Structure-based antibody design for modulating macromolecular interactions

Antibodies are unique in their high affinity and specificity for a binding partner making them one of the most useful molecules for biomedical applications. Currently, therapeutic antibodies are the largest class of biopharmaceuticals with five monoclonal antibodies (mABs) being in the top-ten blockbusters on the global pharmaceuticals market. Antibodies are protein molecules that mediate adaptive immune responses in vertebrates. Exploitation of antibodies for therapeutic purposes demands more efficient ways for the development of these biomolecules, in addition to current standard laboratory-based antibody discovery experiments. Rapidly advancing computational approaches in structural biology are very promising tools for providing fast, biophysically- based results. Different bioinformatics methods such as homology modelling, protein-protein docking, protein interface prediction and molecular dynamics are used for rational antibody design. Moreover, such important factors as immunogenicity and biophysical properties of antibodies can also be assessed with computational approaches. In our research we are aiming to develop and analyse therapeutically relevant antibodies under application of existing computational methods and datasets. Moreover, our goal is to enrich the scientific community with findings which will be developed during the research to support and facilitate advances in computer-based biomolecular research.