Evidence map›Paper›PMID 41087374›Full record

ArticleScientific data2025

Computed ECD spectral data for over 10,000 chiral organic small molecules.

Da Long, Zhihao Li, Xin Xu, Chengchun Liu, Hui Zhang, Xiaoyu Cao, Liulin Yang, Xinchang Wang, Fanyang Mo

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

9 authors.

Da Long *State Key Laboratory of Physical Chemistry of Solid Surfaces, School of Electronic Science and Engineering, Innovation Laboratory for Science and Technologies of Energy Materials of Fujian Province (IKKEM) and College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China.
Zhihao Li *South China Advanced Institute for Soft Matter Science and Technology, School of Emergent Soft Matter, South China University of Technology, Guangzhou, 510640, China.
Xin XuState Key Laboratory of Physical Chemistry of Solid Surfaces, School of Electronic Science and Engineering, Innovation Laboratory for Science and Technologies of Energy Materials of Fujian Province (IKKEM) and College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China.
Chengchun LiuSchool of Materials Science and Engineering, Peking University, Beijing, 100871, China.
Hui ZhangState Key Laboratory of Physical Chemistry of Solid Surfaces, School of Electronic Science and Engineering, Innovation Laboratory for Science and Technologies of Energy Materials of Fujian Province (IKKEM) and College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China.
Xiaoyu CaoState Key Laboratory of Physical Chemistry of Solid Surfaces, School of Electronic Science and Engineering, Innovation Laboratory for Science and Technologies of Energy Materials of Fujian Province (IKKEM) and College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China. xcao@xmu.edu.cn.
Liulin YangState Key Laboratory of Physical Chemistry of Solid Surfaces, School of Electronic Science and Engineering, Innovation Laboratory for Science and Technologies of Energy Materials of Fujian Province (IKKEM) and College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China. llyang@xmu.edu.cn.
Xinchang WangState Key Laboratory of Physical Chemistry of Solid Surfaces, School of Electronic Science and Engineering, Innovation Laboratory for Science and Technologies of Energy Materials of Fujian Province (IKKEM) and College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China. xcwang@xmu.edu.cn.ORCID http://orcid.org/0000-0001-6260-9282
Fanyang MoSchool of Materials Science and Engineering, Peking University, Beijing, 100871, China. fmo@pku.edu.cn.ORCID http://orcid.org/0000-0002-4140-3020

Funding

National Natural Science Foundation of China (National Science Foundation of China) No. 22071004, 21933001, 22150013, 22272133, 21971217, 22372139 and 22250004
6 · The paper itself

Abstract

Determining the absolute configuration of chiral molecules is of fundamental importance in the fields of natural products chemistry, asymmetric catalysis, and pharmaceutical development. A widely adopted approach involves the comparison of experimental and theoretical electronic circular dichroism (ECD) spectra, which has proven to be a reliable method for absolute configuration assignment. However, the generation of theoretical ECD spectra via time-dependent density functional theory (TD-DFT) remains the rate-limiting step in this workflow, making its acceleration both essential and challenging. Although recent advances in deep learning offer promising strategies for establishing structure-spectrum relationships and expediting theoretical spectrum prediction, the lack of standardized and comprehensive ECD spectral datasets continues to hinder progress. This study presents the Chiral Molecular Circular Dichroism Spectral (CMCDS) dataset, a systematically structural benchmark dataset that addresses the fragmentation of existing ECD data. Characterized by high standardization, scalability, and broad molecular diversity, CMCDS facilitates deep learning applications in ECD analysis and fosters data-driven discovery of chiral molecules.

Identifiers

PMID41087374
PMCPMC12521594

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Registered trials

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