Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/460
Title: Toward steroidal anticancer drugs: Non-parametric and 3D-QSAR modeling of 17-picolyl and 17-picolinylidene androstanes with antiproliferative activity on breast adenocarcinoma cells
Authors: Kovačević, Strahinja 
Karadžić Banjac, Milica 
Vukić (Hrnjez), Dajana 
Vukić, Vladimir 
Podunavac-Kuzmanović, Sanja 
Jevrić, Lidija 
Ajduković (Daljev), Jovana 
Issue Date: Mar-2019
Publisher: Elsevier
Journal: Journal of Molecular Graphics and Modelling
Abstract: © 2018 Elsevier Inc. The present study is aimed to analyze lipophilicity and ADMET profiles, and to develop field based 3D-QSAR and ligand-based pharmacophore hypothesis for a series of 17α-picolyl and 17(E)-picolinylidene androstane derivatives in order to give detailed structural insights and to highlight important binding features of novel androstane derivatives, as compounds with antiproliferative activity toward breast adenocarcinoma cells. This study can provide guidelines for the rational design of novel potent compounds. Sum of ranking differences (SRD), as a non-parametric method, was applied for compounds ranking. 3D-QSAR methods, including comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), were applied to predict the antiproliferative effect on breast adenocarcinoma cells and provide the regions in space where interactive fields may influence the activity. The compounds are ranked so the compounds with the most favorable ADME and lipophilicity features together with significant anticancer activity can be distinguished. The established 3D-QSAR model could be used for design of new compounds with antiproliferative activity on the human ER– breast adenocarcinoma cells. The pharmacophore model is able to accurately predict antiproliferative activity. Generally, the present study provides significant guidelines for further selection, synthesis and rational design of new highly potential androstane derivatives as anticancer drugs.
URI: https://open.uns.ac.rs/handle/123456789/460
ISSN: 10933263
DOI: 10.1016/j.jmgm.2018.12.010
Appears in Collections:TF Publikacije/Publications

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