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Use of self-organizing maps and molecular descriptors to predict the cytotoxic activity of sesquiterpene lactones
- Source :
- European Journal of Medicinal Chemistry. 43:2197-2205
- Publication Year :
- 2008
- Publisher :
- Elsevier BV, 2008.
-
Abstract
- Some sesquiterpene lactones (SLs) are the active compounds of a great number of traditionally medicinal plants from the Asteraceae family and possess considerable cytotoxic activity. Several studies in vitro have shown the inhibitory activity against cells derived from human carcinoma of the nasopharynx (KB). Chemical studies showed that the cytotoxic activity is due to the reaction of alpha,beta-unsaturated carbonyl structures of the SLs with thiols, such as cysteine. These studies support the view that SLs inhibit tumour growth by selective alkylation of growth-regulatory biological macromolecules, such as key enzymes, which control cell division, thereby inhibiting a variety of cellular functions, which directs the cells into apoptosis. In this study we investigated a set of 55 different sesquiterpene lactones, represented by 5 skeletons (22 germacranolides, 6 elemanolides, 2 eudesmanolides, 16 guaianolides and nor-derivatives and 9 pseudoguaianolides), in respect to their cytotoxic properties. The experimental results and 3D molecular descriptors were submitted to Kohonen self-organizing map (SOM) to classify (training set) and predict (test set) the cytotoxic activity. From the obtained results, it was concluded that only the geometrical descriptors showed satisfactory values. The Kohonen map obtained after training set using 25 geometrical descriptors shows a very significant match, mainly among the inactive compounds (approximately 84%). Analyzing both groups, the percentage seen is high (83%). The test set shows the highest match, where 89% of the substances had their cytotoxic activity correctly predicted. From these results, important properties for the inhibition potency are discussed for the whole dataset and for subsets of the different structural skeletons.
- Subjects :
- Pharmacology
chemistry.chemical_classification
Germacranolide
Molecular model
Stereochemistry
Organic Chemistry
Drug Evaluation, Preclinical
Antineoplastic Agents
General Medicine
Sesquiterpene
In vitro
Terpenoid
Lactones
chemistry.chemical_compound
chemistry
Biochemistry
Molecular descriptor
Drug Discovery
Humans
Cytotoxic T cell
Neural Networks, Computer
Sesquiterpenes
Lactone
Subjects
Details
- ISSN :
- 02235234
- Volume :
- 43
- Database :
- OpenAIRE
- Journal :
- European Journal of Medicinal Chemistry
- Accession number :
- edsair.doi.dedup.....03f6da2348b47fe13b756a58853de4d1
- Full Text :
- https://doi.org/10.1016/j.ejmech.2008.01.003