Mass spectrometry (MS) is an analytical technique for molecule identification that can be used for investigating protein-metal complex interactions. Once the MS data is collected, the mass spectra are usually interpreted manually to identify the adducts formed as a result of the interactions between proteins and metal-based species. However, with increasing resolution, dataset size, and species complexity, the time required to identify adducts and the error-prone nature of manual assignment have become limiting factors in MS analysis. AdductHunter is a open-source web-based analysis tool that automates the peak identification process using constraint integer optimization to find feasible combinations of protein and fragments, and dynamic time warping to calculate the dissimilarity between the theoretical isotope pattern of a species and its experimental isotope peak distribution. Empirical evaluation on a collection of 22 unique MS datasetsshows fast and accurate identification of protein-metal complex adducts in deconvoluted mass spectra.

中文翻译：

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AdductHunter：在质谱中识别蛋白质-金属复合加合物

质谱 (MS) 是一种分子鉴定分析技术，可用于研究蛋白质-金属复合物相互作用。一旦收集到 MS 数据，通常会手动解释质谱，以识别由于蛋白质和金属物质之间相互作用而形成的加合物。然而，随着分辨率、数据集大小和物种复杂性的增加，识别加合物所需的时间和手动分配的容易出错的性质已成为 MS 分析中的限制因素。 AdductHunter 是一款基于网络的开源分析工具，它使用约束整数优化来自动执行峰值识别过程，以找到蛋白质和片段的可行组合，并使用动态时间扭曲来计算物种的理论同位素模式与其实验同位素之间的差异峰值分布。对 22 个独特 MS 数据集的实证评估表明，可以在解卷积质谱中快速准确地识别蛋白质-金属复合加合物。