Computational identification of PTPRJ peptide targeting the Epstein Barr virus latent membrane protein 1.

The treatment of Epstein-Barr virus (EBV)-associated malignancies is increasingly recognizing the necessity of personalized medicine strategies to enhance therapeutic outcomes. This research addresses this need by computationally investigating potential peptide inhibitors targeting the latent membrane protein 1 (LMP1), a key oncoprotein in EBV-related cancers. The study specifically focuses on the C-terminal activating region (CTAR) of LMP1, a critical domain for its oncogenic signalling. To identify promising inhibitors, a comprehensive computational methodology was employed, encompassing Unidock virtual screening, PYRX molecular docking, AMBER molecular dynamics simulations, and CPPTRAJ analysis. This integrated approach led to the identification of a Protein Tyrosine Phosphatase Receptor Type J (PTPRJ) agonist peptide derived from the CancerPPD database as a potential inhibitor of EBV LMP1. PTPRJ is a known tumour suppressor involved in regulating cellular proliferation, migration, and angiogenesis. The findings suggest that the identified peptide agonist may exert its inhibitory effect on LMP1 by activating PTPRJ, thereby influencing cancer cell behaviour and the tumour microenvironment. This research presents a significant starting point for the development of novel therapeutic interventions tailored for EBV-related cancers. The application of computational methods underscores a strategic approach to tackle the complexities of personalized medicine in the context of these malignancies. Furthermore, the focus on the LMP1 CTAR region as a therapeutic target highlights the critical role of this viral protein in driving oncogenesis. The integration of diverse computational tools in this study signifies a rigorous and multifaceted strategy for identifying potential drug candidates.