Abstract
BackgroundInfectious diseases are a cruel assassin with millions of victims around the world each year. Understanding infectious mechanism of viruses is indispensable for their inhibition. One of the best ways of unveiling this mechanism is to investigate the host-pathogen protein-protein interaction network. In this paper we try to disclose many properties of this network. We focus on human as host and integrate experimentally 32,859 interaction between human proteins and virus proteins from several databases. We investigate different properties of human proteins targeted by virus proteins and find that most of them have a considerable high centrality scores in human intra protein-protein interaction network. Investigating human proteins network properties which are targeted by different virus proteins can help us to design multipurpose drugs.ResultsAs host-pathogen protein-protein interaction network is a bipartite network and centrality measures for this type of networks are scarce, we proposed seven new centrality measures for analyzing bipartite networks. Applying them to different virus strains reveals unrandomness of attack strategies of virus proteins which could help us in drug design hence elevating the quality of life. They could also be used in detecting host essential proteins. Essential proteins are those whose functions are critical for survival of its host. One of the proposed centralities named diversity of predators, outperforms the other existing centralities in terms of detecting essential proteins and could be used as an optimal essential proteins’ marker.ConclusionsDifferent centralities were applied to analyze human protein-protein interaction network and to detect characteristics of human proteins targeted by virus proteins. Moreover, seven new centralities were proposed to analyze host-pathogen protein-protein interaction network and to detect pathogens’ favorite host protein victims. Comparing different centralities in detecting essential proteins reveals that diversity of predator (one of the proposed centralities) is the best essential protein marker.
Highlights
Infectious diseases are a cruel assassin with millions of victims around the world each year
We uncovered the degree of separation of HPPI network (HPPIN)
In this article, we studied the properties of a bipartite network generated from interactions between human proteins versus virus proteins
Summary
Infectious diseases are a cruel assassin with millions of victims around the world each year. One of the best ways of unveiling this mechanism is to investigate the host-pathogen protein-protein interaction network. We investigate different properties of human proteins targeted by virus proteins and find that most of them have a considerable high centrality scores in human intra protein-protein interaction network. Investigating human proteins network properties which are targeted by different virus proteins can help us to design multipurpose drugs. Biological processes, cellular compartment, common pathways and the other properties of host proteins targeted by pathogens can help us in infectious disease inhibition. Centrality measures can be used to find most important HPs in HPPI network (HPPIN) to identify new drug targets [9,10,11,12,13,14,15]. HPPIN has been analyzed by different centralities such as Degree Centrality [16], Closeness [17], Lobby Index [18], Betweenness [19], Clustering Coefficient [20], Leader Rank [21], Topological Coefficient [22], Module Centrality [23], Eigenvector Centrality [24], Neighborhood Connectivity [25], Normalized Alpha Centrality [26], Average Shortest Path Length [27], Subgraph Centrality [28], Radiality [29], Range limited Centrality [30] and Eccentricity [31]
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