MOLECULAR TARGET IDENTIFICATION AND NGS DATA ANALYSIS OF HUMAN PTPN14 IN A COMPLEX WITH CR3 DOMAIN OF HPV18 E7

Cervical carcinoma is one of the major causes of cancer-related mortality among women in whole world, particularly in regions lacking robust screening and vaccination programs. Human papillomavirus (HPV), especially high-risk strains like HPV18, has been known as a primary etiological agent in the development of this malignancy. The E7 oncoprotein encoded by HPV18 is known to interfere with host tumor suppressor proteins, notably Protein Tyrosine Phosphatase Non-Receptor Type 14 (PTPN14). This study investigates the molecular interaction between PTPN14 and the CR3 domain of HPV18 E7 to explore therapeutic targeting opportunities. We utilized crystallographic data from the Protein Data Bank to assess the binding interface between these two proteins and conducted molecular docking studies with clinically relevant chemotherapeutic agents. Through computational docking using molecular docking, three potential ligands Mitomycin, Topotecan, and Paclitaxel C were evaluated for their binding affinity to the interaction interface. Topotecan exhibited the most favorable docking score, suggesting a strong binding affinity and potential disruption of the oncogenic protein complex. Structural validation was carried out using structure Vlaidation and Ramachandran plot analysis via PROCHECK, which confirmed the high stereochemical quality of the model. The binding pockets were visualized using PyMOL, and protein-ligand interactions were assessed for hydrogen bonding and electrostatic compatibility. Next-Generation Sequencing (NGS) data provided supporting evidence for the significance of PTPN14 in cervical carcinogenesis. Our findings suggest that targeting the PTPN14–HPV18 E7 interaction could serve as a novel strategy in the treatment of HPV-associated cervical cancer. The identified compounds, particularly Topotecan, demonstrate potential for further in-vitro and in-vivo validation as lead candidates. This study emphasizes the utility of integrative bioinformatics and structural biology in uncovering molecular mechanisms and therapeutic vulnerabilities in viral oncogenesis.