Evidence mapPaperPMID 39786807Full record

ArticleeLife2025

A high-throughput platform for single-molecule tracking identifies drug interaction and cellular mechanisms.

David Trombley McSwiggen, Helen Liu, Ruensern Tan, Sebastia Agramunt Puig, Lakshmi B Akella, Russell Berman, Mason Bretan, Hanzhe Chen, Xavier Darzacq, Kelsey Ford and 20 more

Abstract read
In one paragraph

Article in eLife, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Leveraging AI for cell biology discovery.Biochemical Society transactions · 2026
    Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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

30 authors.

David Trombley McSwiggenEikon Therapeutics Inc, Hayward, United States.
Helen LiuEikon Therapeutics Inc, Hayward, United States.
Ruensern TanEikon Therapeutics Inc, Hayward, United States.
Sebastia Agramunt PuigEikon Therapeutics Inc, Hayward, United States.
Lakshmi B AkellaEikon Therapeutics Inc, Hayward, United States.
Russell BermanEikon Therapeutics Inc, Hayward, United States.
Mason BretanEikon Therapeutics Inc, Hayward, United States.
Hanzhe ChenEikon Therapeutics Inc, Hayward, United States.
Xavier DarzacqEikon Therapeutics Inc, Hayward, United States.ORCID https://orcid.org/0000-0003-2537-8395
Kelsey FordEikon Therapeutics Inc, Hayward, United States.
Ruth GodbeyEikon Therapeutics Inc, Hayward, United States.
Eric GonzalezEikon Therapeutics Inc, Hayward, United States.
Adi HanukaEikon Therapeutics Inc, Hayward, United States.
Alec HeckertEikon Therapeutics Inc, Hayward, United States.
Jaclyn J HoEikon Therapeutics Inc, Hayward, United States.
Stephanie L JohnsonEikon Therapeutics Inc, Hayward, United States.
Reed KelsoEikon Therapeutics Inc, Hayward, United States.
Aaron KlammerEikon Therapeutics Inc, Hayward, United States.
Ruchira KrishnamurthyEikon Therapeutics Inc, Hayward, United States.
Jifu LiEikon Therapeutics Inc, Hayward, United States.
Kevin LinEikon Therapeutics Inc, Hayward, United States.
Brian MargolinEikon Therapeutics Inc, Hayward, United States.ORCID https://orcid.org/0000-0003-3365-7677
Patrick McNamaraEikon Therapeutics Inc, Hayward, United States.ORCID https://orcid.org/0000-0003-2756-0887
Laurence MeyerEikon Therapeutics Inc, Hayward, United States.
Sarah E PierceEikon Therapeutics Inc, Hayward, United States.
Akshay SuleEikon Therapeutics Inc, Hayward, United States.
Connor StashkoEikon Therapeutics Inc, Hayward, United States.
Yangzhong TangEikon Therapeutics Inc, Hayward, United States.
Daniel J AndersonEikon Therapeutics Inc, Hayward, United States.
Hilary P BeckEikon Therapeutics Inc, Hayward, United States.ORCID https://orcid.org/0000-0002-5003-1361

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The regulation of cell physiology depends largely upon interactions of functionally distinct proteins and cellular components. These interactions may be transient or long-lived, but often affect protein motion. Measurement of protein dynamics within a cellular environment, particularly while perturbing protein function with small molecules, may enable dissection of key interactions and facilitate drug discovery; however, current approaches are limited by throughput with respect to data acquisition and analysis. As a result, studies using super-resolution imaging are typically drawing conclusions from tens of cells and a few experimental conditions tested. We addressed these limitations by developing a high-throughput single-molecule tracking (htSMT) platform for pharmacologic dissection of protein dynamics in living cells at an unprecedented scale (capable of imaging >10

Indexed as

High-Throughput Screening AssaysSingle Molecule ImagingCell Line, TumorDrug DiscoveryDrug InteractionsHumansReceptors, EstrogenReceptors, Estrogencell biologydrug discoveryestrogen receptorhigh-throughput imaginghumanlive-cell imagingphysics of living systemsprotein motionsingle-molecule imaging

Identifiers

PMID39786807
PMCPMC11717362

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.