Computational analysis of domains vulnerable To HPV-16 E6 Oncoprotein and corresponding hot spot residues.

2020 ◽  
Vol 27 ◽  
Author(s):  
Rabbiah Manzoor Malik ◽  
Sahar Fazal ◽  
Mohammad Amjad Kamal
Keyword(s):  
Cervical Cancer ◽  
Hot Spot ◽  
Network Models ◽  
Host Protein ◽  
Hpv 16 ◽  
Protein Protein Interaction ◽  
Linear Peptide ◽  
Peptide Motifs ◽  
E6 Oncoprotein ◽  
Human Proteins

Background: Human Papilloma Virus (HPV) is the primary cause of cancers in cervix, head and neck regions. Oncoprotein E6 of HPV-16, after infecting human body, alters host protein-protein interaction networks. E6 interacts with several proteins, causing the infection to progress into cervical cancer. The molecular basis for these interactions is the presence of short linear peptide motifs on E6 identical to those on human proteins. Methods: Motifs of LXXLL and E/DLLL/V-G after identification on E6, were analyzed for their dynamic fluctuations by use of elastic network models. Correlation analysis of amino acid residues of E6 was also performed in specific regions of motifs. Results: Arginine, Leucine, Glutamine, Threonine and Glutamic acid have been identified as hot spot residues of E6 which can subsequently provide a platform for drug designing and understanding of pathogenesis of cervical cancer. These amino acids play a significant role in stabilizing interactions with host proteins, ultimately causing infections and cancers. Conclusion: Our study validates the role of linear binding motifs of E6 of HPV in interacting with these proteins as an important event in the propagation of HPV in human cells and its transformation into cervical cancer. The study further predicts the domains of protein kinase and armadillo as part of the regions involved in the interaction of E6AP, Paxillin and TNF R1, with viral E6.

Insights into the Dynamic Fluctuations of the Protein HPV16 E1 and Identification of Motifs by Using Elastic Network Modeling

2021 ◽  
Vol 28 ◽  
Author(s):  
Rabbiah Malik ◽  
Sahar Fazal
Keyword(s):  
Drug Targets ◽  
Network Models ◽  
Hpv Infection ◽  
Elastic Network ◽  
Conserved Sequence ◽  
Linear Peptide ◽  
Peptide Motifs ◽  
E1 Protein ◽  
Human Proteins ◽  
Viral Helicase

Background: Cancers of cervix, head and neck regions have been found to be associated with Human Papilloma Virus (HPV) infection. E1 protein makes an important papillomavirus replication factor. Among the ORFs of papillomaviruses, the most conserved sequence is that of the E1 ORF. It is the viral helicase with being a member of class of ATPases associated with diverse cellular activities (AAA+) helicases. The interactions of E1 with human DNA and proteins occurs in the presence of short linear peptide motifs on E1 identical to those on human proteins. Methods: Different Motifs were identified on HPV16 E1 by using ELMs. Elastic network models were generated by using 3D structures of E1. Their dynamic fluctuations were analyzed on the basis of B factors, correlation analysis and deformation energies. Results: 3 motifs were identified on E1 which can interact with Cdk and Cyclin domains of human proteins. 11 motifs identified on E1 have their CDs of Pkinase on human proteins. LIG_MYND_2 has been identified as involved in stabilizing interaction of E1 with Hsp40 and Hsp70. These motifs and amino acids comprising these motifs play a major role in maintaining interactions with human proteins, ultimately causing infections leading to cancers. Conclusion: Our study identified various motifs on E1 which interact with specific counter domains found in human proteins, already reported having the interactions with E1. We also validated the involvement of these specific motifs containing regions of E1 by modeling elastic networks of E1. These motif involving interactions could be used as drug targets.

scholarly journals Computational Analysis of Dynamical Fluctuations of Oncoprotein E7 (HPV 16) for the Hot Spot Residue Identification Using Elastic Network Model

2020 ◽  
Vol 17 (11) ◽  
pp. 1393-1400
Author(s):  
Rabbiah Malik ◽  
Sahar Fazal ◽  
Mohammad Amjad Kamal
Keyword(s):  
Cervical Cancer ◽  
Computational Analysis ◽  
Hot Spot ◽  
Human Cells ◽  
Host Protein ◽  
Elastic Network Model ◽  
Hpv 16 ◽  
Binding Motifs ◽  
Rb Protein ◽  
Human Host

