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dc.contributor.authorYang, Thao
dc.contributor.authorHer, Lysengkeng
dc.date.accessioned2019-01-29T17:35:39Z
dc.date.available2019-01-29T17:35:39Z
dc.date.issued2018-05
dc.identifier.urihttp://digital.library.wisc.edu/1793/78927
dc.descriptionColor poster with text, images, and tables.en_US
dc.description.abstractThe crystal structure of the mucin monoclonal antibody SM3 complexed with a 13 amino acid MUC1 mucin peptide was determined. The high selectivity of the SM3 antibody to the aberrant carbohydrate cancer mucin peptide suggests that it could be a model for studying different ligand binding as a potential target against certain tumors. This study focusses on the computational modeling and docking of the SM3 antibody complexed with MUC1 mucin epitopes to determine the binding properties. The program Autodock is used to perform the dockings of the ligand to the SM3 antibody in order to determine the affinity values of the complex. We specifically docked and studied the three amino acids APD from the MUC1 mucin peptide (GVTSAPD). On the MUC1 epitope structures, the proline (P) residue was substituted with aromatic residues such as tyrosine, and phenylalanine. In addition, we’ve also substituted the proline with unnatural amino acids such as gamma-aminobutyric acid (GABA), D-α-phenylglycine (DPHG), L-α-phenylglycine (PHG) and beta-alanine (β-Ala). The structures of the docked ligands were then analyzed with Pymol to determine the interactions between the SM3 antibody and the peptide derivatives. Results showed that the epitopes containing aromatic residues have the higher affinity.en_US
dc.description.sponsorshipUniversity of Wisconsin--Eau Claire Office of Research and Sponsored Programs ; National Science Foundationen_US
dc.language.isoen_USen_US
dc.relation.ispartofseriesUSGZE AS589;
dc.subjectMucin peptidesen_US
dc.subjectComputational docking simulationsen_US
dc.subjectChemistryen_US
dc.subjectPostersen_US
dc.titleComputational Docking of Mucin Peptide Derivatives with SM3 Antibodyen_US
dc.typePresentationen_US


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    Posters of collaborative student/faculty research presented at Student Research Day

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