Prediction of plasma protein binding rate based on machine learning / 中国药科大学学报

@#Predicting the protein binding rate of drugs in plasma is helpful to us in understanding the pharmacokinetic characteristics of drugs, with much value of reference for early research on drug discovery. In this study, plasma protein binding rate information of 2 452 clinical drugs were collected.Two pieces of software, Molecular Operating Environment (MOE) and Mordred, were used to calculate molecular descriptors, which were used as input features of the model.Extreme gradient boosting (XGBoost) algorithm and random forest (RF) algorithm were then used to build a machine learning model.The results showed that, compared with MOE, the prediction performance of the constructed model was better using the molecular descriptor calculated by Mordred as the input of the model.The prediction performance results of the model constructed using the XGBoost algorithm and the RF algorithm were similar, and the R2 of the optimal model were both 0.715.According to the research results, it can be concluded that the drug plasma protein binding rate is closely related to some physical and chemical properties of the drug molecule, such as water solubility, octanol/water partition coefficient and conjugated double bonds.Using these parameters to predict the plasma protein binding rate of drugs has the advantages of convenience and efficiency, which can provide reference for related pharmacokinetic studies.

Comparison of the Undergraduate Education for Pharmaceutical Analysis Between National University of Singapore and China Pharmaceutical University / 医药导报

The course of pharmaceutical analysis for pharmacy undergraduate students in National University of Singapore and China Pharmaceutical University was compared, in terms of curriculum, lecturing, assessment and practical teaching.This study provides in-depth analysis by the lecturers from both universities,and can provide reference for teaching reform and course construction of pharmaceutical analysis.

Enantiomeric separation of zolmitriptan by CE with a sulfated β-cyclodextrin chiral selector / 中国药科大学学报

Aim:To develop a practical chiral CE method for the quantitative determination of the unwanted enantiomer[( R )-enantiomer]presented in zolmitriptan. Methods:The background electrolyte was 20 mmol/L sodium dihydrogenphosphate solution with 1% S-β-CD,adjusted to pH 3.50 with phosphoric acid. A fused-silica capillary(60 cm×50 μm ID,effective length 51.5 cm)was used at 20 ℃ for the separation. The applied voltage was -30 kV. The samples were loaded by hydrodynamic injection(50 mbar pressure,6 s). UV was measured at 220 nm. Results:Zolmitriptan and its chiral impurity were baseline resolved ( R s=6.66). The linearity was good over the concentration range from 4 to 80 μg/mL( r =0.999 8) of ( R )-enantiomer. The injection precision (expressed as CV%) was 2.83%. The average recovery was 99.97%( n =9). The limit of detection was 1.5 μg/mL. The host-guest complex binding constants were 964 and 905 mol-1 for ( R )-enantiomer and zolmitriptan,respectively. Conclusion:The method is suitable for the determination of ( R )-enantiomer in zolmitriptan and binding constants of zolmitriptan enantiomers to S-β-CD.