Purpose: Inhibition of dipeptidyl peptidase-IV (DPP-IV) is an effective therapy for treating type II diabetes (T2D) that has been widely applied in clinical practice. We aimed to evaluate the DPP-IV inhibitory properties of ginger protease hydrolysate (GPH) and propose a comprehensive approach to screen and evaluate DPP-IV inhibitors. Methods: We evaluated the in vitro inhibitory properties of fish skin gelatin hydrolysates produced by five proteases, namely, neutral protease, alkaline protease, bromelain, papain, and ginger protease, toward DPP-IV. We screened the most potent DPP-IV inhibitory peptide (DIP) using liquid chromatography-tandem mass spectrometry (LC-MS/MS) coupled with in silico analysis. Next, surface plasmon resonance (SPR) technology was innovatively introduced to explore the interactions between DPP-IV and DIP, as well as the IC₅₀. Furthermore, we performed oral administration of DIP in rats to study its in vivo absorption. Results: GPH displayed the highest degree of hydrolysis (20.37%) and DPP-IV inhibitory activity (65.18%). A total of 292 peptides from the GPH were identified using LC-MS/MS combined with de novo sequencing. Gly-Pro-Hyp-Gly-Pro-Pro-Gly-Pro-Gly-Pro (GPXGPPGPGP) was identified as the most potent DPP-IV inhibitory peptide after in silico screening (Peptide Ranker and molecular docking). Then, the in vitro study revealed that GPXGPPGPGP had a high inhibitory effect on DPP-IV (IC₅₀: 1012.3 ± 23.3 μM) and exhibited fast kinetics with rapid binding and dissociation with DPP-IV. In vivo analysis indicated that GPXGPPGPGP was not absorbed intact but partially, in the form of dipeptides and tripeptides. Conclusion: Overall, the results suggested that GPH would be a natural functional food for treating T2D and provided new ideas for searching and evaluating potential antidiabetic compounds. The obtained GPXGPPGPGP can be structurally optimized for in-depth evaluation in animal and cellular experiments.

Topiroxostat is a selective xanthine oxidoreductase (XOR) inhibitor for the management of hyperuricemia in patients with or without gout. In this work, we aim to employ the physiologically based pharmacokinetic (PBPK) model with the drug-target residence time model to predict and characterize both the pharmacokinetics (PK) and pharmacodynamics (PD) of topiroxostat in humans. The plasma concentration-time profile of topiroxostat was simulated based on drug properties and human physiology parameters. The predictive power of this PBPK model was then demonstrated by comparison of stimulated to observed pharmacokinetic parameters. The utility of the model was further demonstrated through predicting the oral absorption and disposition characteristics of topiroxostat in humans. Finally, by combining the PBPK model and the drug-target residence time model, we successfully predicted the target occupancy and built the relationship between PK and PD using in vitro, in vivo and in silico information. The results showed that topiroxostat exhibited significant in vivo pharmacological activity even after the complete clearance of this drug from the liver (target site), which may be due to the long residence time of the binary topiroxostat-XOR complex. This work may be helpful to guide future investigations of topiroxostat and also provides a novel strategy for PK/PD studies.

