Dataset Information

Inferring Virus-Host relationship between HPV and its host Homo sapiens using protein interaction network.

ABSTRACT: Human papilloma virus (HPV) is a serious threat to human life globally with over 100 genotypes including cancer causing high risk HPVs. Study on protein interaction maps of pathogens with their host is a recent trend in 'omics' era and has been practiced by researchers to find novel drug targets. In current study, we construct an integrated protein interaction map of HPV with its host human in Cytoscape and analyze it further by using various bioinformatics tools. We found out 2988 interactions between 12 HPV and 2061 human proteins among which we identified MYLK, CDK7, CDK1, CDK2, JAK1 and 6 other human proteins associated with multiple viral oncoproteins. The functional enrichment analysis of these top-notch key genes is performed using KEGG pathway and Gene Ontology analysis, which reveals that the gene set is enriched in cell cycle a crucial cellular process, and the second most important pathway in which the gene set is involved is viral carcinogenesis. Among the viral proteins, E7 has the highest number of associations in the network followed by E6, E2 and E5. We found out a group of genes which is not targeted by the existing drugs available for HPV infections. It can be concluded that the molecules found in this study could be potential targets and could be used by scientists in their drug design studies.

SUBMITTER: Farooq QUA

PROVIDER: S-EPMC7251128 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Inferring Virus-Host relationship between HPV and its host Homo sapiens using protein interaction network.

Farooq Qurat Ul Ain QUA Shaukat Zeeshan Z Zhou Tong T Aiman Sara S Gong Weikang W Li Chunhua C

Scientific reports 20200526 1

Human papilloma virus (HPV) is a serious threat to human life globally with over 100 genotypes including cancer causing high risk HPVs. Study on protein interaction maps of pathogens with their host is a recent trend in 'omics' era and has been practiced by researchers to find novel drug targets. In current study, we construct an integrated protein interaction map of HPV with its host human in Cytoscape and analyze it further by using various bioinformatics tools. We found out 2988 interactions ...[more]

PMID: 32457456

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Project description:BackgroundHuman T-cell leukemia viruses (HTLV) tend to induce some fatal human diseases like Adult T-cell Leukemia (ATL) by targeting human T lymphocytes. To indentify the protein-protein interactions (PPI) between HTLV viruses and Homo sapiens is one of the significant approaches to reveal the underlying mechanism of HTLV infection and host defence. At present, as biological experiments are labor-intensive and expensive, the identified part of the HTLV-human PPI networks is rather small. Although recent years have witnessed much progress in computational modeling for reconstructing pathogen-host PPI networks, data scarcity and data unavailability are two major challenges to be effectively addressed. To our knowledge, no computational method for proteome-wide HTLV-human PPI networks reconstruction has been reported.ResultsIn this work we develop Multi-instance Adaboost method to conduct homolog knowledge transfer for computationally reconstructing proteome-wide HTLV-human PPI networks. In this method, the homolog knowledge in the form of gene ontology (GO) is treated as auxiliary homolog instance to address the problems of data scarcity and data unavailability, while the potential negative knowledge transfer is automatically attenuated by AdaBoost instance reweighting. The cross validation experiments show that the homolog knowledge transfer in the form of independent homolog instances can effectively enrich the feature information and substitute for the missing GO information. Moreover, the independent tests show that the method can validate 70.3% of the recently curated interactions, significantly exceeding the 2.1% recognition rate by the HT-Y2H experiment. We have used the method to reconstruct the proteome-wide HTLV-human PPI networks and further conducted gene ontology based clustering of the predicted networks for further biomedical research. The gene ontology based clustering analysis of the predictions provides much biological insight into the pathogenesis of HTLV retroviruses.ConclusionsThe Multi-instance AdaBoost method can effectively address the problems of data scarcity and data unavailability for the proteome-wide HTLV-human PPI interaction networks reconstruction. The gene ontology based clustering analysis of the predictions reveals some important signaling pathways and biological modules that HTLV retroviruses are likely to target.

Project description:BackgroundNovel antimalarials should be effective across all species of malaria parasites that infect humans, especially the two species that bear the most impact, Plasmodium falciparum and Plasmodium vivax. Protein kinases encoded by pathogens, as well as host kinases required for survival of intracellular pathogens, carry considerable potential as targets for antimalarial intervention (Adderley et al. Trends Parasitol 37:508-524, 2021; Wei et al. Cell Rep Med 2:100423, 2021). To date, no comprehensive P. vivax kinome assembly has been conducted; and the P. falciparum kinome, first assembled in 2004, requires an update. The present study, aimed to fill these gaps, utilises a recently published structurally-validated multiple sequence alignment (MSA) of the human kinome (Modi et al. Sci Rep 9:19790, 2019). This MSA is used as a scaffold to assist the alignment of all protein kinase sequences from P. falciparum and P. vivax, and (where possible) their assignment to specific kinase groups/families.ResultsWe were able to assign six P. falciparum previously classified as OPK or 'orphans' (i.e. with no clear phylogenetic relation to any of the established ePK groups) to one of the aforementioned ePK groups. Direct phylogenetic comparison established that despite an overall high level of similarity between the P. falciparum and P. vivax kinomes, which will help in selecting targets for intervention, there are differences that may underlie the biological specificities of these species. Furthermore, we highlight a number of Plasmodium kinases that have a surprisingly high level of similarity with their human counterparts and therefore not well suited as targets for drug discovery.ConclusionsDirect comparison of the kinomes of Homo sapiens, P. falciparum and P. vivax sheds additional light on the previously documented divergence of many P. falciparum and P. vivax kinases from those of their human host. We provide the first direct kinome comparison between the phylogenetically distinct species of P. falciparum and P. vivax, illustrating the key similarities and differences which must be considered in the context of kinase-directed antimalarial drug discovery, and discuss the divergences and similarities between the human and Plasmodium kinomes to inform future searches for selective antimalarial intervention.

Dataset Information

Inferring Virus-Host relationship between HPV and its host Homo sapiens using protein interaction network.

Publications

Inferring Virus-Host relationship between HPV and its host Homo sapiens using protein interaction network.

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