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

J 2021

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

HAVRÁNKOVÁ, Eva, E.M. PEÑA-MÉNDEZ, Jozef CSÖLLEI a Josef HAVEL

Základní údaje

Originální název

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

Autoři

HAVRÁNKOVÁ, Eva (203 Česká republika, garant, domácí), E.M. PEÑA-MÉNDEZ, Jozef CSÖLLEI a Josef HAVEL (203 Česká republika, domácí)

Vydání

Bioorganic Chemistry, San Diego, Academic Press Inc Elsevier Science, 2021, 0045-2068

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10400 1.4 Chemical sciences

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 5.307

Kód RIV

RIV/00216224:14160/21:00120916

Organizační jednotka

Farmaceutická fakulta

DOI

http://dx.doi.org/10.1016/j.bioorg.2020.104565

UT WoS

000618103400003

Klíčová slova anglicky

ANN; Structural descriptors1.3.5-triazinyl sulfonamide derivatives; Carbonic anhydrase

Štítky

rivok, ÚChL

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 6. 4. 2021 16:40, Mgr. Marie Šípková, DiS.

Anotace

V originále

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).

Citovat

HAVRÁNKOVÁ, Eva, E.M. PEÑA-MÉNDEZ, Jozef CSÖLLEI a Josef HAVEL. Prediction of biological activity of compounds containing a 1,3,5-triazinyl sulfonamide scaffold by artificial neural networks using simple molecular descriptors. Bioorganic Chemistry. San Diego: Academic Press Inc Elsevier Science, 2021, roč. 107, February 2021, s. 1-15. ISSN 0045-2068. Dostupné z: https://dx.doi.org/10.1016/j.bioorg.2020.104565.

@article{1720496,
   author = {Havránková, Eva and PeñaandMéndez, E.M. and Csöllei, Jozef and Havel, Josef},
   article_location = {San Diego},
   article_number = {February 2021},
   doi = {http://dx.doi.org/10.1016/j.bioorg.2020.104565},
   keywords = {ANN; Structural descriptors1.3.5-triazinyl sulfonamide derivatives; Carbonic anhydrase},
   language = {eng},
   issn = {0045-2068},
   journal = {Bioorganic Chemistry},
   title = {Prediction of biological activity of compounds containing a 1,3,5-triazinyl sulfonamide scaffold by artificial neural networks using simple molecular descriptors},
   url = {https://doi.org/10.1016/j.bioorg.2020.104565},
   volume = {107},
   year = {2021}
}

TY  - JOUR
ID  - 1720496
AU  - Havránková, Eva - Peña-Méndez, E.M. - Csöllei, Jozef - Havel, Josef
PY  - 2021
TI  - Prediction of biological activity of compounds containing a 1,3,5-triazinyl sulfonamide scaffold by artificial neural networks using simple molecular descriptors
JF  - Bioorganic Chemistry
VL  - 107
IS  - February 2021
SP  - 1-15
EP  - 1-15
PB  - Academic Press Inc Elsevier Science
SN  - 00452068
KW  - ANN
KW  - Structural descriptors1.3.5-triazinyl sulfonamide derivatives
KW  - Carbonic anhydrase
UR  - https://doi.org/10.1016/j.bioorg.2020.104565
L2  - https://doi.org/10.1016/j.bioorg.2020.104565
N2  - 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).
ER  -

HAVRÁNKOVÁ, Eva, E.M. PEÑA-MÉNDEZ, Jozef CSÖLLEI a Josef HAVEL. Prediction of biological activity of compounds containing a 1,3,5-triazinyl sulfonamide scaffold by artificial neural networks using simple molecular descriptors. \textit{Bioorganic Chemistry}. San Diego: Academic Press Inc Elsevier Science, 2021, roč.~107, February 2021, s.~1-15. ISSN~0045-2068. Dostupné z: https://dx.doi.org/10.1016/j.bioorg.2020.104565.

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