Analyzing the Protein-Protein Interaction Network and the Topological Properties of Coronary Artery Disease and Allied Diseases: A Computational Bioinformatics Approach.

Abstract

Background and Objectives: Some diseases are related to each other by their metabolic structures. A few examinations showed that Coronary artery disease (CAD), Diabetes mellitus (DM), Parkinson’s Disease (PKD) and Stroke (ST) are related. Some are shown up for affected family backgrounds in their early or grown-up age. Materials and Methods: Python a programming language used for data mining, pre-processing and sorting for finding common genes from gathered data from National Centre of Biotechnology Information (NCBI). However, there is a lack of genetic study to find out the core genes for which they may occur and make Protein-Protein Interaction (PPIs) and Protein Disease Interaction (PDI) by using bioinformatics technology. We use identified hub genes for making co-expression and physical interaction. Results: Interactions for selected top 10 genes are exhibited following different bioinformatics tools. The gene-miRNA interaction generates interactions with a total of 413 links between 10 genes. Where, the TF-gene Interaction creates relationships between 101 nodes and 106 edges. There are 5 seed nodes. Besides, PDI represents a subnetwork which creates 3 sub network relationships between 58 nodes and 55 edges. There are 1 seed node in each sub network. In addition, PCI creates relationships between 1842 nodes and 2685 edges. There are 8 seed nodes. Furthermore, GDA creates relationships between 452 nodes and 537 edges. There are 6 seed nodes. Conclusion: This study will be helpful for further studies of different bioinformatics tools for designing gene network models and drugs design. These drugs can be considered for further verification by chemical experiments.