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Related Experiment Video

Updated: Jun 3, 2026

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Published on: December 25, 2021

Intuitive patent Markush structure visualization tool for medicinal chemists.

Wei Deng¹, Steven J Berthel, W Venus So

¹Roche, 340 Kingsland Street, Nutley, New Jersey 07110, United States.

Journal of Chemical Information and Modeling

|March 9, 2011

Summary

This summary is machine-generated.

Chemists can now easily visualize complex chemical structures in patents using MarVis (Markush Visualization) software. This tool aids in understanding chemical space and identifying specific R-groups within generic structures.

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Area of Science:

Medicinal Chemistry
Computational Chemistry
Intellectual Property Law

Background:

Markush structures are prevalent in chemical and pharmaceutical patents, representing generic chemical entities.
The complexity of Markush structures hinders straightforward analysis of the associated chemical space.
Existing methods for analyzing Markush structures are often inadequate for comprehensive exploration.

Purpose of the Study:

To introduce MarVis, a novel application package designed for visualizing Markush structures in patents.
To provide chemists with a tool for better understanding and analyzing the chemical space defined by Markush structures.
To facilitate the identification of substructures and R-groups within patent claims.

Main Methods:

Development of the MarVis application package for Markush structure visualization.
Implementation of a reporting feature to display Markush structures, query substructures, and R-group tables.
Integration of an interactive interface for exploring and zooming within the chemical space.
Utilization of Simplified Molecular Input Line Entry System (SMILES) with extensions for data representation.

Main Results:

MarVis successfully visualizes complex Markush structures from chemical patents.
The software generates comprehensive reports including substructure identification and R-group tables.
The interactive interface enables efficient exploration and subset identification within the chemical space.
SMILES-based representation facilitates diverse patent Markush structure studies.

Conclusions:

MarVis offers a significant advancement in the analysis of chemical and pharmaceutical patent literature.
The tool enhances chemists' ability to understand and navigate the chemical space defined by Markush structures.
MarVis is valuable for intellectual property analysis, drug discovery, and chemical research.