Topology indices as predictors of retention behavior of newly synthesized androstane 3-oximes in RP-UHPLC: artificial intelligence approach

Kovačević Strahinja and Karadžić Banjac Milica and Anojčić Jasmina and Ajduković Jovana and Podunavac-Kuzmanović Sanja: Topology indices as predictors of retention behavior of newly synthesized androstane 3-oximes in RP-UHPLC: artificial intelligence approach.

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Abstract

The present study describes the application of artificial neural networks (ANNs), as artificial intelligence approach, as a tool in prediction of retention behavior of a series of newly synthesized series of androstane 3-oximes by using several molecular topology descriptors. The retention behavior of the studied androstane derivatives was determined by using reversedphase ultra high performance liquid chromatography (RP-UHPLC) with C18 column, as stationary phase, and methanol/water mobile phase. The retention behavior was determined in the form of logarithm of capacity factor (logk). The ANN modeling was performed applying Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm and multi-layer perceptron (MLP) feedforward networks. The obtained model successfully correlates hyper Wiener index (HWI), Szeged index (SZG) and Wiener index (WI) with logk values. The model was validated by internal validation and based on various statistical parameters. The model can be used for the prediction of retention behavior of the compounds structurally similar to those used in the modeling.

Item Type: Conference or Workshop Item
Journal or Publication Title: Proceedings of the International Symposium on Analytical and Environmental Problems
Date: 2024
Volume: 30
ISBN: 978-963-688-009-5
Page Range: pp. 318-322
Language: English
Publisher: University of Szeged
Place of Publication: Szeged
Event Title: 30th International Symposium on Analytical and Environmental Problems
Event Type: Conference
Event Location: Szeged
Event Dates: 2024. október 7-8.
Related URLs: https://acta.bibl.u-szeged.hu/85607/
Uncontrolled Keywords: Mesterséges intelligencia, Analitikai kémia, Gyógyszerkémia
Additional Information: Bibliogr.: 322. p. ; ill. ; összefoglalás angol nyelven
Subjects: 01. Natural sciences
01. Natural sciences > 01.02. Computer and information sciences
01. Natural sciences > 01.04. Chemical sciences
Date Deposited: 2024. Nov. 26. 13:41
Last Modified: 2024. Nov. 26. 13:41
URI: http://acta.bibl.u-szeged.hu/id/eprint/85748

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