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Updated: May 10, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Similarity searching for potent compounds using feature selection.

Martin Vogt¹, Jürgen Bajorath

¹LIMES Program Unit Chemical Biology and Medicinal Chemistry, Department of Life Science Informatics, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstrasse 2, D-53113 Bonn, Germany.

Journal of Chemical Information and Modeling

|July 2, 2013

Summary

This summary is machine-generated.

This study introduces a new feature selection method for chemical similarity searching. It helps find potent compounds more effectively by prioritizing important molecular features for better recall.

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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
Cheminformatics

Background:

Traditional similarity searching in drug discovery often overlooks compound potency.
Existing methods calculate molecular similarity without using potency as a direct search parameter.

Purpose of the Study:

To develop a feature selection approach for fingerprint similarity searching.
To enhance compound recall and prioritize the detection of potent compounds.

Main Methods:

A novel feature selection method was developed for fingerprint-based similarity searching.
The method identifies fingerprint features that are indicative of compound potency and high recall.
Training examples were used to select optimal feature subsets.

Main Results:

The new method effectively maximizes compound recall.
Potent compounds are preferentially detected, even when reference compounds have moderate or low potency.
Small sets of simple chemical features were found to deliver high search performance.

Conclusions:

The developed feature selection method improves the efficiency of similarity searching for potent compounds.
This approach offers a valuable tool for drug discovery by focusing on potency and recall.
Utilizing selected chemical features enhances the identification of high-value drug candidates.