Evidence map›Paper›PMID 41298428›Full record

ArticleNature communications2025

A virtual platform for automated hybrid organic-enzymatic synthesis planning.

Xiaorui Wang, Xiaodan Yin, Xujun Zhang, Huifeng Zhao, Shukai Gu, Zhenxing Wu, Odin Zhang, Wenjia Qian, Yuansheng Huang, Yuquan Li and 6 more

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

16 authors.

Xiaorui Wang *College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, P.R. China.ORCID http://orcid.org/0000-0001-6893-2013
Xiaodan Yin *College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, P.R. China.
Xujun ZhangCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, P.R. China.
Huifeng ZhaoCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, P.R. China.
Shukai GuCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, P.R. China.
Zhenxing WuCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, P.R. China.ORCID http://orcid.org/0000-0002-1060-5957
Odin ZhangCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, P.R. China.
Wenjia QianCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, P.R. China.
Yuansheng HuangCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, P.R. China.
Yuquan LiState Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, P.R. China.ORCID http://orcid.org/0000-0003-2756-0449
Dejun JiangXiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan, P.R. China.ORCID http://orcid.org/0000-0002-2035-5074
Mingyang WangCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, P.R. China.ORCID http://orcid.org/0009-0001-2779-5769
Huanxiang LiuFaculty of Applied Sciences, Macao Polytechnic University, Macao, P.R. China.ORCID http://orcid.org/0000-0002-9284-3667
Xiaojun YaoFaculty of Applied Sciences, Macao Polytechnic University, Macao, P.R. China. xjyao@mpu.edu.mo.
Chang-Yu HsiehCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, P.R. China. kimhsieh@zju.edu.cn.ORCID http://orcid.org/0000-0002-6242-4218
Tingjun HouCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, P.R. China. tingjunhou@zju.edu.cn.ORCID http://orcid.org/0000-0001-7227-2580

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The integration of organic synthesis with enzymatic catalysis offers a promising route toward efficient and sustainable construction of complex molecules. While organic synthesis enables diverse transformations, enzymatic catalysis enhances stereoselectivity under mild conditions, improving cost-effectiveness and environmental impact. However, current enzymatic synthesis planning algorithms face challenges in formulating robust hybrid organic-enzymatic strategies. Key issues include the difficulty in devising hybrid planning approaches and the reliance on template-based enzyme recommendations, which limits their adaptability across diverse scenarios. Here we show ChemEnzyRetroPlanner, an open-source hybrid synthesis planning platform that combines organic and enzymatic strategies with AI-driven decision-making. The platform features advanced computational modules, including hybrid retrosynthesis planning, reaction condition prediction, plausibility evaluation, enzymatic reaction identification, enzyme recommendation, and in silico validation of enzyme active sites. A central innovation is the RetroRollout* search algorithm, which outperforms existing tools in planning synthesis routes for organic compounds and natural products across multiple datasets. ChemEnzyRetroPlanner provides an intuitive graphical interface and programmatic APIs for scalability, while leveraging the chain-of-thought strategy and the Llama3.1 model to autonomously activate hybrid synthesis strategies for diverse scenarios. The results indicate that this fully automated, open-source system holds potential value for improving the efficiency and sustainability of molecular synthesis.

Indexed as

Chemistry Techniques, SyntheticEnzymesOrganic ChemicalsAlgorithmsBiocatalysisBiological ProductsCatalytic DomainSoftwareBiological ProductsEnzymesOrganic Chemicals

Identifiers

PMID41298428
PMCPMC12686493

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.