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Related Experiment Video

Updated: Jan 19, 2026

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

Scaffold-Based Analytics: Enabling Hit-to-Lead Decisions by Visualizing Chemical Series Linked across Large Datasets.

Deepak Bandyopadhyay¹, Constantine Kreatsoulas¹, Pat G Brady¹

¹GlaxoSmithKline , 1250 S. Collegeville Rd , Collegeville , Pennsylvania 19426 , United States.

Journal of Chemical Information and Modeling

|September 19, 2019

Summary

This summary is machine-generated.

This study introduces a novel method for visualizing and navigating large screening datasets by annotating molecules with their scaffolds. This approach aids in hit triage and lead optimization by revealing chemical space overlaps and structure-activity relationships.

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Area of Science:

Medicinal Chemistry
Cheminformatics
Data Visualization

Background:

Large-scale screening datasets are crucial for drug discovery but present challenges in visualization and navigation.
Existing methods may lead to bias towards potent molecules, neglecting broader chemical space coverage.

Purpose of the Study:

To develop an intuitive method for visualizing and navigating large screening datasets.
To enhance hit triage and lead progression by leveraging scaffold information and structure-activity relationships.
To address bias in hit selection by promoting exploration of diverse chemical space.

Main Methods:

Annotating screening data with all constituent molecular scaffolds.
Developing a Spotfire visualization coupled with fuzzy clustering based on scaffold decomposition.
Mapping structure-activity relationships onto scaffolds for navigation across related molecules.

Main Results:

The scaffold-based visualization and fuzzy clustering facilitate intuitive navigation of large, diverse screening datasets.
Aggregate scaffold parameters enable data merging across datasets and informed progression decisions.
The method reveals overlaps, prioritizes hits, highlights tractable series, and facilitates combining hit aspects.

Conclusions:

The integrated workflow of visualization, fuzzy clustering, and scaffold annotation provides an effective approach for exploring screening data.
This method enables effortless navigation between structurally related molecules, enriching lead populations.
The approach complements established methods by promoting broader chemical space coverage and informed decision-making in drug discovery.