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Updated: Jan 8, 2026

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Published on: December 25, 2021

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

Weiyu Zhou^1,2, Dongliang Ke^1,2, Zhihan Zhang^1,2

¹State Key Laboratory of Petroleum Molecular and Process Engineering, Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200062, China.

Journal of Chemical Information and Modeling

|December 19, 2025

Summary

This summary is machine-generated.

We developed qMol, a novel online platform for searching accessible molecules using a fragment-based reduced graph representation. This tool aids drug discovery by enabling flexible searches for lead identification and analogue exploration.

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Area of Science:

Computational Chemistry
Medicinal Chemistry
Bioinformatics

Background:

Accelerating lead identification is crucial in drug discovery.
Existing molecular database search tools can be limited in flexibility.
Fragment-based approaches offer a promising avenue for molecular representation.

Purpose of the Study:

Introduce qMol, an online platform for searching accessible molecules.
Enable flexible molecular searches using a fragment-based reduced graph representation.
Support analogue identification in drug discovery through precise control over molecular topology and features.

Main Methods:

Molecules are represented as chemically meaningful reduced graphs.
Fragments serve as nodes, and their connections as edges in the graph representation.
The qMol platform allows users to retrieve exact or varied reduced graphs.

Main Results:

qMol provides precise control over global topology and local chemical features.
Users can apply fragment-level constraints for targeted searches.
The platform facilitates efficient exploration of chemical databases.

Conclusions:

qMol is a valuable resource for medicinal researchers.
The fragment-based reduced graph representation enhances molecular search capabilities.
qMol supports efficient lead identification and analogue exploration in drug discovery.