title: Non-linear assessment of anticancer activity of 17-picolyl and 17-picolinylidene androstane derivatives--chemometric guidelines for further syntheses.
abstract: The present paper deals with prediction of cytotoxic activity of 17-picolyl and 17-picolinylidene androstane derivatives toward androgen receptor negative prostate cancer cell line (PC-3). The prediction was achieved applying artificial neural networks (ANNs) method on the basis of molecular descriptors. The most important descriptors (skin permeability (SP), Madin-Darby canine kidney cell permeability (MDCK) and universal salt solubility factor (S+SF)) were selected by using stepwise selection coupled with partial least squares method. The ANN modelling was carried out in order to obtain reliable models which can facilitate further synthesis of androstane derivatives with high antiproliferative activity toward PC-3 cell line. The modelling procedure resulted in three ANN models with the best statistical performance. The obtained results show that the established ANN models can be applied for required purpose.
authors.affiliation: University of Novi Sad, Faculty of Technology, Department of Applied and Engineering Chemistry, Bulevar cara Lazara 1, 21000 Novi Sad, Serbia. Electronic address: strahko@uns.ac.rs.
authors.forename: Strahinja Z
authors.initials: SZ
authors.lastname: Kovačević
authors.affiliation: University of Novi Sad, Faculty of Technology, Department of Applied and Engineering Chemistry, Bulevar cara Lazara 1, 21000 Novi Sad, Serbia.
authors.forename: Sanja O
authors.initials: SO
authors.lastname: Podunavac-Kuzmanović
authors.affiliation: University of Novi Sad, Faculty of Technology, Department of Applied and Engineering Chemistry, Bulevar cara Lazara 1, 21000 Novi Sad, Serbia.
authors.forename: Lidija R
authors.initials: LR
authors.lastname: Jevrić
authors.affiliation: University of Novi Sad, Faculty of Sciences, Department of Chemistry, Biochemistry and Environmental Protection, Trg Dositeja Obradovića 3, 21000 Novi Sad, Serbia.
authors.forename: Evgenija A
authors.initials: EA
authors.lastname: Djurendić
authors.affiliation: University of Novi Sad, Faculty of Sciences, Department of Chemistry, Biochemistry and Environmental Protection, Trg Dositeja Obradovića 3, 21000 Novi Sad, Serbia.
authors.forename: Jovana J
authors.initials: JJ
authors.lastname: Ajduković
mesh_terms: D000731:Androstanes / Q000494:pharmacology*; D000818:Animals; D000970:Antineoplastic Agents / Q000494:pharmacology*; D045744:Cell Line, Tumor; D002470:Cell Survival / Q000187:drug effects; D004285:Dogs; D006801:Humans; D061985:Madin Darby Canine Kidney Cells; D008954:Models, Biological; D008958:Models, Molecular; D016571:Neural Networks, Computer; D015203:Reproducibility of Results
chemical_list: D000731:Androstanes; D000970:Antineoplastic Agents
keywords: Androstane derivatives; Artificial neural networks; Chemometrics; Molecular modelling; Prostate cancer