亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Protein Engineering Approaches in the Post-Genomic Era

计算生物学 生物信息学 生物
作者
Raushan Kumar Singh,Jung-Kul Lee,Chandrabose Selvaraj,Ranjitha Singh,Jinglin Li,Sang-Yong Kim,Vipin Chandra Kalia
出处
期刊:Current Protein & Peptide Science [Bentham Science]
卷期号:19 (1) 被引量:23
标识
DOI:10.2174/1389203718666161117114243
摘要

Proteins are one of the most multifaceted macromolecules in living systems. Proteins have evolved to function under physiological conditions and, therefore, are not usually tolerant of harsh experimental and environmental conditions. The growing use of proteins in industrial processes as a greener alternative to chemical catalysts often demands constant innovation to improve their performance. Protein engineering aims to design new proteins or modify the sequence of a protein to create proteins with new or desirable functions. With the emergence of structural and functional genomics, protein engineering has been invigorated in the post-genomic era. The three-dimensional structures of proteins with known functions facilitate protein engineering approaches to design variants with desired properties. There are three major approaches of protein engineering research, namely, directed evolution, rational design, and de novo design. Rational design is an effective method of protein engineering when the threedimensional structure and mechanism of the protein is well known. In contrast, directed evolution does not require extensive information and a three-dimensional structure of the protein of interest. Instead, it involves random mutagenesis and selection to screen enzymes with desired properties. De novo design uses computational protein design algorithms to tailor synthetic proteins by using the three-dimensional structures of natural proteins and their folding rules. The present review highlights and summarizes recent protein engineering approaches, and their challenges and limitations in the post-genomic era.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
hty完成签到 ,获得积分10
22秒前
zhangqin完成签到 ,获得积分10
1分钟前
小马甲应助科研通管家采纳,获得10
2分钟前
豆乳米麻薯完成签到 ,获得积分10
4分钟前
5分钟前
合不着完成签到 ,获得积分10
5分钟前
zhen发布了新的文献求助10
5分钟前
Shicheng完成签到,获得积分20
6分钟前
6分钟前
Shicheng发布了新的文献求助10
6分钟前
7分钟前
樊伟诚发布了新的文献求助10
7分钟前
7分钟前
8分钟前
8分钟前
刻苦的长颈鹿完成签到,获得积分10
8分钟前
日拱一卒的蕊完成签到,获得积分20
8分钟前
完美世界应助交钱上班采纳,获得10
8分钟前
寻道图强应助maher采纳,获得30
8分钟前
8分钟前
金灶沐完成签到 ,获得积分10
9分钟前
江望雪完成签到 ,获得积分10
9分钟前
10分钟前
RED发布了新的文献求助10
10分钟前
李爱国应助Jeriu采纳,获得10
10分钟前
10分钟前
Jeriu发布了新的文献求助10
10分钟前
桐桐应助希勤采纳,获得10
10分钟前
Jeriu完成签到,获得积分10
10分钟前
10分钟前
10分钟前
交钱上班发布了新的文献求助10
10分钟前
11分钟前
交钱上班完成签到,获得积分10
11分钟前
TWT发布了新的文献求助10
11分钟前
Fonseca完成签到 ,获得积分10
11分钟前
平日裤子完成签到 ,获得积分10
11分钟前
李健应助一剑白采纳,获得10
11分钟前
科研通AI2S应助Fonseca采纳,获得10
11分钟前
zhl完成签到,获得积分10
11分钟前
高分求助中
Sustainability in Tides Chemistry 2800
The Young builders of New china : the visit of the delegation of the WFDY to the Chinese People's Republic 1000
Rechtsphilosophie 1000
Bayesian Models of Cognition:Reverse Engineering the Mind 888
Le dégorgement réflexe des Acridiens 800
Defense against predation 800
XAFS for Everyone (2nd Edition) 600
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3133938
求助须知:如何正确求助?哪些是违规求助? 2784836
关于积分的说明 7768648
捐赠科研通 2440205
什么是DOI,文献DOI怎么找? 1297291
科研通“疑难数据库(出版商)”最低求助积分说明 624911
版权声明 600791