Evidence map›Paper›PMID 36382280›Full record

ArticleChemical science2022

Highly effective identification of drug targets at the proteome level by pH-dependent protein precipitation.

Xiaolei Zhang, Keyun Wang, Sijin Wu, Chengfei Ruan, Kejia Li, Yan Wang, He Zhu, Xiaoyan Liu, Zhen Liu, Guohui Li and 2 more

Open access · diamondAbstract read
In one paragraph

Article in Chemical science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.7field-weighted citation impact, top 4% 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

15 citing papers in PubMed, 34 citations in OpenAlex.

  1. Review
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  13. Stability-based approaches in chemoproteomics.Expert reviews in molecular medicine · 2024
    Review
  14. Article
  15. 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

12 authors at 2 institutions in 1 country.

Xiaolei ZhangCAS Key Laboratory of Separation Sciences for Analytical Chemistry, National Chromatographic R & A Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences Dalian 116023 China mingliang@dicp.ac.cn ghli@dicp.ac.cn.ORCID https://orcid.org/0000-0002-2372-2706
Keyun WangCAS Key Laboratory of Separation Sciences for Analytical Chemistry, National Chromatographic R & A Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences Dalian 116023 China mingliang@dicp.ac.cn ghli@dicp.ac.cn.
Sijin WuCAS Key Laboratory of Separation Sciences for Analytical Chemistry, National Chromatographic R & A Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences Dalian 116023 China mingliang@dicp.ac.cn ghli@dicp.ac.cn.
Chengfei RuanCAS Key Laboratory of Separation Sciences for Analytical Chemistry, National Chromatographic R & A Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences Dalian 116023 China mingliang@dicp.ac.cn ghli@dicp.ac.cn.
Kejia LiCAS Key Laboratory of Separation Sciences for Analytical Chemistry, National Chromatographic R & A Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences Dalian 116023 China mingliang@dicp.ac.cn ghli@dicp.ac.cn.
Yan WangCAS Key Laboratory of Separation Sciences for Analytical Chemistry, National Chromatographic R & A Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences Dalian 116023 China mingliang@dicp.ac.cn ghli@dicp.ac.cn.
He ZhuCAS Key Laboratory of Separation Sciences for Analytical Chemistry, National Chromatographic R & A Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences Dalian 116023 China mingliang@dicp.ac.cn ghli@dicp.ac.cn.
Xiaoyan LiuCAS Key Laboratory of Separation Sciences for Analytical Chemistry, National Chromatographic R & A Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences Dalian 116023 China mingliang@dicp.ac.cn ghli@dicp.ac.cn.
Zhen LiuCAS Key Laboratory of Separation Sciences for Analytical Chemistry, National Chromatographic R & A Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences Dalian 116023 China mingliang@dicp.ac.cn ghli@dicp.ac.cn.
Guohui LiCAS Key Laboratory of Separation Sciences for Analytical Chemistry, National Chromatographic R & A Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences Dalian 116023 China mingliang@dicp.ac.cn ghli@dicp.ac.cn.
Lianghai HuCenter for Supramolecular Chemical Biology, State Key Laboratory of Supramolecular Structure and Materials, School of Life Sciences, Jilin University Changchun 130012 China lianghaihu@jlu.edu.cn.ORCID https://orcid.org/0000-0002-1246-6524
Mingliang YeCAS Key Laboratory of Separation Sciences for Analytical Chemistry, National Chromatographic R & A Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences Dalian 116023 China mingliang@dicp.ac.cn ghli@dicp.ac.cn.ORCID https://orcid.org/0000-0002-5872-9326
Dalian Institute of Chemical Physics · CNJilin University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fully understanding the target spaces of drugs is essential for investigating the mechanism of drug action and side effects, as well as for drug discovery and repurposing. In this study, we present an energetics-based approach, termed pH-dependent protein precipitation (pHDPP), to probe the ligand-induced protein stability shift for proteome-wide drug target identification. We demonstrate that pHDPP works for a diverse array of ligands, including a folate derivative, an ATP analog, a CDK inhibitor and an immunosuppressant, enabling highly specific identification of target proteins from total cell lysates. This approach is compared to thermal and solvent-induced denaturation approaches with a pan-kinase inhibitor as the model drug, demonstrating its high sensitivity and high complementarity to other approaches. Dihydroartemisinin (DHA), a dominant derivative of artemisinin to treat malaria, is known to have an extraordinary effect on the treatment of various cancers. However, the anti-tumor mechanisms remain unknown. pHDPP was applied to reveal the target space of DHA and 45 potential target proteins were identified. Pathway analysis indicated that these target proteins were mainly involved in metabolism and apoptosis pathways. Two cancer-related target proteins, ALDH7A1 and HMGB1, were validated by structural simulation and AI-based target prediction methods. And they were further validated to have strong affinity to DHA by using cellular thermal shift assay (CETSA). In summary, pHDPP is a powerful tool to construct the target protein space to reveal the mechanism of drug action and would have broad application in drug discovery studies.

Identifiers

PMID36382280
PMCPMC9629037
OpenAlexW4309242869

What OpenQuestion holds

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Registered trials

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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.