Evidence map›Paper›PMID 35029987›Full record

ArticleJournal of the American Chemical Society2022

Peptide Tethering: Pocket-Directed Fragment Screening for Peptidomimetic Inhibitor Discovery.

Ashley E Modell, Frank Marrone, Nihar R Panigrahi, Yingkai Zhang, Paramjit S Arora

Abstract read
In one paragraph

Article in Journal of the American Chemical Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Photoredox-Catalyzed Lysine C(spJournal of the American Chemical Society · 2026
    Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Integrated Molecular Modeling and Machine Learning for Drug Design.Journal of chemical theory and computation · 2023
    Review
  10. Article
  11. Two-Step Validation Approach for Tools To Study the DNA Repair Enzyme SNM1A.Chembiochem : a European journal of chemical biology · 2023
    Article
  12. Article
  13. Article
  14. Article
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

5 authors.

Ashley E ModellDepartment of Chemistry, New York University, 100 Washington Square East, New York, New York 10003, United States.
Frank MarroneDepartment of Chemistry, New York University, 100 Washington Square East, New York, New York 10003, United States.
Nihar R PanigrahiDepartment of Chemistry, New York University, 100 Washington Square East, New York, New York 10003, United States.
Yingkai ZhangDepartment of Chemistry, New York University, 100 Washington Square East, New York, New York 10003, United States.ORCID 0000-0002-4984-3354
Paramjit S AroraDepartment of Chemistry, New York University, 100 Washington Square East, New York, New York 10003, United States.ORCID 0000-0001-5315-401X

Funding

Protein Domain Mimics as Modulators of Biomolecular InteractionsR35GM130333 · NIGMS · NEW YORK UNIVERSITY · PI Paramjit S Arora · 2019 to 2026
$6.0M
NIGMS NIH HHS R35 GM130333
6 · The paper itself

Abstract

Constrained peptides have proven to be a rich source of ligands for protein surfaces, but are often limited in their binding potency. Deployment of nonnatural side chains that access unoccupied crevices on the receptor surface offers a potential avenue to enhance binding affinity. We recently described a computational approach to create topographic maps of protein surfaces to guide the design of nonnatural side chains [

Indexed as

PeptidesPeptidomimeticsDrug DiscoveryHumansLigandsModels, Molecularp300-CBP Transcription FactorsLigandsp300-CBP Transcription FactorsPeptidesPeptidomimetics

Identifiers

PMID35029987
PMCPMC8959088

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.