Current Tools and Methods in Molecular Dynamics (MD) Simulations for Drug Design

分子动力学 药物设计 对接(动物) 稳健性(进化) 生物系统 药物发现 伞式取样 结构生物学 计算机科学 计算化学 化学 生物 生物化学 医学 基因 护理部
作者
Maricarmen Hernández‐Rodríguez,Martha Cecilia Rosales‐Hernández,Jessica Elena Mendieta‐Wejebe,Marlet Martínez‐Archundia,José Correa‐Basurto
出处
期刊:Current Medicinal Chemistry [Bentham Science Publishers]
卷期号:23 (34): 3909-3924 被引量:83
标识
DOI:10.2174/0929867323666160530144742
摘要

Molecular Dynamics (MD) simulations is a computational method that employs Newton's laws to evaluate the motions of water, ions, small molecules, and macromolecules or more complex systems, for example, whole viruses, to reproduce the behavior of the biological environment, including water molecules and lipid membranes. Specifically, structural motions, such as those that are dependent of the temperature and solute/ solvent are very important to study the recognition pattern of ligandprotein or protein-protein complexes, in that sense, MD simulations are very useful because these motions can be modeled using this methodology. Furthermore, MD simulations for drug design provide insights into the structural cavities required to design novel structures with higher affinity to the target. Also, the employment of MD simulations to drug design can help to refine the three-dimensional (3D) structure of targets in order to obtain a better sampling of the binding poses and more reliable affinity values with better structural advantages, because they incorporate some biological conditions that include structural motions compared to traditional docking procedures. This work analyzes the concepts and applicability of MD simulations for drug design because molecular structural motions are considered, and these help to identify hot spots, decipher structural details in the reported protein sites, as well as to eliminate sites that could be structural artifacts which could be originated from the structural characterization conditions from MD. Moreover, better free energy values for protein ligand recognition can also be obtained, and these can be validated under experimental procedures due to the robustness of the MD simulation methods.
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