Aims: To find out Potential Drug targets against HPV E7. Background: Oncoprotein E7 of Human Papilloma Virus (HPV-16), after invading human body alter host protein-protein interaction networks caused by the fluctuations of amino acid residues present in E7. E7 interacts with Rb protein of human host with variable residual fluctuations, leading towards the progression of cervical cancer. Objective: Our study was focused our computational analysis of the binding and competing interactions of the E7 protein of HPV with Rb protein. Methods: Our study is based on analysis of dynamic fluctuations of E7 in host cell and correlation analysis of specific residue found in motif of LxCxE, that is the key region in stabilizing interaction between E7 and Rb. Results and Discussion: Cysteine, Leucine and Glutamic acid have been identified as hot spot residues of E7 which can provide platform for drug designing and understanding of pathogenesis of cervical cancer, in future. Our study shows validation of the vitality of linear binding motifs LxCxE of E7 of HPV in interacting with Rb as an important event in propagation of HPV in human cells and transformation of infection into cervical cancer. Conclusion: Our study shows validation of the vitality of linear binding motifs LxCxE of E7 of HPV in interacting with Rb as an important event in propagation of HPV in human cells and transformation of infection into cervical cancer. Other: E7 interacts with Rb protein of human host with variable residual fluctuations, leading towards the progression of cervical cancer.

scholarly journals Prediction of Human proteins having interactions with HPV16 proteins using virus and host sequence motifs.

2021 ◽  
Vol 2 (2) ◽  
pp. 107-126
Author(s):  
Rabbiah Manzoor Malik ◽  
Sahar Fazal ◽  
Syed Touqeer Abbas ◽  
Aamer Bhatti ◽  
Mukhtar Ullah ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Hpv Infection ◽  
Cervical Region ◽  
Sequence Motifs ◽  
Host Proteins ◽  
Human Host ◽  
Linear Peptide ◽  
Peptide Motifs ◽  
Human Proteins ◽  
E6 And E7

Background: Human Papillomavirus (HPV) infection has been found to be the major cause of cancer of cervical region, in females.  Genome of HPV codes for 6 functional proteins E1, E2, E4, E5, E6 and E7. These proteins play different roles in development of HPV infection and its progression towards cervical cancer. The interactions of HPV proteins with human DNA and proteins occurs in the presence of short linear peptide motifs on these proteins, have similar sequence to those found on proteins in human cells. Methods: After identification of human motifs in HPV proteins, by use of ELM resource, their counter domains were found from PROSITE. The proteins of human proteome containing these counter domains were predicted as the proteins having possibility of interactions with HPV proteins.    Results: we predicted 9468 human proteins for having interactions with HPV proteins. Our predicted proteins were enriched with the host proteins having possibility of being interacted by HPV proteins. 10% of our predicted proteins were already reported to be affected by one or more HPV proteins. The list of predicated proteins can be utilized to find out the connectivity between the virus HPV and human host. It can also be used to determine the pathways involved in pathogenesis of HPV leading towards the cervical cancer Conclusion: The list of predicated proteins can be utilized to find out the connectivity between the virus HPV and human host. It can also be used to determine the pathways involved in pathogenesis of HPV leading towards the cervical cancer.

scholarly journals Development of HPV 16/18 E6 oncoprotein paper-based nanokit for enhanced detection of HPV 16/18 E6 oncoprotein in cervical cancer screening

2020 ◽  
Author(s):  
Lucy Muthoni Mwai ◽  
Mutinda C. Kyama ◽  
Caroline W. Ngugi ◽  
Edwin Walong
Keyword(s):  
Cervical Cancer ◽  
Gold Nanoparticles ◽  
Cancer Screening ◽  
Diagnostic Accuracy ◽  
Predictive Value ◽  
Intraepithelial Neoplasia ◽  
Hpv 16 ◽  
Middle Income ◽  
Middle Income Countries ◽  
E6 Oncoprotein

