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Immunome Res. 2007 Sep 18;3:8.

Using the natural evolution of a rotavirus-specific human monoclonal antibody to predict the complex topography of a viral antigenic site.

McKinney BA, Kallewaard NL, Crowe JE Jr, Meiler J.

Department of Genetics, University of Alabama School of Medicine, 720 20th Street South, Birmingham, 35294, USA. bmckinney@genetics.uab.edu.

ABSTRACT: BACKGROUND: Understanding the interaction between viral proteins and neutralizing antibodies at atomic resolution is hindered by a lack of experimentally solved complexes. Progress in computational docking has led to the prediction of increasingly high-quality model antibody-antigen complexes. The accuracy of atomic-level docking predictions is improved when integrated with experimental information and expert knowledge. METHODS: Binding affinity data associated with somatic mutations of a rotavirus-specific human adult antibody (RV6-26) are used to filter potential docking orientations of an antibody homology model with respect to the rotavirus VP6 crystal structure. The antibody structure is used to probe the VP6 trimer for candidate interface residues. RESULTS: Three conformational epitopes are proposed. These epitopes are candidate antigenic regions for site-directed mutagenesis of VP6, which will help further elucidate antigenic function. A pseudo-atomic resolution RV6-26 antibody-VP6 complex is proposed consistent with current experimental information. CONCLUSION: The use of mutagenesis constraints in docking calculations allows for the identification of a small number of alternative arrangements of the antigen-antibody interface. The mutagenesis information from the natural evolution of a neutralizing antibody can be used to discriminate between residue-scale models and create distance constraints for atomic-resolution docking. The integration of binding affinity data or other information with computation may be an advantageous approach to assist peptide engineering or therapeutic antibody design.

PMID: 17877819 [PubMed - in process]

PMCID: PMC2042970

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