Nanobodies have remarkable properties in terms of stability, solubility, high selectivity and specificity towards their targets. This makes them powerful tools in a wide series of biomedical and biotechnological applications that range from the design of tumor-targeted therapies to nanoscale detection. The project aims to develop an effective computational pipeline to predict nanobodies that selectively bind to a specific antigen, in an interdisciplinary effort building upon the complementary expertise of the promoters in experimental nanobody-enabled structural biology and in immunoinformatics. The first module of the pipeline will consist of an in-silico nanobody affinity maturation method which is able to computationally screen a large number of nanobody variants and identify those that most increase the nanobody-antigen affinity. It will be validated through in-vitro biophysical characterization of the in-silico selected mutants. Two other computational modules will be developed, a predictor of nanobody-binding epitopes and a screening tool of DNA nanobody libraries to identify specific antigen binders, which will then be applied to nanobody repertoires of immunized camelids. The computational pipeline developed in this project will confer a huge advantage in guiding experimental analyses and speeding up the identification of antigen-specific nanobodies for their multiple use as therapeutic drugs or biotechnological applications.
Fabrizio Pucci and Marianne Rooman, Computational Biology and Bioinformatics, Université Libre de Bruxelles (ULB), Brussels, Belgium
Alexandre Wohlkonig and Jan Steyaert, Structural Biology Brussels, Vrije Universiteit Brussel (VUB), Brussels, Belgium and VIB-VUB Center for Structural Biology, Vlaams Instituut Biotechnologie (VIB), Brussels, Belgium
Maxime Tixhon, Maxime.Tixhon@ulb.be