Protein–Protein Interaction Network for the Identification of New Targets Against Novel Coronavirus

Kumar, S.

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus in the family of Coronaviridae. The virus causes COVID-19, an infectious disease. SARS-CoV-2 provides novel clinical, immunological, and pathological features, compared to other established coronaviruses, such as the Middle East respiratory syndrome (MERS-CoV) and severe acute respiratory syndrome (SARS-CoV). There is no indication of successful antiviral treatment or vaccination at this stage. Several computational methods have been used to quickly understand the pathogenesis of viruses and to classify antiviral medications. Protein–protein interaction networks allow us to understand pathogenic pathways that contribute to the disease, infection, and development and to translate this knowledge to effective diagnostics and therapeutic strategies. The conventional approach to drug intervention and treatment interventions started to evolve with the complexity of dependence and drug pathways. Identifying drug–target interactions cannot only minimize drug production cycles and costs but can also strengthen awareness of how the future drugs and targets are identified. The purpose of a pharmaceutical network is to classify multi-target compounds focused at different protein groups involved in disrupted complexes. This promotes a network-centered viewpoint on drug action via the mapping of the goal network and offers a fresh insight into the role of polypharmacology in the drug operation. In this chapter, we shall address the available experiments and computations of protein–protein interaction methods to identify SARS-CoV-2 drugs.