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Development of a Structural Model for NF-κB Inhibition of Sesquiterpene Lactones Using Self-Organizing Neural Networks
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Section:Abstract
A variety of sesquiterpene lactones (SLs) possess considerable anti-inflammatory activity. Several studies have shown that they exert this effect in part by inhibiting the activation of the transcription factor NF-κB. In the present study we elaborated on the investigation of a data set of 103 structurally diverse SLs for which we had previously developed several different QSAR equations dependent on the skeletal type. Use of 3D structure descriptors resulted in a single model for the entire data set. In particular, local radial distribution functions (L-RDF) were used that centered on the methylene−carbonyl substructure believed to be the site of attack of cysteine-38 of the p65/NF-κB subunit. The model was developed by using a counterpropagation neural network (CPGNN), attesting to the power of this method for establishing structure−activity-relationships. The investigations shed more light onto the influence of the chemical structure on NF-κB inhibitory activity.
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This article has been cited by 6 ACS Journal articles (5 most recent appear below).
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Modeling anti-Trypanosoma cruzi Activity of N-Oxide Containing Heterocycles
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History
- Published In Issue April 06, 2006
- Received November 8, 2005
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