A Graph-Based Approach for Finding the Dengue Infection Pathways in Humans Using Protein–Protein Interactions

Abstract

Abstract Dengue virus (DENV) is one of the deadly arboviruses, which is primarily transmitted by Aedes aegypti, and causes dengue infection to the humans. According to WHO, every year around 390 million humans are affected by DENV, of which around 50 million deaths are reported. Knowledge of the various diseases caused by the DENV would greatly encourage to understand the infection mechanism and help to design new antiviral drug discovery. We propose a quasi-clique and quasi-biclique algorithm to classify infection gateway proteins of the human body and possible pathways of DENV leading to various diseases. For this, we have examined three networks, dengue-human protein–protein interaction network, human protein interaction network, and human proteins-disease association network. The prediction result states that DENV may lead to various diseases in the human body, including cancer, asthma, ulcerative colitis, multiple sclerosis, premature birth, and so on. Some of the results have recently been validated experimentally. This study may endow with potential targets for more effective anti-dengue remedial contribution.