 clusters. BFVD holds a unique repertoire of protein structures as over 63% of its entries show no or low structural similarity to existing repositories. We demonstrate how BFVD substantially enhances the fraction of annotated bacteriophage proteins compared to sequence-based annotation using Bakta. In that, BFVD is on par with the AFDB, while holding nearly three orders of magnitude fewer structures. BFVD is an important virus-specific expansion to protein structure repositories, offering new opportunities to advance viral research. BFVD is freely available at https://bfvd.steineggerlab.workers.dev
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