Evidence map›Paper›PMID 28759230›Full record

ArticleJournal of the American Chemical Society2017

Targeting Unoccupied Surfaces on Protein-Protein Interfaces.

David Rooklin, Ashley E Modell, Haotian Li, Viktoriya Berdan, Paramjit S Arora, Yingkai Zhang

Abstract read
In one paragraph

Article in Journal of the American Chemical Society, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Integrated Molecular Modeling and Machine Learning for Drug Design.Journal of chemical theory and computation · 2023
    Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. A Sos proteomimetic as a pan-Ras inhibitor.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  17. Review
  18. Article
  19. Article
  20. 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

6 authors.

David RooklinDepartment of Chemistry, New York University , New York, New York 10003, United States.
Ashley E ModellDepartment of Chemistry, New York University , New York, New York 10003, United States.
Haotian LiDepartment of Chemistry, New York University , New York, New York 10003, United States.
Viktoriya BerdanDepartment of Chemistry, New York University , New York, New York 10003, United States.
Paramjit S AroraDepartment of Chemistry, New York University , New York, New York 10003, United States.ORCID 0000-0001-5315-401X
Yingkai ZhangDepartment of Chemistry, New York University , New York, New York 10003, United States.ORCID 0000-0002-4984-3354

Funding

Biomolecular Recognition with Artificial Alpha-HelicesR01GM073943 · NIGMS · NEW YORK UNIVERSITY · PI ARORA, PARAMJIT S · 2005 to 2018
$4.4M
Computational inhibitor design to target protein-protein interactionsR01GM120736 · NIGMS · NEW YORK UNIVERSITY · PI ARORA, PARAMJIT S, ZHANG, YINGKAI · 2016 to 2019
$1.6M
NIGMS NIH HHS R01 GM073943NIGMS NIH HHS R01 GM120736
6 · The paper itself

Abstract

The use of peptidomimetic scaffolds to target protein-protein interfaces is a promising strategy for inhibitor design. The strategy relies on mimicry of protein motifs that exhibit a concentration of native hot spot residues. To address this constraint, we present a pocket-centric computational design strategy guided by AlphaSpace to identify high-quality pockets near the peptidomimetic motif that are both targetable and unoccupied. Alpha-clusters serve as a spatial representation of pocket space and are used to guide the selection of natural and non-natural amino acid mutations to design inhibitors that optimize pocket occupation across the interface. We tested the strategy against a challenging protein-protein interaction target, KIX/MLL, by optimizing a single helical motif within MLL to compete against the full-length wild-type MLL sequence. Molecular dynamics simulation and experimental fluorescence polarization assays are used to verify the efficacy of the optimized peptide sequence.

Indexed as

Amino Acid MotifsAmino Acid SequenceBinding SitesModels, MolecularMolecular Dynamics SimulationProtein BindingProtein DomainsProteinsProteins

Identifiers

PMID28759230
PMCPMC5677581

What OpenQuestion holds

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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.