Evidence map›Paper›PMID 40234417›Full record

ArticleNature communications2025

A modular artificial intelligence framework to facilitate fluorophore design.

Yuchen Zhu, Jiebin Fang, Shadi Ali Hassen Ahmed, Tao Zhang, Su Zeng, Jia-Yu Liao, Zhongjun Ma, Linghui Qian

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
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  4. Article
  5. Review
  6. Article
  7. Review
  8. AI-Driven Acceleration of Fluorescence Probe Discovery.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  9. Article
  10. Review
  11. Review
  12. 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

8 authors.

Yuchen Zhu *Institute of Drug Metabolism and Pharmaceutical Analysis, Research Center for Clinical Pharmacy, College of Pharmaceutical Sciences, State Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, 310058, China.ORCID http://orcid.org/0009-0003-6553-1419
Jiebin Fang *Hainan Institute of Zhejiang University, Sanya, 572025, China.ORCID http://orcid.org/0000-0002-0748-770X
Shadi Ali Hassen AhmedInstitute of Drug Metabolism and Pharmaceutical Analysis, Research Center for Clinical Pharmacy, College of Pharmaceutical Sciences, State Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, 310058, China.ORCID http://orcid.org/0000-0003-4772-9731
Tao ZhangInstitute of Intelligent Innovation, Henan Academy of Sciences, Zhengzhou, 451162, China.
Su ZengInstitute of Drug Metabolism and Pharmaceutical Analysis, Research Center for Clinical Pharmacy, College of Pharmaceutical Sciences, State Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, 310058, China.
Jia-Yu LiaoInstitute of Drug Metabolism and Pharmaceutical Analysis, Research Center for Clinical Pharmacy, College of Pharmaceutical Sciences, State Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, 310058, China. jyliao@zju.edu.cn.ORCID http://orcid.org/0000-0001-6847-4825
Zhongjun MaHainan Institute of Zhejiang University, Sanya, 572025, China. mazj@zju.edu.cn.ORCID http://orcid.org/0000-0002-5825-5095
Linghui QianInstitute of Drug Metabolism and Pharmaceutical Analysis, Research Center for Clinical Pharmacy, College of Pharmaceutical Sciences, State Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, 310058, China. lhqian@zju.edu.cn.ORCID http://orcid.org/0000-0001-7889-1489

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82273887National Natural Science Foundation of China (National Science Foundation of China) 82473881Natural Science Foundation of Zhejiang Province (Zhejiang Provincial Natural Science Foundation) LTZ22B020001
6 · The paper itself

Abstract

Fluorescence imaging, indispensable for fundamental research and clinical practice, has been driven by advances in fluorophores. Despite fast growth over the years, many available fluorophores suffer from insufficient performances, and their development is highly dependent on trial-and-error experiments due to subtle structure-property effects and complicated solvent effects. Herein, FLAME (FLuorophore design Acceleration ModulE), an artificial intelligence framework with a modular architecture, is built by integrating open-source databases, multiple prediction models, and the latest molecule generators to facilitate fluorophore design. First, we constructed the largest open-source fluorophore database to date (FluoDB), containing 55,169 fluorophore-solvent pairs. Then FLSF (FLuorescence prediction with fluoroScaFfold-driven model) with a domain-knowledge-derived fingerprint for characterizing fluorescent scaffolds (called fluoroscaffold) was designed and demonstrated to predict optical properties quickly and accurately, whose reliability and potential have been verified via molecular and atomistic interpretability analysis. Further, a molecule generator was incorporated to provide new compounds with desired fluorescence. Representative 3,4-oxazole-fused coumarins were synthesized and evaluated, creating an unreported compound with bright fluorescence.

Identifiers

PMID40234417
PMCPMC12000321

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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.