Prediction of the Structure of Therapeutic Antibodies with their Antigens PROJECT SUMMARY Antibodies play a critical role for recognition of foreign intruders. Due to their high affinity and specificity, they have been exploited as therapeutic molecules and biotechnological components for sensing and assembly. Recent high-throughput sequencing and nanofluidics technologies have elucidated large sets (103?104) of nave and antigen-exposed antibody sequences, and it is now possible to determine a complete set of viruses that an individual has encountered based on one?s antibodies. In addition to their biological, medical, and technological importance, the extensive knowledge about antibodies makes them an ideal model system for studying protein binding and recognition. A reliable toolkit to study protein binding and recognition is the missing link to fully unlock the bountiful information in antibody and antigen repertoires. Prior work demonstrated success in predicting antibody structures, and this proposal focuses on the docking problem. While docking algorithms are reliable for local searches and small conformational changes, significant challenges remain in searching large antigens to identify epitopes and in determining the correct binding orientation when there is backbone flexibility or uncertainty in the homology-modeled starting structures. Accounting for binding-induced backbone conformational changes remains the central difficulty in the protein?protein docking field, primarily due to sampling limitations. An additional challenge is that many viral coat and bacterial proteins are glycosylated. Glycans are well hydrated and can be flexible; these modifications are typically ignored entirely by docking algorithms. The long-term goal of this research is the accurate prediction of structures of antibodies and antibody?antigen complexes such that they are useful to decode biological mechanisms and engineer improved therapeutics. Thus, the first two aims of the current project are to (1) develop fast, aggressive, flexible backbone docking approaches, and (2) extend docking to include glycosylated antigens. Finally, the third aim will be to (3) apply antibody modeling and docking to determine biomarkers and therapeutics for celiac disease and pulmonary hypertension.
Antibodies play a critical role in the immune system for recognition of foreign intruders, and are excellent therapeutic molecules because of their high affinity and specificity. This project investigates computational approaches to determine the three-dimensional structures of antibodies alone and in complex with their target antigens. Specific challenges include binding-induced backbone conformational change, glycosylated antigens, and applications to celiac disease and pulmonary hypertension.
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