Computational Design of Epitope-Specific Functional Antibodies

• DOI: 10.1016/j.celrep.2018.10.081
• Publication Date: 2018-11-20T10:41:36Z
• Authors: Guy Nimrod; Sharon Fischman; Mark Austin; Asael Herman; Feenagh Keyes; Olga Leiderman; David Hargreaves; Marek Strajbl; Jason Breed; Shelley Klompus; Kevin Minton; Jennifer Spooner; Andrew Buchanan; Tristan J. Vaughan; Yanay Ofran
• Keywords: Models, Molecular; 0303 health sciences; QH301-705.5; Computational Biology; Antibodies; 3. Good health; Epitopes; Immunoglobulin Fab Fragments; 03 medical and health sciences; Antibody Specificity; Humans; Amino Acid Sequence; Biology (General); Algorithms

The ultimate goal of protein design is to introduce new biological activity. We propose a computational approach for designing functional antibodies by focusing on epitopes, integrating large-scale statistical analysis with multiple structural models. Machine learning used analyze these models and predict specific residue-residue contacts. use this antibody counter the proinflammatory effect cytokine interleukin-17A (IL-17A). X-ray crystallography confirms that designed binds targeted epitope interaction mediated Cell-based assays confirm functional. Importantly, does not rely high-quality 3D model complex or even solved structure target. As demonstrated here, can be biologically active antibodies, removing some main hurdles in drug discovery.