Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Minneapolis, Minnesota 55455, United States.
ACS Synth Biol. 2024 Jun 21;13(6):1669-1678. doi: 10.1021/acssynbio.4c00188. Epub 2024 May 31.
HUH-tags have emerged as versatile fusion partners that mediate sequence specific protein-ssDNA bioconjugation through a simple and efficient reaction. Here we present HUHgle, a python-based interactive tool for the visualization, design, and optimization of substrates for HUH-tag mediated covalent labeling of proteins of interest with ssDNA substrates of interest. HUHgle streamlines design processes by integrating an intuitive plotting interface with a search function capable of predicting and displaying protein-ssDNA bioconjugate formation efficiency and specificity in proposed HUH-tag/ssDNA sequence combinations. Validation demonstrates that HUHgle accurately predicts product formation of HUH-tag mediated bioconjugation for single- and orthogonal-labeling reactions. In order to maximize the accessibility and utility of HUHgle, we have implemented it as a user-friendly Google Colab notebook which facilitates broad use of this tool, regardless of coding expertise.
HUH 标签已成为多功能融合伙伴，通过简单高效的反应介导序列特异性蛋白质-ssDNA 生物偶联。在这里，我们介绍了 HUHgle，这是一个基于 Python 的交互式工具，用于可视化、设计和优化 HUH 标签介导的感兴趣的蛋白质与感兴趣的 ssDNA 底物的共价标记的底物。HUHgle 通过将直观的绘图界面与搜索功能集成在一起，简化了设计过程，该搜索功能能够预测和显示拟议的 HUH 标签/ssDNA 序列组合中蛋白质-ssDNA 生物偶联形成效率和特异性。验证表明，HUHgle 准确预测了 HUH 标签介导的生物偶联产物的形成，包括单标记和正交标记反应。为了最大限度地提高 HUHgle 的可访问性和实用性，我们将其实现为一个用户友好的 Google Colab 笔记本，无论编码专业知识如何，都可以方便地广泛使用此工具。
