Pregled bibliografske jedinice broj: 186721
New classification procedure for biologically active compounds based on similarity of their molecular interactions and logP prediction
New classification procedure for biologically active compounds based on similarity of their molecular interactions and logP prediction // Zbornik sažetaka postera znanstvenih novaka izlaganih u inozemstvu 2002., 2003. i 2004. godine / Kniewald, Zlatko (ur.).
Zagreb, 2004. str. 15-16 (poster, domaća recenzija, sažetak, znanstveni)
CROSBI ID: 186721 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
New classification procedure for biologically active compounds based on similarity of their molecular interactions and logP prediction
Autori
Bertoša, Branimir ; Tomić, Sanja ; Kojić-Prodić, Biserka
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Izvornik
Zbornik sažetaka postera znanstvenih novaka izlaganih u inozemstvu 2002., 2003. i 2004. godine
/ Kniewald, Zlatko - Zagreb, 2004, 15-16
Skup
Prvi kongres hrvatskih znanstvenika iz domovine i inozemstva
Mjesto i datum
Vukovar, Hrvatska; Zagreb, Hrvatska, 15.11.2004. - 19.11.2004
Vrsta sudjelovanja
Poster
Vrsta recenzije
Domaća recenzija
Ključne riječi
Auksini; QSAR; logP
(Auxin; QSAR; logP)
Sažetak
The activity of biological compounds is dependent on both specific binding to target receptors and ADME properties (Absorption, Distribution, Metabolism, Excretion). A challenge to prediction of biological activity is to consider both these types of contributions simultaneously in deriving quantitative models. Previously we have developed a method for classification of (biologically active) compounds based on similarity of their molecular interaction fields. Herein we will present our new, more complex model that combines molecular interaction field analysis with the logP prediction. The method is conformation dependent and because of this elucidation of the biologically active conformation of a molecule is possible. The method is tested on a set of about hundred auxin related compounds. In the first run the auxin related molecules were classified on the basis of similarity of their interaction fields, only. Further on the influence of logP value to biological activity was taken into account. This resulted with the classification improvement and indicates that the method is especially efficient in cases where biological activity of compounds is correlated with their transport through cell membranes. The majority of the analyzed compounds were classified in accord with the experimental data available.
Izvorni jezik
Engleski
Znanstvena područja
Kemija
