Theoretical and Molecular Docking Study of Ketoconazole on Heptakis(2,3,6-tri-O-methyl)-ß-cyclodextrin as Chiral Selector.

A molecular docking study, using molecular mechanics calculations with AutoDock and semi-empirical PM3 calculations, was used to predict the enantiodiscrimination of heptakis(2,3,6-tri-O-methyl)-ß-cyclodextrin (TMßCD) and ketoconazole (KTZ) enantiomers. A Density Functional Theory (DFT) single-point calculation at the level of B3LYP/6-311G (d,p) was performed for the PM3-optimized complexes to obtain more accurate binding energy and the electronic structures of the complexes. The difference in energies of the inclusion complexes between the KTZ enantiomers and TMßCD is probably a measure of chiral discrimination, which results in the separation of the enantiomers as observed in the experimental studies.

Chiral separation of four stereoisomers of ketoconazole drugs using capillary electrophoresis.

This work aimed to develop a chiral separation method of ketoconazole enantiomers using electrokinetic chromatography. The separation was achieved using heptakis (2, 3, 6-tri-O-methyl)-ß-cyclodextrin (TMßCD), a commonly used chiral selector (CS), as it is relatively inexpensive and has a low UV absorbance in addition to an anionic surfactant, sodium dodecyl sulfate (SDS). The influence of TMßCD concentration, phosphate buffer concentration, SDS concentration, buffer pH, and applied voltage were investigated. The optimum conditions for chiral separation of ketoconazole was achieved using 10 mM phosphate buffer at pH 2.5 containing 20 mM TMßCD, 5 mM SDS, and 1.0% (v/v) methanol with an applied voltage of 25 kV at 25 °C with a 5-s injection time (hydrodynamic injection). The four ketoconazole stereoisomers were successfully resolved for the first time within 17 min (total analysis time was 28 min including capillary conditioning). The migration time precision of this method was examined to give repeatability and reproducibility with RSDs ≤5.80% (n =3) and RSDs ≤8.88% (n =9), respectively.

Prerequisite for COVID-19 Prediction: A Review on Factors Affecting the Infection Rate.

Since the year 2020, coronavirus disease 2019 (COVID-19) has emerged as the dominant topic of discussion in the public and research domains. Intensive research has been carried out on several aspects of COVID-19, including vaccines, its transmission mechanism, detection of COVID-19 infection, and its infection rate and factors. The awareness of the public related to the COVID-19 infection factors enables the public to adhere to the standard operating procedures, while a full elucidation on the correlation of different factors to the infection rate facilitates effective measures to minimize the risk of COVID-19 infection by policy makers and enforcers. Hence, this paper aims to provide a comprehensive and analytical review of different factors affecting the COVID-19 infection rate. Furthermore, this review analyses factors which directly and indirectly affect the COVID-19 infection risk, such as physical distance, ventilation, face masks, meteorological factor, socioeconomic factor, vaccination, host factor, SARS-CoV-2 variants, and the availability of COVID-19 testing. Critical analysis was performed for the different factors by providing quantitative and qualitative studies. Lastly, the challenges of correlating each infection risk factor to the predicted risk of COVID-19 infection are discussed, and recommendations for further research works and interventions are outlined.