Prediction of biological activity of compounds containing a 1,3,5-triazinyl sulfonamide scaffold by artificial neural networks using simple molecular descriptors

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Publikace nespadá pod Lékařskou fakultu, ale pod Farmaceutickou fakultu. Oficiální stránka publikace je na webu muni.cz.

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HAVRÁNKOVÁ Eva PENA-MÉNDEZ E.M. CSÖLLEI Jozef HAVEL Josef

Rok publikování 2021
Druh Článek v odborném periodiku
Časopis / Zdroj Bioorganic Chemistry
Fakulta / Pracoviště MU

Farmaceutická fakulta

Citace
www https://doi.org/10.1016/j.bioorg.2020.104565
Doi http://dx.doi.org/10.1016/j.bioorg.2020.104565
Klíčová slova ANN; Structural descriptors1.3.5-triazinyl sulfonamide derivatives; Carbonic anhydrase
Popis 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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