(427a) Computational Antibody Design by Canonical Structure Identification and Optimal Amino Acid Selection | AIChE

(427a) Computational Antibody Design by Canonical Structure Identification and Optimal Amino Acid Selection



In this work, we introduce a general computational method for the design of antibody binding pockets to bind specified molecules, including haptens, peptides, and proteins. It has long been known that most of the structural variability of antibodies is confined to six Complimetarity Determining Regions, of which five assume only a well-defined number of canonical structures. We first use geometry optimization criteria to identify combinations of canonical structures consistent with the formation of a favorable binding pocket for a given molecule. Subsequently, we use the Iterative Protein Redesign Optimization (IPRO) procedure to ?fill in? the amino acid choices of the selected structures. The proposed method for computational antibody design is demonstrated with designs to bind fluorescein (hapten), a peptide of the capsid protein of Hepatitis C, and vascular endothelial growth factor (protein).