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CORAL Software: Analysis of Impacts of Pharmaceutical Agents Upon Metabolism via the Optimal Descriptors

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11110%2F17%3A10364181" target="_blank" >RIV/00216208:11110/17:10364181 - isvavai.cz</a>

  • Nalezeny alternativní kódy

    RIV/00064165:_____/17:10364181

  • Výsledek na webu

    <a href="http://dx.doi.org/10.2174/1389200218666170301105916" target="_blank" >http://dx.doi.org/10.2174/1389200218666170301105916</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.2174/1389200218666170301105916" target="_blank" >10.2174/1389200218666170301105916</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    CORAL Software: Analysis of Impacts of Pharmaceutical Agents Upon Metabolism via the Optimal Descriptors

  • Popis výsledku v původním jazyce

    Backgrounds: The CORAL software has been developed as a tool to build up quantitative structureactivity relationships (QSAR) for various endpoints. Objective: The task of the present work was to estimate and to compare QSAR models for biochemical activity of various therapeutic agents, which are built up by the CORAL software. Method: The Monte Carlo technique gives possibility to build up predictive model of an endpoint by means of selection of so-called correlation weights of various molecular features extracted from simplified molecular input-line entry system (SMILES). Descriptors calculated with these weights are basis for building up correlations &quot;structure-endpoint&quot;. Results: Optimal descriptors, which are aimed to predict values of endpoints with apparent influence upon metabolism are crytically compared in aspect of their robustness and heuristic potential. Arguments which are confirming the necessity of reformulation of basics of QSARs are listed: (i) each QSAR model is stochastic experiment. The result of this experiment is defined by distribution into the training set and validation set; (ii) predictive potential of a model should be checked up with a group of different splits; and (iii) only model stochastically stable for a group of splits can be estimated as a reliable tool for the prediction. Examples of the improvement of the models previously suggested are demonstrated. Conclusion: The current version of the CORAL software remains a convenient tool to build up predictive models. The Monte Carlo technique involved for the software confirms the principle &quot;QSAR is a random event&quot; is important paradigm for the QSPR/QSAR analyses.

  • Název v anglickém jazyce

    CORAL Software: Analysis of Impacts of Pharmaceutical Agents Upon Metabolism via the Optimal Descriptors

  • Popis výsledku anglicky

    Backgrounds: The CORAL software has been developed as a tool to build up quantitative structureactivity relationships (QSAR) for various endpoints. Objective: The task of the present work was to estimate and to compare QSAR models for biochemical activity of various therapeutic agents, which are built up by the CORAL software. Method: The Monte Carlo technique gives possibility to build up predictive model of an endpoint by means of selection of so-called correlation weights of various molecular features extracted from simplified molecular input-line entry system (SMILES). Descriptors calculated with these weights are basis for building up correlations &quot;structure-endpoint&quot;. Results: Optimal descriptors, which are aimed to predict values of endpoints with apparent influence upon metabolism are crytically compared in aspect of their robustness and heuristic potential. Arguments which are confirming the necessity of reformulation of basics of QSARs are listed: (i) each QSAR model is stochastic experiment. The result of this experiment is defined by distribution into the training set and validation set; (ii) predictive potential of a model should be checked up with a group of different splits; and (iii) only model stochastically stable for a group of splits can be estimated as a reliable tool for the prediction. Examples of the improvement of the models previously suggested are demonstrated. Conclusion: The current version of the CORAL software remains a convenient tool to build up predictive models. The Monte Carlo technique involved for the software confirms the principle &quot;QSAR is a random event&quot; is important paradigm for the QSPR/QSAR analyses.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    30104 - Pharmacology and pharmacy

Návaznosti výsledku

  • Projekt

  • Návaznosti

    V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Ostatní

  • Rok uplatnění

    2017

  • Kód důvěrnosti údajů

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

Údaje specifické pro druh výsledku

  • Název periodika

    Current Drug Metabolism

  • ISSN

    1389-2002

  • e-ISSN

  • Svazek periodika

    18

  • Číslo periodika v rámci svazku

    6

  • Stát vydavatele periodika

    AE - Spojené arabské emiráty

  • Počet stran výsledku

    11

  • Strana od-do

    500-510

  • Kód UT WoS článku

    000406190300003

  • EID výsledku v databázi Scopus

    2-s2.0-85027866034