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Individuation of monoclonal anti-HPV16 E7 antibody linear peptide epitope by computational biology |
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| Authors: | Darja Kanduc Alberta Lucchese Abraham Mittelman |
| Institution: | a CARSO Cancer Research Center, University of Bari, Italy b Department of Biochemistry and Molecular Biology, University of Bari, Italy c Department of Microbiology and Immunology, New York Medical College, Valhalla, NY 10595, USA d Department Medicine, Division of Oncology/Hematology, New York Medical College, Valhalla, NY, USA 10595, USA |
| Abstract: | We applied computational biology to identify the linear amino acid sequence recognized by a mouse monoclonal antibody raised against the full length HPV16 E7 oncoprotein. Computer-assisted search for the epitopic peptide used two parameters: the capability of E7 peptides to bind to MHC class II molecules, and the similarity level of the oncoprotein sequence to the mouse proteome. We report that anti-E7 mAb recognized the peptide having both high binding potential to MHC II molecules and low level of molecular mimicry to mouse proteome. Peptide ability to bind to MHC II molecules appears a necessary but not sufficient condition to determine peptide immunodominance, by needing to be supported by a low degree of peptide similarity to the host’s proteome. |
| Keywords: | Epitope prediction MHC binding potential Molecular mimicry Peptide immunodominance Computational biology |
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