Sabetian Soudabeh, Shamsir Mohd Shahir
Department of Biological and Health Sciences, Faculty of Bioscience and Medical Engineering, Universiti Teknologi Malaysia, 81310 Johor, Malaysia.
Infertility Research Center, Shiraz University, Shiraz 71454, Iran, Shiraz University of Medical Sciences, Shiraz, Iran.
Bioinformation. 2019 Jul 31;15(7):513-522. doi: 10.6026/97320630015513. eCollection 2019.
Proteins can interact in various ways, ranging from direct physical relationships to indirect interactions in a formation of protein-protein interaction network. Diagnosis of the protein connections is critical to identify various cellular pathways. Today constructing and analyzing the protein interaction network is being developed as a powerful approach to create network pharmacology toward detecting unknown genes and proteins associated with diseases. Discovery drug targets regarding therapeutic decisions are exciting outcomes of studying disease networks. Protein connections may be identified by experimental and recent new computational approaches. Due to difficulties in analyzing in-vivo proteins interactions, many researchers have encouraged improving computational methods to design protein interaction network. In this review, the experimental and computational approaches and also advantages and disadvantages of these methods regarding the identification of new interactions in a molecular mechanism have been reviewed. Systematic analysis of complex biological systems including network pharmacology and disease network has also been discussed in this review.
蛋白质可以通过多种方式相互作用，从直接的物理关系到蛋白质-蛋白质相互作用网络形成中的间接相互作用。蛋白质连接的诊断对于识别各种细胞途径至关重要。如今，构建和分析蛋白质相互作用网络正作为一种强大的方法得到发展，以创建网络药理学来检测与疾病相关的未知基因和蛋白质。发现与治疗决策相关的药物靶点是研究疾病网络令人兴奋的成果。蛋白质连接可以通过实验方法和最新的新计算方法来识别。由于分析体内蛋白质相互作用存在困难，许多研究人员鼓励改进计算方法以设计蛋白质相互作用网络。在这篇综述中，对实验和计算方法以及这些方法在分子机制中识别新相互作用方面的优缺点进行了综述。本综述还讨论了对包括网络药理学和疾病网络在内的复杂生物系统的系统分析。
