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Nonproteinogenic deep mutational scanning of linear and cyclic peptides

Joseph M. Rogers, Toby Passioura, and Hiroaki Suga
PNAS October 23, 2018 115 (43) 10959-10964; published ahead of print October 9, 2018 https://doi.org/10.1073/pnas.1809901115
Joseph M. Rogers
aDepartment of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan;
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Toby Passioura
aDepartment of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan;
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Hiroaki Suga
aDepartment of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan;bCore Research for Evolutionary Science and Technology, Japan Science and Technology Agency, Saitama 332-0012, Japan
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  • For correspondence: hsuga@chem.s.u-tokyo.ac.jp
  1. Edited by David Baker, University of Washington, Seattle, WA, and approved September 18, 2018 (received for review June 10, 2018)

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Significance

The 20 proteinogenic amino acids have physicochemical properties that allow peptides and proteins to fold and bind. However, there are numerous unnatural, nonproteinogenic amino acids that may be equally good, or even better, at folding and binding. Exploration of these alternative peptide building blocks has been limited by slow, one-at-a-time synthesis and testing. We describe how, in a single experiment, multiple nonproteinogenic amino acids can be trialed at all positions in a peptide sequence, with thousands of modifications tested in parallel. This permits detailed analysis of how chemical structure relates to function and allows for systematic comparisons of proteinogenic and nonproteinogenic chemistry. Such analysis can guide the improvement of drug-candidate peptides, including the therapeutically promising class of cyclic peptides.

Abstract

High-resolution structure–activity analysis of polypeptides requires amino acid structures that are not present in the universal genetic code. Examination of peptide and protein interactions with this resolution has been limited by the need to individually synthesize and test peptides containing nonproteinogenic amino acids. We describe a method to scan entire peptide sequences with multiple nonproteinogenic amino acids and, in parallel, determine the thermodynamics of binding to a partner protein. By coupling genetic code reprogramming to deep mutational scanning, any number of amino acids can be exhaustively substituted into peptides, and single experiments can return all free energy changes of binding. We validate this approach by scanning two model protein-binding peptides with 21 diverse nonproteinogenic amino acids. Dense structure–activity maps were produced at the resolution of single aliphatic atom insertions and deletions. This permits rapid interrogation of interaction interfaces, as well as optimization of affinity, fine-tuning of physical properties, and systematic assessment of nonproteinogenic amino acids in binding and folding.

  • BH3 domains
  • noncanonical amino acids
  • structure–activity relationships
  • macrocyclic peptides
  • intrinsically disordered proteins

Footnotes

  • ↵1To whom correspondence should be addressed. Email: hsuga{at}chem.s.u-tokyo.ac.jp.
  • Author contributions: J.M.R. designed research; J.M.R. and T.P. performed research; J.M.R. and T.P. contributed new reagents/analytic tools; J.M.R. analyzed data; and J.M.R., T.P., and H.S. wrote the paper.

  • The authors declare no conflict of interest.

  • This article is a PNAS Direct Submission.

  • This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1809901115/-/DCSupplemental.

  • Copyright © 2018 the Author(s). Published by PNAS.

This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

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Nonproteinogenic deep mutational scanning of linear and cyclic peptides
Joseph M. Rogers, Toby Passioura, Hiroaki Suga
Proceedings of the National Academy of Sciences Oct 2018, 115 (43) 10959-10964; DOI: 10.1073/pnas.1809901115

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Nonproteinogenic deep mutational scanning of linear and cyclic peptides
Joseph M. Rogers, Toby Passioura, Hiroaki Suga
Proceedings of the National Academy of Sciences Oct 2018, 115 (43) 10959-10964; DOI: 10.1073/pnas.1809901115
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