Fungtion:预测和可视化真菌效应蛋白的服务器

IF 4.7 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
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引用次数: 0

摘要

真菌病原体通过分泌效应蛋白操纵植物宿主的防御系统,对植物健康构成重大威胁。然而,识别效应蛋白仍然具有挑战性,部分原因是它们缺乏共同的序列基序。在这里,我们介绍 Fungtion(真菌效应物预测),这是一个利用混合框架准确预测和可视化真菌效应物的工具包。通过将从预训练蛋白质语言模型中学到的全局模式与已知效应物的细化信息相结合,Fungtion 实现了最先进的预测性能。此外,我们开发的交互式可视化技术还能让研究人员探索预测的效应物与已知效应物之间的序列关系和高层关系,从而促进效应物功能的发现、注释以及有关植物病原体相互作用的假设的提出。我们预计 Fungtion 将成为生物学家深入了解真菌效应物功能的宝贵资源,也将成为计算生物学家开发未来真菌效应物预测方法的宝贵资源:https://step3.erc.monash.edu/Fungtion/。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Fungtion: A Server for Predicting and Visualizing Fungal Effector Proteins

Fungtion: A Server for Predicting and Visualizing Fungal Effector Proteins

Fungal pathogens pose significant threats to plant health by secreting effectors that manipulate plant-host defences. However, identifying effector proteins remains challenging, in part because they lack common sequence motifs. Here, we introduce Fungtion (Fungal effector prediction), a toolkit leveraging a hybrid framework to accurately predict and visualize fungal effectors. By combining global patterns learned from pretrained protein language models with refined information from known effectors, Fungtion achieves state-of-the-art prediction performance. Additionally, the interactive visualizations we have developed enable researchers to explore both sequence- and high-level relationships between the predicted and known effectors, facilitating effector function discovery, annotation, and hypothesis formulation regarding plant-pathogen interactions. We anticipate Fungtion to be a valuable resource for biologists seeking deeper insights into fungal effector functions and for computational biologists aiming to develop future methodologies for fungal effector prediction: https://step3.erc.monash.edu/Fungtion/.

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来源期刊
Journal of Molecular Biology
Journal of Molecular Biology 生物-生化与分子生物学
CiteScore
11.30
自引率
1.80%
发文量
412
审稿时长
28 days
期刊介绍: Journal of Molecular Biology (JMB) provides high quality, comprehensive and broad coverage in all areas of molecular biology. The journal publishes original scientific research papers that provide mechanistic and functional insights and report a significant advance to the field. The journal encourages the submission of multidisciplinary studies that use complementary experimental and computational approaches to address challenging biological questions. Research areas include but are not limited to: Biomolecular interactions, signaling networks, systems biology; Cell cycle, cell growth, cell differentiation; Cell death, autophagy; Cell signaling and regulation; Chemical biology; Computational biology, in combination with experimental studies; DNA replication, repair, and recombination; Development, regenerative biology, mechanistic and functional studies of stem cells; Epigenetics, chromatin structure and function; Gene expression; Membrane processes, cell surface proteins and cell-cell interactions; Methodological advances, both experimental and theoretical, including databases; Microbiology, virology, and interactions with the host or environment; Microbiota mechanistic and functional studies; Nuclear organization; Post-translational modifications, proteomics; Processing and function of biologically important macromolecules and complexes; Molecular basis of disease; RNA processing, structure and functions of non-coding RNAs, transcription; Sorting, spatiotemporal organization, trafficking; Structural biology; Synthetic biology; Translation, protein folding, chaperones, protein degradation and quality control.
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