Antibodies are an important class of therapeutic molecules used in the treatment of severe diseases. Computational tools used to facilitate the design and engineering of antibody molecules with drug-like properties rely on good structural understanding of complex formation with their target antigens. Complementarity-determining regions (CDRs), also known as hypervariable loops, on the antibody provide specificity and affinity for a particular antigen and are thus the focus of drug discovery efforts. However, predicting antigen-binding sites, or epitopes, remains a significant challenge in the absence of structural information for the antibody-antigen complex.

 A recent study by BioExcel researchers at Utrecht Universiteit demonstrates that modelling of antibody-antigen complexes using information about hypervariable loops and, when available, a loose definition of the epitope, improves docking results. HADDOCK, which directly uses this information to guide docking, performs better than three other software applications tested.

Of particular interest was the success obtained with HADDOCK in improving the binding conformation of the CDR H3, which provides the highest binding contribution in antibody-antigen complex formation and is notoriously difficult to model due to its high structural and sequence variability. In cases where CDR H3 underwent a large conformational change upon binding HADDOCK succeeded in improving its conformation toward the bound form, with the largest improvements seen in the side-chain contacts rather than in the backbone conformation. Predicting correct contacts is particularly relevant for antibody engineering.

To get you started with setting up antibody-antigen docking modelling calculations we have developed a free online tutorial which uses the HADDOCK webserver to predict the structure of the monoclonal antibody gevokizumab in complex with its antigen Interleukin 1-ß.

If you would like to know more about antibody-antigen docking using HADDOCK for your industry project, please contact