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Updated: Dec 7, 2025

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

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SMARTS.plus - A Toolbox for Chemical Pattern Design.

Christiane Ehrt¹, Bennet Krause¹, Robert Schmidt¹

¹Universität Hamburg, ZBH - Center for Bioinformatics, Bundesstraße 43, 20146, Hamburg, Germany.

Molecular Informatics

|September 30, 2020

Summary

This summary is machine-generated.

Chemists can now easily filter screening libraries using novel SMARTS patterns. The SMARTS.plus web server simplifies the creation and application of these chemical patterns, addressing challenges with Pan-Assay Interference Compounds.

Keywords:

Chemical Patterns Filter Collections Medicinal Chemistry SMARTS Comparison SMARTS Visualization

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Last Updated: Dec 7, 2025

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Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

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Published on: June 6, 2025

Area of Science:

Medicinal Chemistry
Cheminformatics
Computational Chemistry

Background:

Increasing publications on Pan-Assay Interference Compounds (PAICs) necessitate better filtering methods for chemical screening libraries.
Existing chemical pattern languages like SMARTS can be complex, hindering accessibility for many chemists.
There is a growing need for user-friendly tools to manage and analyze chemical patterns.

Purpose of the Study:

To introduce the SMARTS.plus web server, a novel toolbox for creating, editing, and analyzing chemical patterns.
To demonstrate the utility of SMARTS.plus for deriving specific SMARTS patterns to filter problematic compounds.
To enable chemists with limited SMARTS experience to effectively manage screening libraries.

Main Methods:

Development of a suite of software tools for chemical pattern manipulation over the past decade.
Integration of these tools into the user-friendly SMARTS.plus web server.
Showcasing the application of the web server for filtering frequent hitters from screening libraries.

Main Results:

The SMARTS.plus web server provides an accessible platform for chemical pattern analysis.
Researchers can generate custom SMARTS patterns for filtering PAICs and frequent hitters rapidly.
The tools require minimal prior experience with the SMARTS language.

Conclusions:

The SMARTS.plus web server significantly lowers the barrier to entry for utilizing advanced chemical pattern filtering.
This resource empowers researchers to improve the quality and efficiency of their screening libraries.
The platform facilitates the identification and removal of problematic compounds in drug discovery pipelines.