FlatProt: 2D可视化简化蛋白质结构比较。

IF 3.3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Tobias Olenyi, Constantin Carl, Tobias Senoner, Ivan Koludarov, Burkhard Rost
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引用次数: 0

摘要

背景:了解和比较蛋白质的三维(3D)结构可以促进生物信息学、分子生物学和药物发现。虽然3D模型提供了详细的见解,但同时比较多个结构仍然具有挑战性,特别是在二维(2D)显示器上。现有的二维可视化工具缺乏标准化的方法来流水线检测大型蛋白质集,限制了它们在大规模预过滤中的应用。结果:我们介绍了FlatProt,这是一种工具,旨在通过实现单个蛋白质结构或大型蛋白质结构的标准化2D可视化来补充3D观察者。通过包含基于foldseek的家族旋转对齐或基于惯性的回退,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。它支持领域感知分解、家族级覆盖和二级结构的轻量级视觉抽象。正如人类蛋白质组的一个子集所展示的那样,FlatProt可以有效地处理蛋白质。结论:FlatProt提供清晰,一致,用户友好的可视化,支持快速,大规模的蛋白质结构比较检查。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的特征,检测异常值,并优先考虑进一步分析的结构。可用性:GitHub (https://github.com/t03i/FlatProt);Zenodo (https://doi.org/10.5281/zenodo.15697296)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FlatProt: 2D visualization eases protein structure comparison.

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 ).

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来源期刊
BMC Bioinformatics
BMC Bioinformatics 生物-生化研究方法
CiteScore
5.70
自引率
3.30%
发文量
506
审稿时长
4.3 months
期刊介绍: BMC Bioinformatics is an open access, peer-reviewed journal that considers articles on all aspects of the development, testing and novel application of computational and statistical methods for the modeling and analysis of all kinds of biological data, as well as other areas of computational biology. BMC Bioinformatics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.
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