The Intricacy of the Viral-Human Protein Interaction Networks: Resources, Data, and Analyses

Abstract

Viral infections are one of the major causes of human diseases that cause yearly millions of deaths and seriously threaten global health, as we have experienced with the COVID-19 pandemic. Numerous approaches have been adopted to understand viral diseases and develop pharmacological treatments. Among them, the study of virus-host protein-protein interactions is a powerful strategy to comprehend the molecular mechanisms employed by the virus to infect the host cells and to interact with their components. Experimental protein-protein interactions described in the scientific literature have been systematically captured into several molecular interaction databases. These data are organized in structured formats and can be easily downloaded by users to perform further bioinformatic and network studies. Network analysis of available virus-host interactomes allow us to understand how the host interactome is perturbed upon viral infection and what are the key host proteins targeted by the virus and the main cellular pathways that are subverted. In this review, we give an overview of publicly available viral-human protein-protein interactions resources and the community standards, curation rules and adopted ontologies. A description of the main virus-human interactome available is provided, together with the main network analyses that have been performed. We finally discuss the main limitations and future challenges to assess the quality and reliability of protein-protein interaction datasets and resources.

Bioinformatics approaches for unveiling virus-host interactions

“…For example, human viruses occupy approximately 84% of over 10 million nucleotide sequences registered in the NCBI Virus Database ( https://www.ncbi.nlm.nih.gov/labs/virus/vssi/ ). Furthermore, previous studies on public databases of virus–host PPIs have shown that the available data are biased towards viruses that cause infectious diseases in humans, such as coronaviruses or influenza viruses [23] , [22] . It is unclear whether models trained on only limited virus species found in limited host species can be used for non-human hosts or novel viruses [51] , [52] .…”

“…However, the PPIs in the two datasets are in the order of thousands and negative interactions involving viral proteins are less than 100. Saha et al pointed out that researchers must systematically provide negative PPI data and expand the database [23] .…”

“…In addition, for various viral species, the interaction data identified in these experiments were collected in public databases, such as IntAct [18] , VirusMetha [19] , VirusMINT [20] , and HPIDB [21] . The following papers have discussed the viral-host PPIs in more detail [22] , [23] . Although the SARS-CoV-2 PPI network was determined very quickly because of the critical nature of the pandemic and the importance of the disease [16] , the scalability of these techniques is generally limited by the time and financial costs required for virus culture and antibody production.…”

Oncolytic Viruses in the Era of Omics, Computational Technologies, and Modeling: Thesis, Antithesis, and Synthesis

“…involved in fighting or preserving different types of cancers to envision strategies to manipulate the activity of specific immune subpopulations and skew the immune responses elicited by OVs against the tumors [118][119][120][121][122]. Virus-host protein-protein interactions are organized in a number of molecular interaction databases that provide information per virus or per host [123,124] that can be browsed, searched, visualized, and downloaded for subsequent bioinformatic and network analyses. These databases can be the starting point for the OV-tumor interactome, for which only a few reports exist [125].…”