YabXnization Platform: A Monoclonal Antibody Heterologization Server based on Rational Design and Artificial Intelligence-Assisted Computation

The application of antibody therapeutics is promising in the field of immunotherapy. While, heterologization should be done in most cases before applying the therapeutic antibodies into bodies, e.g., humanization, caninization and felinization for human beings, canine and feline, respectively. Here we report YabXnization, the platform which realizes antibody heterologization on the basis of rational design and artificial intelligence (AI)-assisted computation. YabXnization provides two ways for heterologization: traditional CDR-grafting and backmutation-based rational design; and AI-assisted fusion computational design. Taking humanization as example, both of the two ways first find the proper template for heavy and light chains with CDR-grafting followed. For rational design, bioinformatics analysis-based backmutation is then conducted. For AI-assisted computational design, the backmutation and humanness evaluation are implemented through evolutionary computation framework with DeepForest-based humanness evaluation model and the distance to the previously found human template as objective functions. Finally, the top