English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Quantitative structure-retention relationship (QSRR) analysis is a useful technique capable of relating chromatographic retention time to the chemical structure of a solute. A QSRR study has been carried out on the reversed-phase high-performance liquid chromatography retention times (log tR) of 62 diverse drugs (painkillers) by using molecular descriptors. Multiple linear regression (MLR) is utilized to construct the linear QSRR model. The applied MLR is based on a variety of theoretical molecular descriptors selected by the stepwise variable subset selection procedure. Stepwise regression was employed to develop a regression equation based on 50 training compounds, and predictive ability was tested on 12 compounds reserved for that purpose. The geometry of all drugs was optimized by the semi-empirical method AM1 and used to calculate different molecular descriptors. The regression equation included three parameters: n-octanol-water partition coefficient (log P), molecular surface area, and hydrophilic-lipophilic balance of the drug molecules, all of which could be related to retention time property. Modeling of retention times of these compounds as a function of the theoretically derived descriptors was established by MLR. The results indicate that a strong correlation exists between the log tR and the previously mentioned descriptors for drug compounds. The prediction results are in good agreement with the experimental values.

QSRR Prediction of the Chromatographic Retention Behavior of Painkiller Drugs