Evidence map›Paper›PMID 35969791›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

Small molecule photocatalysis enables drug target identification via energy transfer.

Aaron D Trowbridge, Ciaran P Seath, Frances P Rodriguez-Rivera, Beryl X Li, Barbara E Dul, Adam G Schwaid, Benito F Buksh, Jacob B Geri, James V Oakley, Olugbeminiyi O Fadeyi and 7 more

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed
10.2field-weighted citation impact, top 1% of its field
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

66 citing papers in PubMed, 99 citations in OpenAlex.

  1. Review
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  8. 2-Alkyl Furans Undergo Radiolytic Oxidative Protein Cross-Linking.Journal of the American Chemical Society · 2026
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  9. Review
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  11. AbioRxiv : the preprint server for biology · 2026
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  14. B(COrganic letters · 2026
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6 more citing papers are in PubMed but not listed here.

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

17 authors at 2 institutions in 1 country.

Aaron D TrowbridgeMerck Center for Catalysis, Princeton University, Princeton, NJ 08544.
Ciaran P SeathMerck Center for Catalysis, Princeton University, Princeton, NJ 08544.
Frances P Rodriguez-RiveraDiscovery Chemistry, Merck & Co., Inc., Kenilworth, NJ 07033.
Beryl X LiMerck Center for Catalysis, Princeton University, Princeton, NJ 08544.
Barbara E DulDepartment of Chemistry, Princeton University, Princeton, NJ 08544.
Adam G SchwaidDiscovery Chemistry, Merck & Co., Inc., Boston, MA 02115.
Benito F BukshMerck Center for Catalysis, Princeton University, Princeton, NJ 08544.
Jacob B GeriMerck Center for Catalysis, Princeton University, Princeton, NJ 08544.
James V OakleyMerck Center for Catalysis, Princeton University, Princeton, NJ 08544.ORCID 0000-0003-4774-5205
Olugbeminiyi O FadeyiMerck Exploratory Science Center, Merck & Co., Inc., Cambridge, MA 02141.
Rob C OslundMerck Exploratory Science Center, Merck & Co., Inc., Cambridge, MA 02141.
Keun Ah RyuMerck Exploratory Science Center, Merck & Co., Inc., Cambridge, MA 02141.
Cory WhiteMerck Exploratory Science Center, Merck & Co., Inc., Cambridge, MA 02141.
Tamara Reyes-RoblesMerck Exploratory Science Center, Merck & Co., Inc., Cambridge, MA 02141.
Paul TawaPharmacology, Merck & Co., Inc., Kenilworth, NJ 07033.
Dann L ParkerDiscovery Chemistry, Merck & Co., Inc., Kenilworth, NJ 07033.
David W C MacMillanMerck Center for Catalysis, Princeton University, Princeton, NJ 08544.
Merck & Co., Inc., Rahway, NJ, USA (United States) · USPrinceton University · US

Funding

Photoredox Catalysis Applications in Organometallics and Chemical BiologyR35GM134897 · NIGMS · PRINCETON UNIVERSITY · PI David W MacMillan · 2020 to 2026
$6.3M
Photoredox-Enabled Applications of Primary Amines as Alkylating ReagentsF32GM133133 · NIGMS · PRINCETON UNIVERSITY · PI GERI, JACOB · 2019 to 2020
$123k
NIGMS NIH HHS F32 GM133133NIGMS NIH HHS R35 GM134897
6 · The paper itself

Abstract

Over half of new therapeutic approaches fail in clinical trials due to a lack of target validation. As such, the development of new methods to improve and accelerate the identification of cellular targets, broadly known as target ID, remains a fundamental goal in drug discovery. While advances in sequencing and mass spectrometry technologies have revolutionized drug target ID in recent decades, the corresponding chemical-based approaches have not changed in over 50 y. Consigned to outdated stoichiometric activation modes, modern target ID campaigns are regularly confounded by poor signal-to-noise resulting from limited receptor occupancy and low crosslinking yields, especially when targeting low abundance membrane proteins or multiple protein target engagement. Here, we describe a broadly general platform for photocatalytic small molecule target ID, which is founded upon the catalytic amplification of target-tag crosslinking through the continuous generation of high-energy carbene intermediates via visible light-mediated Dexter energy transfer. By decoupling the reactive warhead tag from the small molecule ligand, catalytic signal amplification results in unprecedented levels of target enrichment, enabling the quantitative target and off target ID of several drugs including (+)-JQ1, paclitaxel (Taxol), dasatinib (Sprycel), as well as two G-protein-coupled receptors-ADORA2A and GPR40.

Indexed as

Drug Delivery SystemsEnergy TransferProteomicsDrug DiscoveryMass Spectrometryphotocatalysisproteomicstarget identification

Identifiers

PMID35969791
PMCPMC9407219
OpenAlexW4291804711

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.