Evidence map›Paper›PMID 30301798›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2018

Nonproteinogenic deep mutational scanning of linear and cyclic peptides.

Joseph M Rogers, Toby Passioura, Hiroaki Suga

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

48 citing papers in PubMed.

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  7. De novo discovery of bicyclic cysteine-rich peptides targeting gasdermin D.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  10. Journal of the American Chemical Society · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Joseph M RogersDepartment of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan.
Toby PassiouraDepartment of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan.
Hiroaki SugaDepartment of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan; hsuga@chem.s.u-tokyo.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Amino AcidsAmino Acid SequenceGenetic CodePeptides, CyclicProtein BindingProteinsStructure-Activity RelationshipThermodynamicsAmino AcidsPeptides, CyclicProteinsBH3 domainsintrinsically disordered proteinsmacrocyclic peptidesnoncanonical amino acidsstructure–activity relationships

Identifiers

PMID30301798
PMCPMC6205457

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.