Chromatographic lipophilicity as a predictor of antiproliferative activity of 17-picolyl and 17-picolinylidene androstane derivatives toward prostate cancer | Zendy

Strаhinjа Kоvаčеvić | Zendy; Sanja Podunavac-Kuzmаnоvić | Zendy; Lidija R. Jevrić | Zendy; Evgenija A. Djurendić | Zendy; Jovana J. Ajduković | Zendy; Pavle Jovanov | Zendy

Open Access

Chromatographic lipophilicity as a predictor of antiproliferative activity of 17-picolyl and 17-picolinylidene androstane derivatives toward prostate cancer

Author(s) -

Strаhinjа Kоvаčеvić,

Sanja Podunavac-Kuzmаnоvić,

Lidija R. Jevrić,

Evgenija A. Djurendić,

Jovana J. Ajduković,

Pavle Jovanov

Publication year - 2015

Publication title -

acta periodica technologica

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.134

H-Index - 15

eISSN - 2406-095X

pISSN - 1450-7188

DOI - 10.2298/apt1546239k

Subject(s) - lipophilicity , androstane , chemistry , chromatography , prostate cancer , quantitative structure–activity relationship , prostate , cancer , medicine , stereochemistry

The present study describes the quantitative retention - (anticancer) activity relationship analysis of a series of 17-picolyl and 17-picolinylidene androstane derivatives based on the chromatographic data obtained by reversed-phase high performance liquid chromatography (C18-RP-HPLC) in a mobile phase consisting of 90% of methanol and 10% of water. The obtained retention factor or chromatographic lipophilicity factor (logk0.90) was correlated with the antiproliferative activity of studied compounds (IC50) toward androgen-receptor negative prostate cancer cell line (AR-neg. PC-3). Correlation analysis was carried out by applying non-linear artificial neural networks (ANNs) method. Statistical validation showed that the obtained ANNs can successfully predict the IC50 values of structurally similar androstane derivatives

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research