Institute of Microbiology, v.v.i., The Czech Academy of Sciences, Videnska 1083, Prague 14220, Czech Republic.
Department of Biochemistry, Faculty of Science, Charles University, Albertov 6, 12800 Prague 2, Czech Republic.
J Proteome Res. 2021 Apr 2;20(4):2021-2027. doi: 10.1021/acs.jproteome.0c00858. Epub 2021 Mar 3.
Chemical cross-linking mass spectrometry has become a popular tool in structural biology. Although several algorithms exist that efficiently analyze data-dependent mass spectrometric data, the algorithm to identify and quantify intermolecular cross-links located at the interaction interface of homodimer molecules was missing. The algorithm in LinX utilizes high mass accuracy for ion identification. In contrast with standard data-dependent analysis, LinX enables the elucidation of cross-linked peptides originating from the interaction interface of homodimers labeled by N/N, including their ratio or cross-links from protein-nucleic acid complexes. The software is written in Java language, and its source code and a detailed user's guide are freely available at https://github.com/KukackaZ/LinX or https://ms-utils.org/LinX. Data are accessible via the ProteomeXchange server with the data set identifier PXD023522.
化学交联质谱已成为结构生物学中一种流行的工具。尽管存在几种能够高效分析数据依赖性质谱数据的算法,但用于识别和定量位于同源二聚体分子相互作用界面的分子间交联的算法却一直缺失。LinX 算法利用高精度的离子鉴定。与标准的数据依赖性分析不同,LinX 能够阐明由 N/N 标记的同源二聚体的相互作用界面产生的交联肽,包括它们的比值或来自蛋白质-核酸复合物的交联。该软件是用 Java 语言编写的,其源代码和详细的用户指南可在 https://github.com/KukackaZ/LinX 或 https://ms-utils.org/LinX 上免费获得。通过 ProteomeXchange 服务器可获取数据集标识符 PXD023522 来访问数据。