Evidence map›Paper›PMID 40203090›Full record

ArticleScience advances2025

Discovery of diverse and high-quality mRNA capping enzymes through a language model-enabled platform.

Tianze Wang, Bowen R Qin, Sihong Li, Zimo Wang, Xuejian Li, Yuanxu Jiang, Chenrui Qin, Qi Ouyang, Chunbo Lou, Long Qian

Abstract read
In one paragraph

Article in Science advances, 2025. 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. Review
  2. Article
  3. 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

10 authors.

Tianze WangCenter for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.ORCID 0009-0003-5280-369X
Bowen R QinCenter for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.ORCID 0009-0004-5298-1506
Sihong LiCenter for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.ORCID 0000-0001-6411-5323
Zimo WangCenter for Cell and Gene Circuit Design, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.ORCID 0009-0008-7256-2535
Xuejian LiBeyond Flux Technology Co. Ltd., Beijing 100000, China.
Yuanxu JiangCenter for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.
Chenrui QinInstitute for Advanced Study in Physics, Zhejiang University, Hangzhou 310058, China.
Qi OuyangInstitute for Advanced Study in Physics, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0003-1585-7368
Chunbo LouCenter for Cell and Gene Circuit Design, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.ORCID 0000-0002-7941-6038
Long QianCenter for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.ORCID 0000-0003-3728-7917

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mining and expanding high-quality genetic parts for synthetic biology and bioengineering are urgent needs in the research and development of next-generation biotechnology. However, gene mining has relied on sequence homology or ample expert knowledge, which fundamentally limits the establishment of a comprehensive genetic part catalog. In this work, we propose SYMPLEX (synthetic biological part mining platform by large language model-enabled knowledge extraction), a universal gene-mining platform based on large language models. We applied SYMPLEX to mine enzymes responsible for messenger RNA (mRNA) capping, a key process in eukaryotic posttranscriptional modification, and obtained thousands of diverse candidates with traceable evidence from biomedical literature and databases. Of the 46 experimentally tested integral capping enzyme candidates, 14 demonstrated in vivo cross-species capping activity, and 2 displayed superior in vitro activity over the commercial vaccinia capping enzymes currently used in mRNA vaccine production. SYMPLEX provides a distinct paradigm for functional gene mining and offers powerful tools to facilitate knowledge discovery in fundamental research.

Indexed as

NucleotidyltransferasesRNA CapsRNA, MessengerComputational BiologyData MiningHumansNucleotidyltransferasesRNA CapsRNA, Messenger

Identifiers

PMID40203090
PMCPMC11980835

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.