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NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode
Published on: June 4, 2021
Random molecular fragment methods in computational medicinal chemistry.
Eugen Lounkine1, José Batista, Jürgen Bajorath
1Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology & Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstr. 2, D-53113 Bonn, Germany.
Current Medicinal Chemistry
|September 11, 2008
Summary
Random fragmentation methods offer novel ways to identify molecular substructures and create fragment descriptors for drug design. These techniques complement existing approaches, enhancing computational chemistry tools.
Area of Science:
- Computational chemistry
- Medicinal chemistry
- Drug design
Background:
- Molecular substructures and fragment descriptors are crucial for computational applications in medicinal chemistry and drug design.
- Established molecular fragmentation methods have a history of use in these fields.
Purpose of the Study:
- To review the history and current widely used molecular fragmentation methods.
- To focus on recently introduced random fragmentation methods and their applications.
- To demonstrate the potential of random fragmentation for novel descriptor identification and similarity search tools.
Main Methods:
- Review of historical and current molecular fragmentation techniques.
- Focus on the generation and mining of random fragment populations.
- Application of random fragmentation schemes in computational drug design.
Main Results:
- Random fragmentation methods enable the identification of novel fragment descriptors.
- These methods facilitate the creation of similarity search tools that differ from conventional approaches.
- Random fragmentation complements and extends existing fragment-based methods.
Conclusions:
- Random fragmentation represents a significant advancement in molecular descriptor generation.
- This approach offers new possibilities for drug discovery and computational chemistry.
- The integration of random fragmentation enhances the toolkit for designing novel therapeutics.
