qMol: A Web Server for Efficient Molecular Queries Using Fragment-Based Reduced Graphs

Computational tools for searching molecular databases accelerate lead identification in drug discovery. In this work, we introduce qMol, an online platform designed to enable the search for accessible molecules using a fragment-based reduced graph representation, wherein molecules are represented as chemically meaningful reduced graphs with fragments as nodes and their connections as edges. qMol enables flexible molecular searches by allowing users to retrieve exact or varied reduced graphs and apply fragment-level constraints, providing precise control over global topology and local chemical features to support analogue identification in drug discovery. We hope that qMol will be a useful resource for medicinal researchers to efficiently explore chemical databases. qMol is publicly available and can be accessed at https://qmol.xundrug.cn.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2025-12-19
DOI
https://doi.org/10.1021/acs.jcim.5c02195
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

qMol: A Web Server for Efficient Molecular Queries Using Fragment-Based Reduced Graphs

Zhihan Zhang, Xiaolin Pan, Yi Wu, Dongliang Ke et al.
Journal of Chemical Information and Modeling
Computational Drug Discovery Methods
article

qMol: A Web Server for Efficient Molecular Queries Using Fragment-Based Reduced Graphs

Zhihan Zhang, Xiaolin Pan, Yi Wu, Dongliang Ke, Kun Zhang, Changge Ji, Xingyu Wang, Cheqing Jin, Xudong Xiao, Weiyu Zhou
article en

Abstract

Computational tools for searching molecular databases accelerate lead identification in drug discovery. In this work, we introduce qMol, an online platform designed to enable the search for accessible molecules using a fragment-based reduced graph representation, wherein molecules are represented as chemically meaningful reduced graphs with fragments as nodes and their connections as edges. qMol enables flexible molecular searches by allowing users to retrieve exact or varied reduced graphs and apply fragment-level constraints, providing precise control over global topology and local chemical features to support analogue identification in drug discovery. We hope that qMol will be a useful resource for medicinal researchers to efficiently explore chemical databases. qMol is publicly available and can be accessed at https://qmol.xundrug.cn.

Journal of Chemical Information and ModelingVol. 66(1)
New York University Shanghai (CN), Key Laboratory of Guangdong Province (CN), East China Normal University (CN)
Openalex Percentile: Top 60%
Computational Drug Discovery Methods
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qMol: A Web Server for Efficient Molecular Queries Using Fragment-Based Reduced Graphs — Zhihan Zhang, Xiaolin Pan, et al. · Journal of Chemical Information and Modeling (2025) | TGRS Research Map | TGRS