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

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

Document Type: Research Article

Publication date: 01 March 2012

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  • Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, etc., providing excellent rationales for drug development.
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