Bioinformatics Based Approaches to Study Virus–Host Interactions During Chikungunya Virus Infection

Abstract

The limitations of high-throughput genomic methods used for studying virus-host interactions make it difficult to directly obtain insights on virus pathogenesis. In this chapter, the central steps of a protein structure similarity based computational approach used to predict the host interactors of Chikungunya virus are explained by highlighting the important aspects that need to be considered. Identification of such conserved set of putative interactions that allow the virus to take control of the host has the potential to deepen our understanding of the virus-specific remodeling processes of the host cell and illuminate new arenas of disease intervention.

Identification of potential therapeutic targets for COVID-19 through a structural-based similarity approach between SARS-CoV-2 and its human host proteins

“…Although finding intraspecies PPIs is common, predicting PPIs among different species is rare; therefore, this study may allow researchers to understand not only how a pathogenic protein interacts with its host on a molecular level but also how such interactions function in a more extensive cellular network (Lee et al, 2008). In this study, to elucidate the host-virus protein-protein interactions (HV-PPIs), a structure-based interaction approach was implemented to identify PPIs among human proteins (HPs) with known interactions that are structurally similar to viral proteins (Franzosa and Xia, 2011;Keskin et al, 2016;Rajasekharan et al, 2016). The primary limitation of using a structure-based interaction approach is the inadequate availability of three-dimensional structures and protein interaction of either pathogens or their host (Mariano and Wuchty, 2017).…”