AbstractCervical cancer caused mainly by high risk human papillomavirus (HPV) 16 and 18 strains is the second most prevalent cancer of women in Kenya. It is often diagnosed late when treatment is difficult due to very low percentage of women attending screening thus, mortalities remain high. The most available tests in low-and-middle-income countries (LMICs) have relatively low specificity, low sensitivity, require a laboratory setting and huge technical and financial support not readily available. HPV 16/18 E6 oncoprotein has been identified as a potential biomarker in a more specific early diagnosis of cervical cancer. This retrospective cross-sectional study developed a paper-based nanokit with enhanced detection of HPV 16/18 E6 oncoprotein for cervical cancer screening. The HRP labelled antibodies HPV 16 E6/18 E6-HRP (CP15) passively conjugated to citrate stabilized 20nm gold nanoparticles were evaluated for immune sensing mechanism using a recombinant viral HPV E6 protein. The diagnostic accuracy was evaluated using 50 tissue lysates from formalin fixed paraffin embedded cervical biopsy, including control (n=10), Mild Dysplasia (n=10), Cervical intraepithelial neoplasia 3 (CIN3) (n=10), Cervical intraepithelial neoplasia 4 (CIN4) (n=10) and invasive carcinoma (n=10). The molecular technique used was dot blot molecular assay. A positive result was generated by catalytic oxidation of peroxidase enzyme on 3,3’,5,5’-Tetramethylbenzidine (TMB) substrate. The gold nanoparticles were used to enhance the signal produced by peroxidase activity of horseradish peroxidase (HRP) enzyme giving a more sensitive assay as compared to use of non-conjugated antibody. This study provides a significantly high and reliable diagnostic accuracy for precancerous and cancerous lesions with a sensitivity of 90%, a specificity of 90%, a likelihood ratio for positive and negative tests as 9:1 and 1:9 respectively, a Positive Predictive Value of 97.3% and a Negative Predictive Value of 69.2%. This study avails a sensitive, rapid test using paper-based nanotechnology which can be utilised in community-based screening outreaches particularly in low- and middle-income countries.

scholarly journals Different subtypes of influenza A viruses target different human proteins and pathways leading to different pathogenic phenotypes

2019 ◽  
Author(s):  
Yujie Wang ◽  
Ting Song ◽  
Kaiwu Li ◽  
Yuan Jin ◽  
Junjie Yue ◽  
...  
Keyword(s):  
Influenza A ◽  
Influenza Viruses ◽  
Host Protein ◽  
Yeast Two Hybrid ◽  
Influenza A Viruses ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Tnf Α ◽  
Human Proteins ◽  
Two Hybrid

AbstractDifferent subtypes of Influenza A viruses cause different pathogenic phenotypes after infecting human bodies. Direct binary interactions between viral proteins and human proteins provide an important background for influenza viruses to cause complex pathologies of hosts. Here, we demonstrated the different impacts on the TNF-α-induced NF-κB activation of H1N1 and H5N1 virus proteins. By further examining the virus-host protein-protein interactions (PPI), we found that the same segment protein of the H1N1 and H5N1 viruses target on different host proteins. We then performed a yeast two-hybrid analysis of a highly pathogenic avian H5N1 influenza virus and human proteins. Influenza-host protein-protein interaction networks of three strains of influenza A viruses (including two other reported influenza-host PPI networks) were systematically compared and mapped on the network level and the pathway level. The results show subtype-specific characters of the influenza-host protein interactome, which may response for the specific pathogenic mechanisms of different subtypes of influenza viruses.ImportanceInfluenza A virus (IAV) can cause contagious respiratory illness, namely influenza (flu). The symptoms of infections from different subtypes of IAVs vary from mild to severe illness. The mechanism of these different pathogenic phenotypes remains poorly understood. Our results show that the same NA and NP segments from H1N1 and H5N1 virus cause different impacts on the TNF-α-induced NF-κB pathway. Furthermore, we generated a yeast two-hybrid protein-protein interaction (PPI) network between H5N1 and human proteins. By systematically comparing the influenza-host PPI networks of three strains of IAVs, we show that different subtypes of IAVs target different human proteins and pathways, which may have led to different pathogenic phenotypes.

scholarly journals Alignment of virus-host protein-protein interaction networks by integer linear programming: SARS-CoV-2

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0236304
Author(s):  
Mercè Llabrés ◽  
Gabriel Valiente
Keyword(s):  
Linear Programming ◽  
Protein Interaction ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Host Protein ◽  
Host Interactions ◽  
Protein Protein Interaction ◽  
Human Proteins ◽  
Consensus Alignment ◽  
Protein Protein Interaction Networks

