In silico prediction of structural changes in human papillomavirus type 16 (HPV16) E6 oncoprotein and its variants

Abstract

Abstract Background HPV16 infection is one of the main risk factors involved in the development of cervical cancer, mainly due to the high oncogenic potential of the viral proteins E6 and E7, which are involved in the different processes of malignant transformation. There is a broad spectrum of intratypical variation of E6, which is reflected in its high diversity, biological behavior, global distribution and risk of causing cervical cancer. Experimental studies have shown that the intratypical variants of the protein E6 from the European variants (E-G350, E-A176/G350, E-C188/G350) and Asian-American variants (AAa and AAc), are capable of inducing the differential expression of genes involved in the development of cervical cancer. Results An in silico analysis was performed to characterize the molecular effects of these variations using the structure of the HPV16 E6 oncoprotein (PDB: 4XR8; chain H) as a template. In particular, we evaluated the 3D structures of the intratypical variants by structural alignment, ERRAT, Ramachandran plots and prediction of protein disorder, which was further validated by molecular dynamics simulations. Our results, in general, showed no significant changes in the protein 3D structure. However, we observed subtle changes in protein physicochemical features and structural disorder in the N- and C-termini. Conclusions Our results showed that mutations in the viral oncogene E6 of six high-risk HPV16 variants are effectively neutral and do not cause significant structural changes except slight variations of structural disorder. As structural disorder is involved in rewiring protein-protein interactions, these results suggest a differential pattern of interaction of E6 with the target protein P53 and possibly different patterns of tumor aggressiveness associated with certain types of variants of the E6 oncoprotein.

Keywords

• HPV16
• E6 oncoprotein variants
• 3D structure
• Molecular modeling
• Protein disorder
• Molecular dynamics simulations