Comprehensive Network and Structural Analysis of Bovine Papillomavirus, Squamous Cell Carcinoma Markers, and Elucidation of Efficacy Mechanisms of Phytochemicals from Thuja Occidentalis
Rahman, S.; Kumar, A. H.
Show abstract
Papillomaviruses infect cutaneous tissue in various species including bovines and from benign warts to malignant squamous cell carcinoma causing severe economic losses to the farmers. The mechanisms by which bovine papillomaviruses interact with host tissue are unclear. Hence in this study using classical network analysis tools, we evaluated interactions of Bovine papilloma (BPV) variants, with markers and receptors implicated in squamous cell carcinoma. Additionally, the thuja phytoconstituents were also evaluated for its potential to target the BPV and squamous cell carcinoma network interactions to understand the mechanism of its clinical benefits. Various protein composition of 14 different virus variants of BPV were assessed against 24 markers of squamous cell carcinoma. Among these interactions EGFR consistently exhibited high-affinity interactions with the E1 protein in all isoforms of BPV. Type 4 BPV displayed the maximum number of binding sites (14) with a binding pocket score ranging from 15.47 to 141.34 and a probability score of 0.75 to 0.99. The comparison of the binding pockets identified that BPV types 2 and 13 had the highest number of common amino acid sequences. Further the alpha helix structure of specific common amino acid sequences, contribute to a more robust and widespread affinity interaction with both E1 of various BPV types and EGFR. Analysis of thuja phytochemicals suggested superior efficacy of Beyerene and Terpinene-4-ol towards all ten BPV targets and bEGFR. In conclusion, our comprehensive study leading to identification of E1 protein of BPV as a major interacting network with bEGFR, their key binding sites, and efficacy of thuja phytoconstituents offer valuable insight into further experimental validation and development of novel therapeutic strategies against BPV-associated diseases.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Identification of novel therapeutic inhibitors against E6 and E7 oncogenes of HPV-16 associated with cervical cancer 97%
- A proteomic perspective and involvement of cytokines in SARS-CoV-2 infection 95%
- In silico comparative genomics of SARS-CoV-2 to determine the source and diversity of the pathogen in Bangladesh 95%
Similar papers in this journal
Similar papers in this journal
- Prediction and Evolution of B Cell Epitopes of Surface Protein in SARS-CoV-2 94%
- Reverse-transcription recombinase-aided amplification assay for H5 subtype avian influenza virus 93%
- HTLV-1 reverse transcriptase homology model provides structural basis for sensitivity to existing nucleoside/nucleotide reverse transcriptase inhibitors 92%
Similar papers in this journal
- Crystal violet structural analogues identified by in silico drug repositioning present anti-Trypanosoma cruzi activity through inhibition of proline transporter TcAAAP069 95%
- Identifying potential natural inhibitors of Brucella melitensis Methionyl-tRNA synthetase through an in-silico approach 95%
- Chikungunya Outbreak in Bangladesh (2017): Clinical and hematological findings 94%
Similar papers in this journal
- In vitro screening of anti-viral and virucidal effects against SARS-CoV-2 by Hypericum perforatum and Echinacea. 96%
- Machine learning prediction of antiviral-HPV protein interactions for anti-HPV pharmacotherapy 95%
- Emergence of SARS-CoV-2 Omicron Variant JN.1 in Tamil Nadu, India - Clinical Characteristics and Novel Mutations 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.