Motivation Beside socio-economic issues, coronavirus pandemic COVID-19, the infectious disease caused by the newly discovered coronavirus SARS-CoV-2, has caused a deep impact in the scientific community, that has considerably increased its effort to discover the infection strategies of the new virus. Among the extensive and crucial research that has been carried out in the last months, the analysis of the virus-host relationship plays an important role in drug discovery. Virus-host protein-protein interactions are the active agents in virus replication, and the analysis of virus-host protein-protein interaction networks is fundamental to the study of the virus-host relationship. Results We have adapted and implemented a recent integer linear programming model for protein-protein interaction network alignment to virus-host networks, and obtained a consensus alignment of the SARS-CoV-1 and SARS-CoV-2 virus-host protein-protein interaction networks. Despite the lack of shared human proteins in these virus-host networks, and the low number of preserved virus-host interactions, the consensus alignment revealed aligned human proteins that share a function related to viral infection, as well as human proteins of high functional similarity that interact with SARS-CoV-1 and SARS-CoV-2 proteins, whose alignment would preserve these virus-host interactions.

scholarly journals Computational Analysis of Dynamical Fluctuations of Oncoprotein E7 (HPV) for the Hot Spot Residue Identification Using Elastic Network Model

2018 ◽  
Author(s):  
R. M. Malik ◽  
F. Nazir ◽  
S. Fazal ◽  
A. Bhatti ◽  
M. Ullah ◽  
...  
Keyword(s):  
Human Body ◽  
Protein Interactions ◽  
Computational Study ◽  
Hot Spot ◽  
Network Models ◽  
Biologically Active ◽  
Host Protein ◽  
Elastic Network Model ◽  
Elastic Network ◽  
Topological Features

AbstractVirus proteins after invading human body alter host protein-protein interaction networks, resulting in the creation of new interactions, along with destroying or modifying other interactions or proteins. Topological features of new or modified networks compromise the host system causing increased production of viral particles. The molecular basis for this alteration of proteins interactivity is short linear peptide motifs similar in both virus and humans. These motifs are identified by modular domains, which are the subunits of a protein, in the human body, resulting in stabilization or moderation of these protein interactions Protein molecules can be modeled by elastic network models showing the fluctuations of residues when they are biologically active. We focused our computational study on the binding and competing interactions of the E7 protein of HPV with Rb protein. Our study was based on analysis of dynamic fluctuations of E7 in host cell and correlation analysis of specific residue found in motif of LxCxE, that is the key region in stabilizing interaction between E7 and Rb. Hot spot residue of E7 were also identified which could provide platform for drug prediction in future. Nevertheless, our study validates the role of linear binding motifs LxCxE of E7 of HPV in interacting with Rb as an important event in propagation of HPV in human cells and transformation of infection into cervical cancer.

Protein–protein interactions of HPV–Chlamydia trachomatis–human and their potential in cervical cancer

2020 ◽  
Vol 15 (7) ◽  
pp. 509-520
Author(s):  
Abdul Arif Khan ◽  
Abdulwahab A Abuderman ◽  
Mohd Tashfeen Ashraf ◽  
Zakir Khan
Keyword(s):  
Cervical Cancer ◽  
Chlamydia Trachomatis ◽  
Protein Interactions ◽  
Cancer Development ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Pathogen Protein ◽  
Associated Proteins ◽  
Human Proteins ◽  
Cervical Cancer Development

Aim: HPV is an important cause of cervical cancer, but Chlamydia trachomatis (CT) is suspiciously involved in this disease ranging from direct to its involvement as a cofactor with HPV. We performed this study to understand the interaction of HPV and C. trachomatis with humans and its contribution to cervical cancer. Materials & methods: Host–pathogen and pathogen–pathogen protein–protein interaction maps of HPV/CT/human were prepared and compared to analyze interactions during single/coinfection of C. trachomatis and HPV. The interacting human proteins were detected by their involvement in cervical cancer. Results: C. trachomatis may interact with several cancer associated proteins while HPV and C. trachomatis largely interact with different human proteins, suggesting different pathogenesis. Conclusion: C. trachomatis coinfection with HPV may modulate cervical cancer development.

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