Applications of Integrated Data Mining Methods to Exploring Natural Product Space for Acetylcholinesterase Inhibitors

Authors: Schuster, Daniela; Kern, Lisa; Hristozov, Dimitar P.; Terfloth, Lothar; Bienfait, Bruno; Laggner, Christian; Kirchmair, Johannes; Grienke, Ulrike; Wolber, Gerhard; Langer, Thierry

Source: Combinatorial Chemistry & High Throughput Screening, Volume 13, Number 1, January 2010 , pp. 54-66(13)

Publisher: Bentham Science Publishers

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Abstract:

Nature, especially the plant kingdom, is a rich source for novel bioactive compounds that can be used as lead compounds for drug development. In order to exploit this resource, the two neural network-based virtual screening techniques novelty detection with self-organizing maps (SOMs) and counterpropagation neural network were evaluated as tools for efficient lead structure discovery. As application scenario, significant descriptors for acetylcholinesterase (AChE) inhibitors were determined and used for model building, theoretical model validation, and virtual screening. Topranked virtual hits from both approaches were docked into the AChE binding site to approve the initial hits. Finally, in vitro testing of selected compounds led to the identification of forsythoside A and (+)-sesamolin as novel AChE inhibitors.

Keywords: Natural products; drug discovery; acetylcholinesterase; virtual screening; counterpropagation network; spinne; novelty detection

Document Type: Research article

DOI: http://dx.doi.org/10.2174/138620710790218212

Affiliations: 1: Department of Pharmacognosy, Institute of Pharmacy, University of Innsbruck, Innrain 52c, A-6020 Innsbruck, Austria.

Publication date: 2010-01-01

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Combinatorial Chemistry & High Throughput Screening publishes full length original research articles and reviews describing various topics in combinatorial chemistry (e.g. small molecules, peptide, nucleic acid or phage display libraries) and/or high throughput screening (e.g. developmental, practical or theoretical). Ancillary subjects of key importance, such as robotics and informatics, will also be covered by the journal. In these respective subject areas, Combinatorial Chemistry & High Throughput Screening is intended to function as the most comprehensive and up-to-date medium available. The journal should be of value to individuals engaged in the process of drug discoveryand development, in the settings of industry, academia or government.

Applications of Integrated Data Mining Methods to Exploring Natural Product Space for Acetylcholinesterase Inhibitors

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