Article ID Journal Published Year Pages File Type
4497578 Journal of Theoretical Biology 2010 7 Pages PDF
Abstract

High-risk types of human papillomaviruses (HPVs) are the etiological agents in nearly all cases (99.7%) of cervical cancer, and the HPV E6 protein is one of the two viral oncoproteins which is expressed in virtually all HPV-positive cancers. Therefore, classifying the risk type of HPVs is very useful and necessary for diagnosis and remedy of cervical cancer. To predict and to classify the risk types of HPV by bioinformatics analysis, 96 E6 protein sequences from available databases were obtained. To investigate the risk type of these sequences, PseAAC server, ROC curves and statistical analysis were applied. Our classification was based on some characters of HPV E6 proteins, such as hydrophobicity, hydrophilicity, side chain mass, PK of the α-COOH group, PK of the α-NH3+ group and PI at 25 °C. Risk type of 4 unknown HPV types and 25 non-reported HPV types were also predicted. These results show that bioinformatics based theoretical approaches can direct and simplify experimental studies.

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