Principles for computational design of binding antibodies
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Edited by William F. DeGrado, School of Pharmacy, University of California, San Francisco, CA, and approved August 25, 2017 (received for review May 1, 2017)

Significance
Antibodies are the most versatile class of binding molecule known, and have numerous applications in biomedicine. Computational design of antibodies, however, poses unusual difficulties relative to previously designed proteins, as antibodies comprise multiple nonideal features, such as long and unstructured loops and buried charges and polar interaction networks. We developed an algorithm that uses information on backbone conformations and sequence-conservation patterns observed in natural antibodies to design new antibody binders. Designed antibodies were very different in sequence from natural ones, but had similarly desirable properties of affinity and stability, and molecular structures showed high accuracy relative to the design models. The design principles we implemented can be used to design other functional folds, including many enzyme classes.
Abstract
Natural proteins must both fold into a stable conformation and exert their molecular function. To date, computational design has successfully produced stable and atomically accurate proteins by using so-called “ideal” folds rich in regular secondary structures and almost devoid of loops and destabilizing elements, such as cavities. Molecular function, such as binding and catalysis, however, often demands nonideal features, including large and irregular loops and buried polar interaction networks, which have remained challenging for fold design. Through five design/experiment cycles, we learned principles for designing stable and functional antibody variable fragments (Fvs). Specifically, we (i) used sequence-design constraints derived from antibody multiple-sequence alignments, and (ii) during backbone design, maintained stabilizing interactions observed in natural antibodies between the framework and loops of complementarity-determining regions (CDRs) 1 and 2. Designed Fvs bound their ligands with midnanomolar affinities and were as stable as natural antibodies, despite having >30 mutations from mammalian antibody germlines. Furthermore, crystallographic analysis demonstrated atomic accuracy throughout the framework and in four of six CDRs in one design and atomic accuracy in the entire Fv in another. The principles we learned are general, and can be implemented to design other nonideal folds, generating stable, specific, and precise antibodies and enzymes.
Footnotes
↵1D.B. and M.G.P. contributed equally to this work.
↵2Present address: IgC Bio Ltd., Ness Ziona 7403622, Israel.
↵3Present address: Department of Biochemistry and Structural Biology, Center for Molecular Protein Science, Lund University, SE-221 00 Lund, Sweden.
- ↵4To whom correspondence should be addressed. Email: sarel{at}weizmann.ac.il.
Author contributions: D.B., M.G.P., and S.J.F. designed research; D.B., M.G.P., O.D., T.U., S.A., and M.D.T. performed research; G.D.L. and C.N. contributed new reagents/analytic tools; D.B., M.G.P., O.D., S.A., and S.J.F. analyzed data; and M.G.P. and S.J.F. wrote the paper.
Conflict of interest statement: S.J.F. is a consultant for IgC Bio Ltd. The Weizmann Institute of Science has filed a patent on antibody design.
This article is a PNAS Direct Submission.
Data deposition: The atomic coordinates and structure factors for the unbound antigen-binding fragments 5ins16_ev and 5ins14 have been deposited in the RCSB Protein Data Bank with accession codes 5NB5 and 5NBI, respectively.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1707171114/-/DCSupplemental.
Freely available online through the PNAS open access option.
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