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Skin Partitioning Prediction of Drug-like Compounds

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F15%3A33156088" target="_blank" >RIV/61989592:15310/15:33156088 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Skin Partitioning Prediction of Drug-like Compounds

  • Original language description

    Here we report the developments on in silico methods usable for prediction of partitioning into skin lipids. We have developed simple bilayer models of ceramides or skin lipid mixture. Using continuum solvent method - COSMOmic, we have evaluated free energy profiles of individual drug-like compounds and we concluded that skin lipid mixture model is more reliable to predict partitioning of set of 20 compounds into skin lipids when compared to experimentally measured values. We have also assessed the effect of conformers and ionizable groups. Finally, we have also studied possibilities of advanced sampling method for molecular dynamics of skin barrier membrane - metadynamics - in order to generate free energy profiles for comparison. This methodology isintended to add piece for calculation of bioavailability of permeants via skin absorption in collaboration with P&G.

  • Czech name

  • Czech description

Classification

  • Type

    V<sub>souhrn</sub> - Summary research report

  • CEP classification

    CF - Physical chemistry and theoretical chemistry

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    N - Vyzkumna aktivita podporovana z neverejnych zdroju

Others

  • Publication year

    2015

  • Confidentiality

    C - Předmět řešení projektu podléhá obchodnímu tajemství (§ 504 Občanského zákoníku), ale název projektu, cíle projektu a u ukončeného nebo zastaveného projektu zhodnocení výsledku řešení projektu (údaje P03, P04, P15, P19, P29, PN8) dodané do CEP, jsou upraveny tak, aby byly zveřejnitelné.

Data specific for result type

  • Number of pages

    36

  • Place of publication

  • Publisher/client name

    Procter&amp;Gamble

  • Version