Mass spectrometry‐based proteomics is a popular and powerful method for precise and highly multiplexed protein identification. The most common method of analyzing untargeted proteomics data is called database searching, where the database is simply a collection of protein sequences from the target organism, derived from genome sequencing. Experimental peptide tandem mass spectra are compared to simplified models of theoretical spectra calculated from the translated genomic sequences. However, in several interesting application areas, such as forensics, archaeology, venomics, and others, a genome sequence may not be available, or the correct genome sequence to use is not known. In these cases, de novo peptide identification can play an important role. De novo methods infer peptide sequence directly from the tandem mass spectrum without reference to a sequence database, usually using graph‐based or machine learning algorithms. In this review, we provide a basic overview of de novo peptide identification methods and applications, briefly covering de novo algorithms and tools, and focusing in more depth on recent applications from venomics, metaproteomics, forensics, and characterization of antibody drugs.

中文翻译：

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盲目飞行，还是只是在雷达下飞行？质谱肽鉴定从头方法的功效被低估。

基于质谱的蛋白质组学是一种流行且强大的方法，用于精确和高度多重的蛋白质鉴定。分析非目标蛋白质组数据的最常见方法称为数据库搜索，其中数据库只是来自目标生物体的蛋白质序列的集合，这些序列源自基因组测序。将实验肽串联质谱与根据翻译的基因组序列计算的理论光谱的简化模型进行比较。然而，在一些有趣的应用领域，例如法医学、考古学、毒液学等，可能无法获得基因组序列，或者不知道要使用的正确基因组序列。在这些情况下，从头肽鉴定可以发挥重要作用。从头方法通常使用基于图形或机器学习算法，直接从串联质谱推断肽序列，而不参考序列数据库。在这篇综述中，我们提供了从头肽鉴定方法和应用的基本概述，简要介绍了从头算法和工具，并更深入地关注毒液组学、宏蛋白质组学、法医学和抗体药物表征的最新应用。