In silico strategy to model LMP1 of Epstein–Barr virus protein

Epstein-Barr Virus (EBV) is among the world's most common and best-studied viruses. The latent membrane protein 1 (LMP1) is an essential latent EBV gene variation. LMP1 is an important EBV oncoprotein with self-renewal properties and cancer stem cell phenotypes. It is found that LMP1 of EBV has a critical role in activating the NF-κB pathway, which is involved in inflammation and immunity. Generally, LMP1 has 386 amino acids, although some strains may have slightly fewer or more amino acids depending on the virus strain. The transmembrane protein LMP1 comprised two terminus domains (N and C terminal) and six hydrophobic transmembrane domains. To date, no complete crystal structure is available for LMP1 except for some of its peptide ligands; hence, this predictive study is crucial for visualising LMP1's entire structure. In silico analysis has helped to analyse the protein sequence. Thus, the present study aims to enlist some of the LMP1 protein's physicochemical and functional properties and provides information about its three-dimensional structure. The complete LMP1 sequence was retrieved from UniProt and was subjected to protein structure analysis based on their protein fragments/regions. The separate regions were then analysed for comparative modelling, protein threading and ab-initio prediction methods to find the best predictive results. The obtained predictive structures were then further validated using various web tools. After validation, the chunked models were combined into one complete structure using PyMol software. The predictive structure modelled through PyMol looks promising and can be validated further with molecular dynamics simulation. In conclusion, this study is the first step in studying the LMP1 and protein interactions to discover LMP1 inhibitors for targeted therapy.