Molecular Dynamics Simulation of Protein and Protein–Ligand Complexes

分子动力学 化学 蛋白质动力学 计算机科学 生物系统 灵活性(工程) 计算生物学 计算科学 计算化学 生物 数学 统计
作者
Rohit Shukla,Timir Tripathi
出处
期刊:Springer eBooks [Springer Nature]
卷期号:: 133-161 被引量:79
标识
DOI:10.1007/978-981-15-6815-2_7
摘要

Biomacromolecules, including proteins and their complexes, adopt multiple conformations that are linked to their biological functions. Though some of the structural heterogeneity can be studied by methods like X-ray crystallography, NMR, or cryo-electron microscopy, these methods fail to explain the detailed conformational transitions and dynamics. The dynamic structural states in proteins are covered in magnitude between 10−11 and 10−6 m and time-scales from 10−12 s to 10−5 s. For a comprehensive analysis of the biomolecular dynamics, molecular dynamics (MD) simulation has evolved as the most powerful technique. With the advent of high-end computational power, MD simulations can be performed between μs to the ms time-scale that can accurately describe the dynamics of any system. Various force fields like GROMOS, AMBER, and CHARMM have been developed for MD simulations. Tools like GROMACS, AMBER, CHARMM-GUI, and NAMD are the most widely used methods for MD simulation that can provide precise information on the motions and flexibility of a protein, which contributes to the interaction dynamics of protein–ligand complexes. MD simulation has several other practical applications in diverse research areas, including molecular docking and drug design, refining protein structure predictions, and studying the unfolding pathway of a protein. Combining MD simulation with wet-lab experiments has become an indispensable complement in the investigation of several important and intricate biological processes. Various tools like principal component analysis, cross-correlation analysis, and residues interaction network analysis are additional useful approaches for analyzing MD data. In this chapter, we will discuss MD simulation for a layman understanding and explain how it can be used for protein–ligand characterization as well as for use in diverse biomolecular applications.
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
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
强健的妙菱完成签到,获得积分10
1秒前
1秒前
小蘑菇应助温柔若采纳,获得10
1秒前
李爱国应助通~采纳,获得10
1秒前
经竺应助小马哥采纳,获得10
1秒前
3秒前
单纯的芷蝶完成签到,获得积分10
3秒前
研友完成签到,获得积分10
3秒前
勤奋若风完成签到,获得积分10
3秒前
英姑应助每天都想下班采纳,获得10
4秒前
shooin完成签到,获得积分10
4秒前
佳佳发布了新的文献求助10
4秒前
MADKAI发布了新的文献求助10
4秒前
lin完成签到,获得积分20
5秒前
思源应助科研民工采纳,获得10
5秒前
忧郁凌波完成签到,获得积分10
5秒前
姜姜姜完成签到 ,获得积分10
6秒前
凶狠的绿兰完成签到,获得积分10
7秒前
多多少少忖测的情完成签到,获得积分10
7秒前
科研通AI5应助兴奋的宛白采纳,获得10
8秒前
9秒前
zhanlonglsj发布了新的文献求助10
9秒前
9秒前
芍药完成签到,获得积分10
9秒前
Yogita完成签到,获得积分10
10秒前
DoctorYan完成签到,获得积分10
10秒前
Adler完成签到,获得积分10
10秒前
11秒前
坐宝马吃地瓜完成签到 ,获得积分10
11秒前
SciGPT应助Strike采纳,获得10
11秒前
自强不息完成签到,获得积分10
11秒前
12秒前
czq发布了新的文献求助30
12秒前
望春风完成签到,获得积分10
12秒前
12秒前
huangJP完成签到,获得积分10
13秒前
情怀应助Tira采纳,获得10
13秒前
王阳洋完成签到,获得积分10
13秒前
13秒前
14秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527521
求助须知:如何正确求助?哪些是违规求助? 3107606
关于积分的说明 9286171
捐赠科研通 2805329
什么是DOI,文献DOI怎么找? 1539901
邀请新用户注册赠送积分活动 716827
科研通“疑难数据库(出版商)”最低求助积分说明 709740