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Related Experiment Video

Updated: Oct 4, 2025

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin

Published on: March 3, 2021

FragExplorer: GRID-Based Fragment Growing and Replacement.

Simon Cross¹, Gabriele Cruciani²

¹Molecular Discovery, Kinetic Business Centre, Theobald Street, Elstree, Borehamwood, Hertfordshire WD6 4PJ, U.K.

Journal of Chemical Information and Modeling

|February 4, 2022

Summary

FragExplorer aids drug design by identifying optimal molecular fragments for protein binding sites. This software explores vast chemical spaces, accelerating the discovery of novel drug candidates.

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Last Updated: Oct 4, 2025

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin

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Published on: March 3, 2021

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source

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Published on: May 29, 2021

NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode

NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode

Published on: June 4, 2021

Area of Science:

Computational chemistry
Medicinal chemistry
Drug discovery

Background:

Structure-based drug design (SBDD) relies on understanding ligand modifications.
The GRID software pioneered computational approaches to molecular interactions.
Identifying optimal fragments is crucial for lead optimization.

Purpose of the Study:

To develop FragExplorer, a software tool to identify suitable molecular fragments for protein binding sites.
To assist users of the GRID software in exploring chemical modifications of known ligands.
To enable rapid exploration of large chemical spaces for drug design.

Main Methods:

FragExplorer integrates with 3D molecular editors for interactive use.
R-Group Exploration mode identifies and searches for R-group replacements.
Scaffold Exploration mode identifies and searches for scaffold replacements.
Computational speed was optimized, with typical fragment searches taking 20 seconds.

Main Results:

FragExplorer explores chemical spaces up to 10^22 potential molecules.
Demonstrated a 55% overall fragment retrieval rate, increasing to 69% for smaller fragments.
Achieved an ~80% retrieval rate at a 90% substructural match.
Successfully demonstrated application in optimizing known drug molecules and lead compounds.

Conclusions:

FragExplorer significantly enhances structure-based drug design by efficiently identifying optimal molecular fragments.
The software enables rapid exploration of vast chemical diversity for novel drug discovery.
FragExplorer provides a practical tool for lead optimization and exploring structure-activity relationships.