Evidence map›Paper›PMID 41116072›Full record

ArticleEMBO reports2025

Tudor-based proteomic strategy pan-specifically enriches and identifies protein arginine methylation.

Lingzi Lu, Ting Li, Rou Zhang, Yutong Wang, Xiaoping Ye, Yixin Luo, Lingyu Sun, Liang Qi, Zilu Ye, Yang Mao and 1 more

Abstract read
In one paragraph

Article in EMBO reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

  1. Review
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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

11 authors.

Lingzi Lu *State Key Laboratory of Anti-Infective Drug Discovery and Development, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China.ORCID 0009-0006-4479-158X
Ting Li *State Key Laboratory of Anti-Infective Drug Discovery and Development, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China.
Rou Zhang *State Key Laboratory of Anti-Infective Drug Discovery and Development, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China.ORCID 0000-0001-5846-3284
Yutong WangState Key Laboratory of Anti-Infective Drug Discovery and Development, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China.
Xiaoping YeState Key Laboratory of Anti-Infective Drug Discovery and Development, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China.
Yixin LuoState Key Laboratory of Anti-Infective Drug Discovery and Development, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China.
Lingyu SunGuangdong Institute for Drug Control, Guangzhou, China.
Liang QiState Key Laboratory of Anti-Infective Drug Discovery and Development, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China.
Zilu YeState Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou, China. yzl@ism.pumc.edu.cn.ORCID 0000-0001-8829-6579
Yang MaoState Key Laboratory of Anti-Infective Drug Discovery and Development, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China. maoyang3@mail.sysu.edu.cn.ORCID 0000-0002-9674-1158
Yanqiu YuanState Key Laboratory of Anti-Infective Drug Discovery and Development, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China. yuanyq8@mail.sysu.edu.cn.ORCID 0000-0001-8360-4843

Funding

China Postdoctoral Science Foundation (China Postdoctoral Foundation Project) 2025M773561Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences grant no. 2022-I2M-2-004, 2023-I2M-2-005, 2021-I2M-1-061Guangdong Provincial Key Laboratory of Drug Non-clinical Evaluation and Research 2023B1212070029MOST | National Key Research and Development Program of China (NKPs) 2021YFA1200903MOST | National Natural Science Foundation of China (NSFC) 32271497MOST | National Natural Science Foundation of China (NSFC) 92478126MOST | National Natural Science Foundation of China (NSFC) T2450074National Natural Science Foundation of China 22574120Natural Science Foundation of Jiangsu Province BK20240443Non-profit Central Research Institute Fund of the Chinese Academy of Medical Sciences grant no. 2023-RC180-03Suzhou Municipal Key Laboratory SZS2022005
6 · The paper itself

Abstract

Protein arginine methylation is an important post-translational modification (PTM) in eukaryotes, regulating a variety of biological processes. Proteomic profiling of arginine methylation has advanced our understanding of its roles in biology and disease. However, pan-specific enrichment of methylarginine-containing peptides remains challenging. Herein we report a molecular affinity strategy based on the Tudor domain of SMN, a naturally occurring methylarginine reader protein, for comprehensive proteomic profiling of cellular arginine methylation. We demonstrate that the Tudor domain-based approach exhibits broad specificity for proteins harboring mono- or di-methylated arginines, encompassing both RGG/RG-rich and non-RG motifs, facilitating the discovery of novel methylation sites. Using this strategy, we identify asymmetric dimethylarginine (aDMA) in protein eIF3D, an essential component of the eukaryotic translation initiation complex. Biochemical analyses reveal that aDMA modification at R99 of eIF3D plays a regulatory role in protein translation initiation. Our findings establish a generally applicable approach for proteomic profiling of arginine methylation and unveil its novel regulatory role for this modification in eukaryotic protein translation.

Indexed as

ArginineProtein Processing, Post-TranslationalProteomicsEukaryotic Initiation Factor-3HEK293 CellsHumansMethylationArginineEukaryotic Initiation Factor-3N,N-dimethylarginineArginine MethylationeIF3DMolecular Affinity EnrichmentProteomics

Identifiers

PMID41116072
PMCPMC12678802

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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.