General strategies for using amino acid sequence data to guide biochemical investigation of protein function

功能(生物学) 计算生物学 序列(生物学) 蛋白质家族 领域(数学分析) 序列空间 蛋白质测序 蛋白质结构域 财产(哲学) 计算机科学 生物 肽序列 遗传学 数学 基因 认识论 巴拿赫空间 数学分析 哲学 纯数学
作者
Emily N. Kennedy,Clay A. Foster,Sarah A. Barr,Robert B. Bourret
出处
期刊:Biochemical Society Transactions [Portland Press]
卷期号:50 (6): 1847-1858 被引量:5
标识
DOI:10.1042/bst20220849
摘要

The rapid increase of ‘-omics' data warrants the reconsideration of experimental strategies to investigate general protein function. Studying individual members of a protein family is likely insufficient to provide a complete mechanistic understanding of family functions, especially for diverse families with thousands of known members. Strategies that exploit large amounts of available amino acid sequence data can inspire and guide biochemical experiments, generating broadly applicable insights into a given family. Here we review several methods that utilize abundant sequence data to focus experimental efforts and identify features truly representative of a protein family or domain. First, coevolutionary relationships between residues within primary sequences can be successfully exploited to identify structurally and/or functionally important positions for experimental investigation. Second, functionally important variable residue positions typically occupy a limited sequence space, a property useful for guiding biochemical characterization of the effects of the most physiologically and evolutionarily relevant amino acids. Third, amino acid sequence variation within domains shared between different protein families can be used to sort a particular domain into multiple subtypes, inspiring further experimental designs. Although generally applicable to any kind of protein domain because they depend solely on amino acid sequences, the second and third approaches are reviewed in detail because they appear to have been used infrequently and offer immediate opportunities for new advances. Finally, we speculate that future technologies capable of analyzing and manipulating conserved and variable aspects of the three-dimensional structures of a protein family could lead to broad insights not attainable by current methods.

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
大个应助旺仔采纳,获得10
刚刚
huyuxuan完成签到,获得积分10
1秒前
1秒前
脑洞疼应助cd采纳,获得10
1秒前
psybrain9527发布了新的文献求助10
1秒前
1秒前
颜凡桃完成签到,获得积分10
2秒前
好好学习发布了新的文献求助10
2秒前
你不懂发布了新的文献求助10
2秒前
3秒前
3秒前
penglin163com发布了新的文献求助10
5秒前
阔达尔芙完成签到,获得积分10
5秒前
MOON完成签到,获得积分10
5秒前
干净的南烟完成签到,获得积分10
6秒前
momoly发布了新的文献求助10
6秒前
composite66完成签到,获得积分10
7秒前
8秒前
英吉利25发布了新的文献求助10
8秒前
懵懵发布了新的文献求助10
8秒前
华灯初上完成签到 ,获得积分10
8秒前
心心发布了新的文献求助10
9秒前
9秒前
狮子头大王关注了科研通微信公众号
9秒前
丘比特应助Fury采纳,获得10
9秒前
pbj发布了新的文献求助10
10秒前
10秒前
共享精神应助戴佳伟彩笔采纳,获得10
11秒前
汉堡包应助Alien采纳,获得10
11秒前
11秒前
13秒前
13秒前
科研通AI6.2应助77采纳,获得10
13秒前
zhao完成签到 ,获得积分10
13秒前
13秒前
Owen应助酷炫迎夏采纳,获得10
14秒前
ltt应助yy采纳,获得10
14秒前
wyt123发布了新的文献求助10
14秒前
14秒前
松花酿酒发布了新的文献求助10
14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
The Organometallic Chemistry of the Transition Metals 800
Chemistry and Physics of Carbon Volume 18 800
The Organometallic Chemistry of the Transition Metals 800
The formation of Australian attitudes towards China, 1918-1941 640
Signals, Systems, and Signal Processing 610
全相对论原子结构与含时波包动力学的理论研究--清华大学 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6439929
求助须知:如何正确求助?哪些是违规求助? 8253806
关于积分的说明 17568054
捐赠科研通 5497981
什么是DOI,文献DOI怎么找? 2899564
邀请新用户注册赠送积分活动 1876329
关于科研通互助平台的介绍 1716706