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.
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