Computational design of antibody-affinity improvement beyond in vivo maturation

Abstract

Antibodies are used extensively in diagnostics and as therapeutic agents. Achieving high-affinity binding is important for expanding detection limits, extending dissociation half-times, decreasing drug dosages, and increasing drug efficacy. However, antibody affinity maturation in vivo often fails to produce antibody drugs of the targeted potency 1 , making further affinity maturation in vitro by directed evolution or computational design necessary. Here we present an iterative computational design procedure that focuses on electrostatic binding contributions and single mutants. By combining multiple designed mutations, a 10-fold affinity improvement to 52 pM was engineered into the anti-EGFR drug cetuximab (Erbitux), and a 140-fold improvement in affinity to 30 pM was obtained for the anti-lysozyme model antibody D44.1. The generality of the methods were further demonstrated through identification of known affinity-enhancing mutations in the therapeutic antibody bevacizumab (Avastin) and the model anti-fluorescein antibody 4-4-20. These results demonstrate novel computational capabilities for enhancing and accelerating the development of protein reagents and therapeutics.Computational design depends critically on two capabilities: accurate energetic evaluation and thorough conformational search. Previous work has addressed many problems related to the design of improved protein-protein binding affinity, such as the design of stable protein folds 2-4 , binding pockets for peptides and small molecules [5][6][7] , altered protein-protein specificity [8][9][10][11][12] , and altered enzymatic activity [13][14][15] . The design of improved antigen-binding affinity has met with limited success, however [16][17][18][19] . Challenges for protein-protein affinity design include conformational change upon binding, interfacial trapped water molecules, polar and charged side chains, and the trade-off of protein-solvent with protein-protein interactions from the unbound to bound state. Fine free energy discrimination for redesign from nanomolar to picomolar affinities is a particular challenge.Correspondence and requests for materials should be addressed to B.T. (tidor@mit.edu) or K.D.W. (wittrup@mit.edu).. ‡ Present address: Codon Devices, Inc., One Kendall Square, Building 300, Cambridge, MA 02139, USA Author Contributions B.T. oversaw all computational aspects of the work, and K.D.W. oversaw all experimental aspects of the work. S.M.L. developed and adopted the design methods and software and carried out all computational and experimental studies. The authors as a group interpreted the results of the calculations and selected the mutants to create experimentally. S.M.L. drafted the manuscript, and all authors contributed to its editing. Competing Interests StatementThe authors declare that they have no competing financial interests. NIH Public Access NIH-PA Author ManuscriptA robust design strategy should both produce a considerable fraction of designs that are successful when tested experimentally, and yield su...

Computational structure-based redesign of enzyme activity

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Assessment of Solvated Interaction Energy Function for Ranking Antibody–Antigen Binding Affinities

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Redesign of a cross-reactive antibody to dengue virus with broad-spectrum activity and increased in vivo potency

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