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FlatProt:二维可视化便于蛋白质结构比较。

FlatProt: 2D visualization eases protein structure comparison.

作者信息

Olenyi Tobias, Carl Constantin, Senoner Tobias, Koludarov Ivan, Rost Burkhard

机构信息

Department of Informatics, Bioinformatics & Computational Biology, School of Computation, Information, and Technology (CIT), TUM (Technical University of Munich), 85748, Garching/Munich, Germany.

TUM School of Life Sciences Weihenstephan (WZW), Alte Akademie 8, Freising, Germany.

出版信息

BMC Bioinformatics. 2025 Aug 13;26(1):210. doi: 10.1186/s12859-025-06233-x.

DOI:10.1186/s12859-025-06233-x
PMID:40804367
Abstract

BACKGROUND

Understanding and comparing three-dimensional (3D) structures of proteins can advance bioinformatics, molecular biology, and drug discovery. While 3D models offer detailed insights, comparing multiple structures simultaneously remains challenging, especially on two-dimensional (2D) displays. Existing 2D visualization tools lack standardized approaches for pipelined inspection of large protein sets, limiting their utility in large-scale pre-filtering.

RESULTS

We introduce FlatProt, a tool designed to complement 3D viewers by enabling standardized 2D visualization of individual protein structures or large sets thereof. By including Foldseek-based family rotation alignment or an inertia-based fallback, FlatProt creates consistent and scalable visual representations for user-defined protein structures. It supports domain-aware decomposition, family-level overlays, and lightweight visual abstraction of secondary structures. FlatProt processes proteins efficiently, as showcased on a subset of the human-proteome.

CONCLUSION

FlatProt provides clear, consistent, user-friendly visualizations that support rapid, comparative inspection of protein structures at scale. By bridging the gap between interactive 3D tools and static visual summaries, it enables users to explore conserved features, detect outliers, and prioritize structures for further analysis.

AVAILABILITY

GitHub ( https://github.com/t03i/FlatProt ); Zenodo ( https://doi.org/10.5281/zenodo.15697296 ).

摘要

背景

理解和比较蛋白质的三维(3D)结构可以推动生物信息学、分子生物学和药物发现的发展。虽然3D模型能提供详细的见解,但同时比较多个结构仍然具有挑战性,尤其是在二维(2D)显示上。现有的2D可视化工具缺乏用于对大型蛋白质集进行流水线式检查的标准化方法,限制了它们在大规模预筛选中的效用。

结果

我们引入了FlatProt,这是一种旨在通过对单个蛋白质结构或其大型集合进行标准化2D可视化来补充3D查看器的工具。通过纳入基于Foldseek的家族旋转比对或基于惯性的备用方法,FlatProt为用户定义的蛋白质结构创建一致且可扩展的视觉表示。它支持基于结构域的分解、家族级叠加以及二级结构的轻量级视觉抽象。FlatProt能高效处理蛋白质,如在人类蛋白质组的一个子集上所展示的那样。

结论

FlatProt提供清晰、一致且用户友好的可视化,支持对蛋白质结构进行大规模的快速比较检查。通过弥合交互式3D工具和静态视觉摘要之间的差距,它使用户能够探索保守特征、检测异常值并对结构进行优先级排序以进行进一步分析。

可用性

GitHub(https://github.com/t03i/FlatProt);Zenodo(https://doi.org/10.5281/zenodo.15697296)。

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本文引用的文献

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Meta-MolNet: A Cross-Domain Benchmark for Few Examples Drug Discovery.元分子网络:用于少量样本药物发现的跨域基准
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AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences.2024 年的 AlphaFold 蛋白质结构数据库:为超过 2.14 亿个蛋白质序列提供结构覆盖。
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Domain loss enabled evolution of novel functions in the snake three-finger toxin gene superfamily.结构域丢失使蛇类三指毒素基因超家族获得新功能。
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Fast and accurate protein structure search with Foldseek.使用 Foldseek 进行快速准确的蛋白质结构搜索。
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UniProt: the Universal Protein Knowledgebase in 2023.UniProt:2023 年的通用蛋白质知识库。
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