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Current Computer-Aided Drug Design

Editor-in-Chief

ISSN (Print): 1573-4099
ISSN (Online): 1875-6697

Structure-Retention Relationship Study of HPLC Data of Antiepileptic Hydantoin Analogues

Author(s): Tatjana Djakovic-Sekulic, Anamarija Mandic, Nemanja Trisovic and Gordana Uscumlic

Volume 8, Issue 1, 2012

Page: [3 - 9] Pages: 7

DOI: 10.2174/157340912799218525

Price: $65

Abstract

In the study, 18 antiepileptic hydantoin analogues were investigated by means of reversed-phase HPLC on C- 18 stationary phase and eluent acetonitrile-water. Quantitative structure – retention relationship (QSRR) study has been applied in order to understand factors that affect the retention which is closely correlated to the activity (ED50 values). To overview the compounds for similarities and dissimilarities principal component analysis (PCA) has been applied. Six multiple linear regression models based on the most relevant descriptors were developed. Descriptors for MLR were selected according to variable importance calculated by partial least squares (PLS) analysis. Besides ALOGP the most important is aromatic ratio for mobile phases with more than 45% of acetonitrile, as well as electrotopological states when the % of acetonitrile is less than 40%. High agreement between experimental and predicted retention, obtained in the validation procedure, indicated the good quality of the derived QSRR models. For individual linear models, crossvalidation squared correlation coefficients (Q2) ranging from 0.697 to 0.837 were obtained. The residual values (difference between observed and calculated) agreed well within experimental error. Additionally, models were compared in terms of the smallest residual value by recently developed method of ranking based on the sum of ranking differences (SRD).

Keywords: Antiepileptic hydantoin analogues, quantitative structure, , retention relationship (QSRR), liquid chromatography, activity, principal component analysis (PCA), multiple linear regression (MLR), sum of ranking differences (SRD), ADME, molecular descriptors, DRAGON software

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