The accurate quantitative determination of affinity and binding kinetics (BK) for tight binding inhibition is extraordinary important from both the continuous optimization of compounds, particularly in developing structure-activity relationships (SAR), and the prediction of in vivo target occupancy (TO). Due to the unique properties for tight binding inhibition that the inhibitors are characterized by the ultrahigh-affinity, relatively fast association to the target enzyme combined with extremely slow dissociation of the inhibitor-enzyme binary complex, the classical steady state equilibrium methods are no longer valid. Here, we made several recommendations of how to design the optimal experiments and apply special mathematical calculation approaches to quantitatively evaluate the accurate affinity and BK as the examples of two tight binding inhibitors against the xanthine oxidase (XO), as well as compared the differences in the results calculated from the different data analytical methods and analyzed the influence of these differences on the XO engagement in human. Analysis of the results displayed that the accurate apparent dissociation constant (Ki*,app) was 0.2 ± 0.06 nM for topiroxotstat and was 0.45 ± 0.2 nM for febuxostat; that on-rate (kon) was (4.3 ± 1.1) × 106 M-1s-1 for topiroxotstat and was(133.3 ± 3.5) × 106 M-1s-1 for febuxostat, and off-rate (koff) was (1.0±0.2) × 10-5 s-1 for topiroxotstat and was ≤ 0.16 × 10-5 s-1for febuxostat. Moreover, there were significant differences in the Ki*,app and koff values estimated using the appropriate specialized methods for tight binding inhibition versus classical steady state equilibrium methods, with the substantial differences of 14-fold and 32-fold reduction for topiroxostat, respectively, and of 9.6-fold and ≥ 213-fold reduction for febuxostat, while the kon values remain the moderate differences for the two inhibitors. The obvious greater AUC of XO engagement time courses and longer durations of above 70% engagement by the appropriate specialized methods for tight binding inhibition were observed that the results display the differences of 70.1% and 88%, respectively for topiroxostat and of 38.1% and 35.0%, respectively for febuxostat in human liver cell than by classical steady state equilibrium methods. Again, our studies provide several valuable recommendations of the optimal experiment protocols and appropriate analytical approaches for accurately quantitatively assessing the affinity and BK parameters as well as demonstrate the ability of our recommended methods to generate reliable data for tight binding inhibitors against XO.

Red clover consists of the overground parts and inflorescence of Trifolium pratense L., a leguminous plant belonging to the genus Trifolium. It is widely distributed worldwide and has long been used in traditional medicine. In this study, a combination approach using UPLC-MS and network pharmacology was applied to explore the quality control markers for the quality assessments of red clover. Firstly, UPLC-MS was used to identify the compounds in different parts of red clover. Twenty-eight compounds were totally identified. According to the traditional clinical efficacy of red clover, a compound-target-function network was constructed by network pharmacology to discover the main active compounds based on the identified compounds. Nine compounds of chlorogenic acid, daidzin, calycosin-7-O-β-d-glucoside, genistin, ononin, daidzein, genistein, formononetin, and biochanin A were filtrated and further confirmed in rat plasma in view of the blood-absorbed components taking effects. Finally, a novel method for simultaneously detecting the nine quality control markers was developed by UPLC-QQQ-MS in an effort to assess the quality of red clover. For all samples, the average contents of the nine compounds measured from high to low consist of formononetin, ononin, biochanin A, genistin, daidzin, calycosin-7-O-β-d-glucoside, genistein, daidzein, and chlorogenic acid. The samples from Gansu province showed the best quality in the three producing areas This study provides new strategies to explore the quality control markers and develops a novel method for the quality assessment of red clover.

This study aimed to apply a physiologically based pharmacokinetic (PBPK) model to predict optimal dosing regimens of pazopanib (PAZ) for safe and effective administration when co-administered with CYP3A4 inhibitors, acid-reducing agents, food, and administered in patients with hepatic impairment. Here, we have successfully developed the population PBPK model and the predicted PK variables by this model matched well with the clinically observed data. Most ratios of prediction to observation were between 0.5 and 2.0. Suitable dosage modifications of PAZ have been identified using the PBPK simulations in various situations, i.e., 200 mg once daily (OD) or 100 mg twice daily (BID) when co-administered with the two CYP3A4 inhibitors, 200 mg BID when simultaneously administered with food or 800 mg OD when avoiding food uptake simultaneously. Additionally, the PBPK model also suggested that dosing does not need to be adjusted when co-administered with esomeprazole and administration in patients with wild hepatic impairment. Furthermore, the PBPK model also suggested that PAZ is not recommended to be administered in patients with severe hepatic impairment. In summary, the present PBPK model can determine the optimal dosing adjustment recommendations in multiple clinical uses, which cannot be achieved by only focusing on AUC linear change of PK.