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NABh分类器服务器:一种用于识别蛋白质中螺旋核酸结合序列的工具。

NABhClassifier Server: A Tool for the Identification of Helical Nucleic Acid-Binding Sequences in Proteins.

作者信息

Margis Rogerio, Macedo Iara, Rodrigues Nureyev F, Dias-Oliveira Mateus, Lazzarotto Fernanda, Trindade de Souza Diego, Zanatta Geancarlo

机构信息

Postgraduate Programme in Cellular and Molecular Biology (PPGBCM), Center of Biotechnology, Federal University of Rio Grande do Sul, 90650-001 Porto Alegre, RS, Brazil.

Postgraduate Programme in Genetics and Molecular Biology (PPGBM), Federal University of Rio Grande do Sul, 91501-970 Porto Alegre, RS, Brazil.

出版信息

J Chem Inf Model. 2025 Mar 10;65(5):2361-2367. doi: 10.1021/acs.jcim.4c02244. Epub 2025 Feb 22.

Abstract

Engineered proteins capable of binding and transporting nucleic acids hold significant potential for advancing disease control in both the medical and agricultural fields. However, identifying small nucleic acid-binding domains remains challenging, as existing predictors primarily classify entire proteins as binders or nonbinders rather than targeting specific binding regions. Here, we introduce NABhClassifier, a highly efficient and precise web server designed to detect small helical sequences with nucleic acid-binding potential. Featuring an intuitive interface and a fully automated prediction pipeline, NABhClassifier integrates eight machine learning models for rapid analysis, delivering results in seconds per protein sequence. Predictions are summarized in the NABh index, a consensus score that combines outputs from all models for enhanced reliability. The server's accuracy has been validated on data sets of DNA-binding and single- and double-stranded RNA-binding proteins from various species. NABhClassifier provides a powerful tool for identifying small helices with nucleic acid-binding capacity, facilitating the discovery of novel biotechnological applications. The server, along with tutorials, is freely accessible at http://143.54.25.149.

摘要

能够结合并转运核酸的工程蛋白在医学和农业领域推进疾病控制方面具有巨大潜力。然而,识别小的核酸结合结构域仍然具有挑战性,因为现有的预测器主要将整个蛋白质分类为结合蛋白或非结合蛋白,而不是针对特定的结合区域。在此,我们介绍NABhClassifier,这是一个高效且精确的网络服务器,旨在检测具有核酸结合潜力的小螺旋序列。NABhClassifier具有直观的界面和全自动的预测流程,集成了八个机器学习模型以进行快速分析,每个蛋白质序列只需数秒即可得出结果。预测结果汇总在NABh指数中,这是一个共识分数,结合了所有模型的输出以提高可靠性。该服务器的准确性已在来自各种物种的DNA结合蛋白以及单链和双链RNA结合蛋白的数据集上得到验证。NABhClassifier为识别具有核酸结合能力的小螺旋提供了一个强大的工具,有助于发现新的生物技术应用。该服务器以及教程可通过http://143.54.25.149免费访问。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e049/11898072/69bbf1c848d5/ci4c02244_0001.jpg

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