IBC's 22nd Annual Antibody Engineering and 9th Annual Antibody Therapeutics International Conferences and the 2011 Annual Meeting of The Antibody Society, December 5-8, 2011, San Diego, CA

Generation and testing anti-influenza human monoclonal antibodies in a new humanized mouse model (DRAGA: HLA-A2. HLA-DR4. Rag1 KO. IL-2Rγc KO. NOD)

Pandemic outbreaks of influenza type A viruses have resulted in numerous fatalities around the globe. Since the conventional influenza vaccines (CIV) provide less than 20% protection for individuals with weak immune system, it has been considered that broadly cross-neutralizing antibodies may provide a better protection. Herein, we showed that a recently generated humanized mouse (DRAGA mouse; HLA-A2. HLA-DR4. Rag1KO. IL-2Rgc KO. NOD) that lacks the murine immune system and expresses a functional human immune system can be used to generate cross-reactive, human anti-influenza monoclonal antibodies (hu-mAb). DRAGA mouse was also found to be suitable for influenza virus infection, as it can clear a sub-lethal infection and sustain a lethal infection with PR8/A/34 influenza virus. The hu-mAbs were designed for targeting a human B-cell epitope (¹⁸⁰WGIHHPPNSKEQ QNLY¹⁹⁵) of hemagglutinin (HA) envelope protein of PR8/A/34 (H1N1) virus with high homology among seven influenza type A viruses. A single administration of HA_180-195 specific hu-mAb in PR8-infected DRAGA mice significantly delayed the lethality by reducing the lung damage. The results demonstrated that DRAGA mouse is a suitable tool to (i) generate heterotype cross-reactive, anti-influenza human monoclonal antibodies, (ii) serve as a humanized mouse model for influenza infection, and (iii) assess the efficacy of anti-influenza antibody-based therapeutics for human use.

PyIgClassify: a database of antibody CDR structural classifications

Classification of the structures of the complementarity determining regions (CDRs) of antibodies is critically important for antibody structure prediction and computational design. We have previously performed a clustering of antibody CDR conformations and defined a systematic nomenclature consisting of the CDR, length and an integer starting from the largest to the smallest cluster in the data set (e.g. L1-11-1). We present PyIgClassify (for Python-based immunoglobulin classification; available at http://dunbrack2.fccc.edu/pyigclassify/), a database and web server that provides access to assignments of all CDR structures in the PDB to our classification system. The database includes assignments to the IMGT germline V regions for heavy and light chains for several species. For humanized antibodies, the assignment of the frameworks is to human germlines and the CDRs to the germlines of mice or other species sources. The database can be searched by PDB entry, cluster identifier and IMGT germline group (e.g. human IGHV1). The entire database is downloadable so that users may filter the data as needed for antibody structure analysis, prediction and design.