Title

Elastic Network Modeling of Human Papilloma Virus Proteins

Abstract

Cancers are the main reason for elevating death rate among human population all over the world as well as in Pakistan. Low cancer survival rate and lack of awareness regarding cervical cancer risk is raising significant cancer burden in females of Pakistan therefore; our country is in terrible need of cancer management and prevention measures. It has been reported in literature that more than 30% of cancer deaths could be prevented by modifying or avoiding key risk factors responsible for cancer development. Early detection, accurate diagnosis, and effective treatment, may help increase cancer survival rates and reduce suffering. There are a group of viruses including Hepatitis Virus, Papilloma Virus, Epstein Barr Virus, which in their advance stage of infection cause development of cancers. It has been found that a major cause of cervical cancer is Papilloma viral infection. Human Papillomavirus (HPV) have a specific mechanism by which it causes pathogenesis in humans, which ultimately leads to cervical cancer. The major mechanism involved in this pathogenesis is interaction of specific viral proteins with human proteins resulting in carcinogenesis. In recent years characterization of proteins has been enhanced by the development of elastic network modelling, among which Anisotropic Network Modelling helps in explaining functioning of proteins while Gaussian Network Modelling covers the structural aspect of proteins. In present project the techniques of Anisotropic network modelling and Gaussian network modelling have been applied to have a deep analysis of interactions of HPV viral and human proteins involved in carcinogenesis of cervical cancer. In first step, amino acids sequences of HPV proteins E1, E2, E4, E5, E6 and E7 were mapped on sequences of Eukaryotic Linear Motifs (ELM) in human beings, by using tool ELM. There were retrieved seventy-seven ELMs which had sequences identical to those of human ELMs. On that basis it could be considered that these ELMs are present on HPV proteins. As ELMs interact with their counter domains in other proteins to establish a protein-protein interaction. we predicted protein domains which interact with those conserved linear motifs. Human proteins were predicted which may be targeted by HPV proteins by establishing interactions through a motif conserved in HPV and the equivalent interacting protein domain. Our predicted proteins were enriched with host proteins known to interact with HPV proteins E1, E2, E4, E5, E6 and E7. We found the Cancer Pathways to be statistically enriched for our predicted proteins. We also analyzed our predictions for enrichment with Gene Ontology molecular function of level 5 categories with both predicted and confirmed HPV targeted proteins. The enriched functions included molecular activities associated with events of phosphorylation, protein kinases and adenyl ribonucleotide binding. We modeled 3D structures of HPV proteins by using FASTA sequences of proteins. These 3D structures were used as input for modeling elastic networks of HPV proteins. Elastic network gave us insights into the HPV proteins, for their flexible regions and their molecular dynamics. On the basis of our findings of the flexible regions shown by elastic network models of HPV proteins, sequence and site of presence of motifs on HPV proteins, predicted proteins, and previous literature about the interactions of HPV with human proteins we predicted new motifs on HPV proteins and domains in human proteins involved in interactions of HPV with human proteins. We also predicted hot spot residues of HPV proteins, for already reported interactions of HPV proteins E2, E6, and E7 with DNA, hDlg and retinoblastoma, respectively. Our study authenticates the part of linearly binding motifs commonly shared between virus and human proteins as a significant part of the crosstalk among virus and host. We also validated the previously reported interactions of HPV proteins with human proteins, by the elastic network models on the basis of flexibility, dynamic fluctuations, correlations analysis and deformation energies, of those specific regions involved in those interactions

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