Abstract：
Concerted interactions between all the cell components form the basis of biological processes. Protein-protein interactions (PPIs) constitute a tremendous part of this interaction network. Deeper insight into PPIs can help us better understand numerous diseases and lead to the development of new diagnostic and therapeutic strategies. PPI interfaces, until recently, were considered undruggable. However, it is now believed that the interfaces contain \"hot spots,\" which could be targeted by small molecules. Such a strategy would require high-quality structural data of PPIs, which are difficult to obtain experimentally. Therefore, in silico modeling can complement or be an alternative to in vitro approaches. There are several computational methods for analyzing the structural data of the binding partners and modeling of the protein-protein dimer/oligomer structure. The major problem with in silico structure prediction of protein assemblies is obtaining sufficient sampling of protein dynamics. One of the methods that can take protein flexibility and the effects of the environment into account is Molecular Dynamics (MD). While sampling of the whole protein-protein association process with plain MD would be computationally expensive, there are several strategies to harness the method to PPI studies while maintaining reasonable use of resources. This chapter reviews known applications of MD in the PPI investigation workflows.
摘要：
所有细胞成分之间的协同相互作用形成了生物过程的基础。蛋白质-蛋白质相互作用（PPIs）构成了这种相互作用网络的重要组成部分。对PPI的深入了解可以帮助我们更好地了解许多疾病，并导致新的诊断和治疗策略的发展。PPI接口，直到最近,被认为是无药可救的。然而,现在人们认为接口包含“热点”，“可以被小分子靶向。这样的策略需要高质量的PPI结构数据，很难通过实验获得。因此,计算机建模可以补充或替代体外方法。有几种计算方法用于分析结合配偶体的结构数据和蛋白质-蛋白质二聚体/寡聚体结构的建模。蛋白质装配的计算机结构预测的主要问题是获得足够的蛋白质动力学采样。可以考虑蛋白质灵活性和环境影响的方法之一是分子动力学（MD）。虽然用普通MD对整个蛋白质-蛋白质关联过程进行采样在计算上是昂贵的，有几种策略可以利用PPI研究的方法，同时保持资源的合理利用。本章回顾了MD在PPI调查工作流程中的已知应用。
