ABSTRACT

Introduction

Proteins are crucial for every cellular activity and unraveling their sequence and structure is a crucial step to fully understand their biology. Early methods of protein sequencing were mainly based on the use of enzymatic or chemical degradation of peptide chains. With the completion of the human genome project and with the expansion of the information available for each protein, various databases containing this sequence information were formed.

Areas covered

De novo protein sequencing, shotgun proteomics and other mass-spectrometric techniques, along with the various software are currently available for proteogenomic analysis. Emphasis is placed on the methods for de novo sequencing, together with potential and shortcomings using databases for interpretation of protein sequence data.

Expert opinion

As mass-spectrometry sequencing performance is improving with better software and hardware optimizations, combined with user-friendly interfaces, de-novo protein sequencing becomes imperative in shotgun proteomic studies. Issues regarding unknown or mutated peptide sequences, as well as, unexpected post-translational modifications (PTMs) and their identification through false discovery rate searches using the target/decoy strategy need to be addressed. Ideally, it should become integrated in standard proteomic workflows as an add-on to conventional database search engines, which then would be able to provide improved identification.

中文翻译：

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通过质谱法对蛋白质进行从头测序

摘要

介绍

蛋白质对每一种细胞活动都至关重要，解开它们的序列和结构是充分了解其生物学的关键步骤。蛋白质测序的早期方法主要基于使用肽链的酶促或化学降解。随着人类基因组计划的完成以及每个蛋白质可用信息的扩展，形成了包含该序列信息的各种数据库。

覆盖区域

从头蛋白质测序、鸟枪蛋白质组学和其他质谱技术以及各种软件目前可用于蛋白质基因组学分析。重点放在从头测序的方法上，以及使用数据库解释蛋白质序列数据的潜力和缺点。

专家意见

随着质谱测序性能随着更好的软件和硬件优化而提高，结合用户友好的界面，从头蛋白质测序在鸟枪蛋白质组学研究中变得势在必行。需要解决有关未知或突变的肽序列以及意外的翻译后修饰 (PTM) 及其通过使用目标/诱饵策略进行错误发现率搜索进行识别的问题。理想情况下，它应该作为传统数据库搜索引擎的附加组件集成到标准蛋白质组学工作流程中，然后能够提供改进的识别。