ANN and GMDH Algorithms in QSAR Analyses of Reactivation Potency for Acetylcholinesterase Inhibited by VX Warfare Agent

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F17%3A50013731" target="_blank" >RIV/62690094:18450/17:50013731 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-319-67077-5_17" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-67077-5_17</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-67077-5_17" target="_blank" >10.1007/978-3-319-67077-5_17</a>

Jazyk výsledku

angličtina

Název v původním jazyce

ANN and GMDH Algorithms in QSAR Analyses of Reactivation Potency for Acetylcholinesterase Inhibited by VX Warfare Agent

Popis výsledku v původním jazyce

Successful development of novel drugs requires a close cooperation of experimental subjects, such as chemistry and biology, with theoretical disciplines in order to confidently design new chemical structures eliciting the desired therapeutic effects. Herein, especially quantitative structure-activity relationships (QSAR) as correlation models may elucidate which molecular features are significantly associated with enhancing a specific biological activity. In the present study, QSAR analyses of 30 pyridinium aldoxime reactivators for VX-inhibited rat acetylcholinesterase (AChE) were performed using the group method of data handling (GMDH) approach. The self-organizing polynomial networks based on GMDH were compared with multilayer perceptron networks (MPN) trained by 10 different algorithms. The QSAR models developed by GMHD and MPN were critically evaluated and proposed for further utilization in drug development.

Název v anglickém jazyce

ANN and GMDH Algorithms in QSAR Analyses of Reactivation Potency for Acetylcholinesterase Inhibited by VX Warfare Agent

Popis výsledku anglicky

Successful development of novel drugs requires a close cooperation of experimental subjects, such as chemistry and biology, with theoretical disciplines in order to confidently design new chemical structures eliciting the desired therapeutic effects. Herein, especially quantitative structure-activity relationships (QSAR) as correlation models may elucidate which molecular features are significantly associated with enhancing a specific biological activity. In the present study, QSAR analyses of 30 pyridinium aldoxime reactivators for VX-inhibited rat acetylcholinesterase (AChE) were performed using the group method of data handling (GMDH) approach. The self-organizing polynomial networks based on GMDH were compared with multilayer perceptron networks (MPN) trained by 10 different algorithms. The QSAR models developed by GMHD and MPN were critically evaluated and proposed for further utilization in drug development.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Computational Collective Intelligence

ISBN

978-3-319-67076-8

ISSN

0302-9743

e-ISSN

neuvedeno

Počet stran výsledku

11

Strana od-do

171-181

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Nicosia, Cyprus

Datum konání akce

27. 9. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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