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Random Molecular Fragment Methods in Computational Medicinal Chemistry

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Molecular substructures and fragment descriptors are important tools for many computational applications in medicinal chemistry and drug design. Here we briefly review the history of molecular fragmentation methods and describe the currently most widely used approaches. Then we focus on random fragmentation methods that have only recently been introduced and discuss selected applications. It is shown that the generation and mining of random fragment populations makes it possible to identify novel types of fragment descriptors and generate similarity search tools that depart from conventional design approaches. Thus, random fragmentation schemes complement and further extend established fragment methods.
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Keywords: Substructures; computational medicinal chemistry; database mining; fragment descriptors; molecular similarity; random fragmentation; structure-activity relationships; systematic and knowledge-based fragment design

Document Type: Research Article

Affiliations: Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology & Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universitat, Dahlmannstr. 2, D-53113 Bonn, Germany.

Publication date: 2008-09-01

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  • Current Medicinal Chemistry covers all the latest and outstanding developments in medicinal chemistry and rational drug design. Each issue contains a series of timely in-depth reviews written by leaders in the field covering a range of the current topics in medicinal chemistry. Current Medicinal Chemistry is an essential journal for every medicinal chemist who wishes to be kept informed and up-to-date with the latest and most important developments.
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