Evidence map›Paper›PMID 36268127›Full record

ArticleACS pharmacology & translational science2022

Precision Targeting of Endogenous Epidermal Growth Factor Receptor (EGFR) by Structurally Aligned Dual-Modifier Labeling.

Ivan de Jesus Salazar-Estrada, Karthik Shantharam Kamath, Fei Liu

Open access · greenAbstract read
In one paragraph

Article in ACS pharmacology & translational science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 49% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

3 authors at 2 institutions in 1 country.

Ivan de Jesus Salazar-EstradaSchool of Natural Sciences, Macquarie University, Sydney, NSW 2109, Australia.
Karthik Shantharam KamathAustralian Proteome Analysis Facility, Macquarie University, Sydney, NSW 2109, Australia.
Fei LiuSchool of Natural Sciences, Macquarie University, Sydney, NSW 2109, Australia.ORCID https://orcid.org/0000-0002-2175-6670
Macquarie University · AUAGRF Ltd · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Covalent modification of endogenous proteins by chemical probes is used for proteome-wide profiling of cellular protein function and drug discovery. However, probe selectivity in the complex cellular environment is a challenge, and new probes with better target selectivity are continuously needed. On the basis of the success of monocovalent activity-based and reactivity-based probes, an approach of structurally aligned dual-modifier labeling (SADL) was investigated here on its potential in improving target precision. Two reactive groups, based on the acrylamide and NHS ester chemistry, were linked with structural alignment to be under the same anilinoquinazoline ligand-directive for targeting the epidermal growth factor receptor (EGFR) protein kinase as the model system for proteome-wide profiling. The SADL approach was compared with its monocovalent precursors in a label-free MaxLFQ workflow using MDA-MB-468 triple negative breast cancer cells. The dual-modifier probe consistently showed labeling of EGFR with improved precision over both monocovalent precursors under various controls. The workflow also labeled endogenous USP34 and PKMYT1 with high selectivity. Precision labeling with two covalent modifiers under a common ligand directive may broaden protein identification opportunities in the native environment to complement genetic and antibody-based approaches for elucidating biological or disease mechanisms, as well as accelerating drug target discovery.

Identifiers

PMID36268127
PMCPMC9578136
OpenAlexW4296347310

What OpenQuestion holds

Textmetadata
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.