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Updated: May 17, 2026

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Published on: April 18, 2019

Rules for identifying potentially reactive or promiscuous compounds.

Robert F Bruns¹, Ian A Watson

¹Lilly Research Laboratories, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, Indiana 46285, USA. bruns_robert_f@lilly.com

Journal of Medicinal Chemistry

|October 16, 2012

Summary

This summary is machine-generated.

This study developed 275 rules to identify and remove interfering compounds from biological screening sets, improving data reliability. A biological promiscuity index and nuisance list further refine compound selection for drug discovery.

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Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

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Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

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Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

Published on: June 6, 2025

Area of Science:

Medicinal Chemistry
Assay Development
Computational Chemistry

Background:

Biological assays are crucial for drug discovery but can be confounded by interfering compounds.
Identifying and removing these problematic compounds is essential for reliable screening data.

Purpose of the Study:

To describe a comprehensive set of rules and methods for identifying and removing compounds that interfere with biological assays.
To improve the quality and reliability of compound screening data in drug discovery programs.

Main Methods:

Development of 275 structural rules to flag reactive, interfering, unstable, or non-druggable compounds.
Creation of a biological promiscuity index based on the number of gene subfamilies a compound affects.
Establishment of a 'nuisance list' to identify interfering compounds not caught by substructure rules, often due to occult contaminants.

Main Results:

A robust set of 275 rules was established over 18 years, validated by medicinal chemists.
The biological promiscuity index effectively flagged compounds with broad, potentially artefactual activity.
The nuisance list successfully identified interfering compounds missed by substructure analysis, highlighting the issue of occult contaminants.

Conclusions:

The developed rules and associated methods significantly enhance the ability to identify and remove problematic compounds from screening libraries.
These strategies improve the accuracy of biological assay results and streamline the drug discovery process.
Addressing both structural and contaminant-based interference is critical for robust compound profiling.