Prediction of biological activity of compounds containing a 1,3,5-triazinyl sulfonamide scaffold by artificial neural networks using simple molecular descriptors
Jazyk angličtina Země Spojené státy americké Médium print-electronic
Typ dokumentu časopisecké články
PubMed
33418318
DOI
10.1016/j.bioorg.2020.104565
PII: S0045-2068(20)31863-0
Knihovny.cz E-zdroje
- Klíčová slova
- 1,3,5-triazinyl sulfonamide derivatives, ANN, Carbonic anhydrase, Structural descriptors,
- MeSH
- antigeny nádorové metabolismus MeSH
- inhibitory karboanhydras chemie metabolismus MeSH
- karboanhydrasa II antagonisté a inhibitory metabolismus MeSH
- karboanhydrasa IX antagonisté a inhibitory metabolismus MeSH
- lidé MeSH
- neuronové sítě * MeSH
- racionální návrh léčiv MeSH
- sulfonamidy chemie metabolismus MeSH
- triaziny chemie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- antigeny nádorové MeSH
- CA9 protein, human MeSH Prohlížeč
- inhibitory karboanhydras MeSH
- karboanhydrasa II MeSH
- karboanhydrasa IX MeSH
- sulfonamidy MeSH
- triaziny MeSH
Simple molecular descriptors of extensive series of 1,3,5-triazinyl sulfonamide derivatives, based on the structure of sulfonamides and their physicochemical properties, were designed and calculated. These descriptors were successfully applied as inputs for artificial neural network (ANN) modelling of the relationship between the structure and biological activity. The optimized ANN architecture was applied to the prediction of the inhibition activity of 1,3,5-triazinyl sulfonamides against human carbonic anhydrase (hCA) II, tumour-associated hCA IX, and their selectivity (hCA II/hCA IX).
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