利用AlphaFold输出精确分割噬菌体内溶素结构域。

IF 5.4
Alexandre Boulay, Emma Cremelie, Clovis Galiez, Yves Briers, Elsa Rousseau, Roberto Vázquez
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引用次数: 0

摘要

摘要:SPAED是一种易于使用的精确分割蛋白质结构域的工具,它利用从AlphaFold获得的预测对齐误差(PAE)矩阵中包含的信息来更好地识别结构域连接子边界和检测末端无序区域。在376个噬菌体内溶素(降解细菌细胞壁的蛋白质)的数据集上,SPAED的平均交叉超结合得分为96%,区域边界距离得分为89%,而最先进的工具链锯分别为94%和70%。可用性和实现:用Python实现,SPAED可在web上访问(https://spaed.ca),并可从https://github.com/Rousseau-Team/spaed或https://pypi.org/project/spaed下载。用于测试SPAED的数据可在https://doi.org/10.5281/zenodo.15285860.Supplementary信息中找到:补充数据可在生物信息学在线上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SPAED: Harnessing AlphaFold Output for Accurate Segmentation of Phage Endolysin Domains.

Summary: SPAED is an accessible tool for the accurate segmentation of protein domains that leverages information contained in the predicted aligned error (PAE) matrix obtained from AlphaFold to better identify domain-linker boundaries and detect terminal disordered regions. On a dataset of 376 bacteriophage endolysins (proteins that degrade the bacterial cell wall), SPAED achieves a mean intersect-over-union score of 96% and a domain-boundary-distance score of 89% compared to 94% and 70%, respectively, for the state-of-the-art tool Chainsaw.

Availability and implementation: Implemented in Python, SPAED is accessible on the web (https://spaed.ca) and available for download from https://github.com/Rousseau-Team/spaed or https://pypi.org/project/spaed. The data used to test SPAED can be found at https://doi.org/10.5281/zenodo.15285860.

Supplementary information: Supplementary data are available at Bioinformatics online.

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