Evidence map›Paper›PMID 37917986›Full record

ReviewJournal of proteome research2023

Automation to Enable High-Throughput Chemical Proteomics.

Zongtao Lin, Joanna Gongora, Xingyu Liu, Yixuan Xie, Chenfeng Zhao, Dongwen Lv, Benjamin A Garcia

Abstract readReview
In one paragraph

Review in Journal of proteome research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. StageTip: a little giant unveiling the potential of mass spectrometry-based proteomics.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2025
    Review
  4. Review
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

7 authors.

Zongtao LinDepartment of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, Missouri 63110, United States.
Joanna GongoraDepartment of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, Missouri 63110, United States.
Xingyu LiuDepartment of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, Missouri 63110, United States.
Yixuan XieDepartment of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, Missouri 63110, United States.ORCID 0000-0002-8512-6053
Chenfeng ZhaoMcKelvey School of Engineering, Washington University in St. Louis, St. Louis, Missouri 63110, United States.
Dongwen LvDepartment of Biochemistry and Structural Biology and Center for Innovative Drug Discovery, School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas 78229, United States.
Benjamin A GarciaDepartment of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, Missouri 63110, United States.ORCID 0000-0002-2306-1207

Funding

Shared Resources Core 2: Quantitative Proteomics CoreP01CA196539 · NCI · ROCKEFELLER UNIVERSITY · PI MUIR, TOM · 2015 to 2024
$17.6M
Viral modulation of epitranscriptomic mechanismsR01AI118891 · NIAID · WASHINGTON UNIVERSITY · PI GARCIA, BENJAMIN A, WEITZMAN, MATTHEW D. · 2015 to 2025
$5.4M
Quantitative mass spectrometry for comprehending epigenetic mechanisms in a new underlying neurological developmental disorderR01HD106051 · NICHD · WASHINGTON UNIVERSITY · PI Benjamin A Garcia · 2022 to 2026
$2.6M
A Mass Spectrometry Approach to the Genetic and Epigenetic Mechanisms Controlling Neuronal IdentityR01NS111997 · NINDS · WEILL MEDICAL COLL OF CORNELL UNIV · PI DAHMANE, NADIA, GARCIA, BENJAMIN A · 2020 to 2024
$2.6M
NCI NIH HHS P01 CA196539NIAID NIH HHS R01 AI118891NICHD NIH HHS R01 HD106051NINDS NIH HHS R01 NS111997
6 · The paper itself

Abstract

Chemical proteomics utilizes small-molecule probes to covalently engage with their interacting proteins. Since chemical probes are tagged to the active or binding sites of functional proteins, chemical proteomics can be used to profile protein targets, reveal precise binding sites/mechanisms, and screen inhibitors competing with probes in a biological context. These capabilities of chemical proteomics have great potential to enable discoveries of both drug targets and lead compounds. However, chemical proteomics is limited by the time-consuming bottleneck of sample preparations, which are processed manually. With the advancement of robotics and artificial intelligence, it is now possible to automate workflows to make chemical proteomics sample preparation a high-throughput process. An automated robotic system represents a major technological opportunity to speed up advances in proteomics, open new frontiers in drug target discovery, and broaden the future of chemical biology.

Indexed as

Artificial IntelligenceProteomicsAutomationDrug DiscoveryProteinsProteinsartificial intelligenceautomationchemical proteomicshigh-throughputroboticssample preparation

Identifiers

PMID37917986
PMCPMC11037874

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.