Nonproteinogenic deep mutational scanning of linear and cyclic peptides.
Nonproteinogenic deep mutational scanning of linear and cyclic peptides.
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DOI：
10.1073/pnas.1809901115
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发表时间：
2018-10-23
影响因子：
11.1
通讯作者：
Suga H
中科院分区：
文献类型：
--
作者：
Rogers JM;Passioura T;Suga H
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. 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.
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影响因子：
16.6
作者：
Kawamura A;Münzel M;Kojima T;Yapp C;Bhushan B;Goto Y;Tumber A;Katoh T;King ON;Passioura T;Walport LJ;Hatch SB;Madden S;Müller S;Brennan PE;Chowdhury R;Hopkinson RJ;Suga H;Schofield CJ
通讯作者：
Schofield CJ
影响因子：
3.3
作者：
Gray VE;Hause RJ;Fowler DM
通讯作者：
Fowler DM
影响因子：
4
作者：
Rezaei Araghi R;Ryan JA;Letai A;Keating AE
通讯作者：
Keating AE
影响因子：
9.2
作者：
Olson, C. Anders;Wu, Nicholas C.;Sun, Ren
通讯作者：
Sun, Ren
影响因子：
4.6
作者：
Lyamichev, Victor I.;Goodrich, Lauren E.;Patel, Jigar J.
通讯作者：
Patel, Jigar J.