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Identification and Application of Antitarget Activity Hotspots to Guide Compound Optimization
Gerhard Hessler1, Hans Matter2, Friedemann Schmidt2
1R&D, LGCR, Structure, Design and Informatics, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Building G838, D-65926 Frankfurt am Main, Germany phone/fax: ++49-69-305-40098. Gerhard.Hessler@sanofi-aventis.com.
Molecular Informatics
|July 29, 2016
Summary
This study introduces a novel method to identify and utilize antitarget activity hotspots for drug development. This approach helps optimize lead compounds by minimizing unwanted side effects, improving drug safety.
Area of Science:
- Medicinal Chemistry
- Computational Chemistry
- Drug Discovery
Background:
- Optimizing lead compounds into drug candidates necessitates removing undesirable antitarget activities.
- Existing methods may struggle with local structure-activity relationship (SAR) trends for antitargets.
Purpose of the Study:
- To develop and demonstrate an approach for extracting and applying antitarget activity hotspots.
- To guide the optimization of lead structures by mitigating unwanted side effects.
Main Methods:
- Extracting antitarget activity hotspots as informative molecule pairs (similar structure, different activity).
- Utilizing 3D-based similarity searching to link hotspots to new lead structures.
- Applying the workflow to optimize compounds against hERG and CYP3A4 inhibition.
Main Results:
- Demonstrated feasibility in optimizing lead structures for relevant antitargets.
- 3D-shape searching successfully identified related chemical scaffolds.
- Antitarget hotspot information effectively guided optimization to reduce undesirable activities.
Conclusions:
- The developed workflow serves as an effective idea generator in early drug optimization.
- This approach is particularly valuable when traditional antitarget quantitative structure-activity relationship (QSAR) models are insufficient.
- The method facilitates prospective drug design by transferring knowledge of antitarget activities.
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