Title of article :
Antitumor structure–activity relationship in bis-stannoxane derivatives from pyridine dicarboxylic and benzoic acids
Author/Authors :
Valcarcel، نويسنده , , José Antonio and Razo-Hern?ndez، نويسنده , , Rodrigo Said and Valdez-Vel?zquez، نويسنده , , Laura Leticia and Garc?a، نويسنده , , Manuel Villanueva and Organillo، نويسنده , , ?ngel Andrés Ramos and V?zquez-Vuelvas، نويسنده , , Oscar F. and Garc?a Ruiz، نويسنده , , Miguel A. and G?mez-Sandoval، نويسنده , , Zeferino، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2012
Abstract :
Organometallic compounds have been proposed as new drugs for cancer treatment due to the large metal mesh with DNA. This study estimated four quantitative structure–activity relationship (QSAR) descriptive models relating antitumor biological activity essays (ID50) in breast (MFC-7) and colon cancer (WiDr) cell lines with stannoxanes compounds derived from 2,6-pyridine-dicarboxylates [C5H3N(COO)2SnRR′] (R, R′ = alkyl, aryl) and di-n-butyltinbis-benzoates [(C6H5COO)2SnBu2]. A series of thermodynamic, structural and molecular descriptors were calculated from the geometric and electrical optimizations (PM3) of the two organotin series, in order to correlate the biological activity of the tin esters. The use of genetic algorithms and multilinear correlations yielded four mathematical models, each one with four descriptors related to molecular, area/volume, lipophilicity, and molecular dipole polarizability. These descriptors were entered into a back-propagation neural network to obtain theoretical descriptive models with the goal of proposing the development of new organotin molecules with enhanced antitumor activity.
Keywords :
Organotin compounds , QSAR , NEURAL NETWORKS , Genetic algorithms , MCF-7 , WiDr
Journal title :
INORGANICA CHIMICA ACTA
Journal title :
INORGANICA CHIMICA ACTA