N-terminomics – its past and recent advancements

蛋白质组 计算生物学 蛋白质组学 计算机科学 人类蛋白质组计划 生物 生物信息学 遗传学 基因
作者
Prashant Kaushal,Cheolju Lee
出处
期刊:Journal of Proteomics [Elsevier BV]
卷期号:233: 104089-104089 被引量:31
标识
DOI:10.1016/j.jprot.2020.104089
摘要

N-terminomics is a rapidly evolving branch of proteomics that encompasses the study of protein N-terminal sequence. A proteome-wide collection of such sequences has been widely used to understand the proteolytic cascades and in annotating the genome. Over the last two decades, various N-terminomic strategies have been developed for achieving high sensitivity, greater depth of coverage, and high-throughputness. We, in this review, cover how the field of N-terminomics has evolved to date, including discussion on various sample preparation and N-terminal peptide enrichment strategies. We also compare different N-terminomic methods and highlight their relative benefits and shortcomings in their implementation. In addition, an overview of the currently available bioinformatics tools and data analysis pipelines for the annotation of N-terminomic datasets is also included. It has been recognized that proteins undergo several post-translational modifications (PTM), and a number of perturbed biological pathways are directly associated with modifications at the terminal sites of a protein. In this regard, N-terminomics can be applied to generate a proteome-wide landscape of mature N-terminal sequences, annotate their source of generation, and recognize their significance in the biological pathways. Besides, a system-wide study can be used to study complicated proteolytic machinery and protease cleavage patterns for potential therapeutic targets. Moreover, due to unprecedented improvements in the analytical methods and mass spectrometry instrumentation in recent times, the N-terminomic methodologies now offers an unparalleled ability to study proteoforms and their implications in clinical conditions. Such approaches can further be applied for the detection of low abundant proteoforms, annotation of non-canonical protein coding sites, identification of candidate disease biomarkers, and, last but not least, the discovery of novel drug targets.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2780034682发布了新的文献求助10
刚刚
内向芷云应助宝宝鼠采纳,获得50
4秒前
脑洞疼应助柔弱紊采纳,获得10
5秒前
kxy0311完成签到 ,获得积分10
6秒前
7秒前
9秒前
灰苓完成签到,获得积分10
9秒前
白桃完成签到,获得积分10
9秒前
9秒前
11秒前
七盘西完成签到,获得积分10
11秒前
爆米花应助zwx0201采纳,获得10
12秒前
Akim应助霸气的晓夏采纳,获得10
12秒前
1433223发布了新的文献求助10
13秒前
爆米花应助张美采纳,获得10
13秒前
14秒前
15秒前
qinsu发布了新的文献求助10
16秒前
科研通AI6.2应助无情代芹采纳,获得10
17秒前
葛初蓝发布了新的文献求助10
20秒前
高兴的向秋完成签到,获得积分10
23秒前
24秒前
26秒前
26秒前
Nikki发布了新的文献求助10
27秒前
科研通AI6.3应助SYSUer采纳,获得10
27秒前
科研通AI6.1应助WN采纳,获得10
28秒前
28秒前
WZY16666完成签到,获得积分10
29秒前
29秒前
29秒前
29秒前
29秒前
29秒前
任天野应助科研通管家采纳,获得10
29秒前
英俊的铭应助科研通管家采纳,获得10
29秒前
小马甲应助科研通管家采纳,获得10
29秒前
29秒前
蓝天应助科研通管家采纳,获得10
30秒前
蓝天应助科研通管家采纳,获得10
30秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Modern Epidemiology, Fourth Edition 5000
Handbook of pharmaceutical excipients, Ninth edition 5000
Aerospace Standards Index - 2026 ASIN2026 2000
Digital Twins of Advanced Materials Processing 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Social Cognition: Understanding People and Events 1000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6031959
求助须知:如何正确求助?哪些是违规求助? 7716540
关于积分的说明 16198478
捐赠科研通 5178714
什么是DOI,文献DOI怎么找? 2771433
邀请新用户注册赠送积分活动 1754750
关于科研通互助平台的介绍 1639786