Quantitative retention–activity relationship models for quinolones using biopartitioning micellar chromatography

Abstract

A simple and reproducible quantitative retention-activity relationship (QRAR) model utilizing biopartitioning micellar chromatography was developed for the biological parameter estimation of drugs. The correlation between retention factors of quinolones obtained in physiological conditions (pH, ionic strength) and biological activities was investigated using different second-order polynomial models. The predictive and interpretative ability of the chromatographic models was evaluated in terms of cross-validated data (RMSEC, RMSECV and RMSECVi). The aim was to obtain adequate QRAR models of half-life, clearance, volume of distribution, plasma protein combination rate, area under concentration-time curve and toxicity (LD50) of quinolones, and to elucidate the advantages and limitations of using a single parameter as independent variable for describing and estimating the activities.

Ionic Liquid-Functionalized Magnetic Metal–Organic Framework Nanocomposites for Efficient Extraction and Sensitive Detection of Fluoroquinolone Antibiotics in Environmental Water

“…Through zeta potential characterization, it was found that the zeta potentials of UiO-66, UiO-66-pydc, UiO-67, and UiO-67-bpydc were −7.6 mV, −4.7 mV, −8.5 mV, and −5.9 mV, respectively (Figure C). As shown in Figure S1 and Table S1, the p K a2 values of FQs are 5.7–6.4. − When pH > 6.4, FQs are mainly negatively charged, it is difficult for the adsorption of FQs by Zr-MOFs. When magnetic Fe 3 O 4 was introduced into the structures of Zr-MOFs, zeta potentials of Fe 3 O 4 @UiO-66, Fe 3 O 4 @UiO-66-pydc, Fe 3 O 4 @UiO-67, and Fe 3 O 4 @UiO-67-bpydc were +34.5 mV, +38.8 mV, +30.2 mV, and +31.8 mV, respectively (Figure S2), which suggested that there may be an electrostatic interaction between Fe 3 O 4 @Zr-MOFs and FQs.…”

Modeling the separation of small peptides by cation‐exchange chromatography

“…In results, RMSECV 1 corresponds to the leave-one-out approach, and RMSECV 10 to the tenfold cross-validation. From a qualitative point of view, comparable RMSE, RMSEC and RMSECV values indicate that both the interpolations and extrapolations of the model should be adequate, whereas large differences point out a lack of robustness [36].…”

“…When experimental data could appear rather limited, statistical analysis of various possible models has proved useful not only to validate each model, to assess its significance and its predictive ability but also to evaluate significance of each parameter in a model [36].…”

Liquid Chromatography on the Different Methods for the Determination of Lipophilicity: An Essential Analytical Tool in Medicinal Chemistry

“…Exploiting the ability to mimic the phospholipidic barriers, log k MLC values have been used to predict several pharmacokinetic parameters, such as human oral absorption (HOA) [196][197][198][199], blood-brain barrier (BBB) permeability [196], plasma protein binding (PPB) [200,201], the volume of distribution [200,201], and therapeutic parameters [200,201]. When compared to other chromatographic techniques, MLC appears to be in the midground between IAM and RP-HPLC.…”