Phosphodiesterase 4 (PDE4) has been established as a drug target for inflammatory diseases of respiratory tract like asthma and chronic obstructive pulmonary disease. The selective inhibitors of PDE4B, a subtype of PDE4, are devoid of adverse effects like nausea and vomiting commonly associated with non-selective PDE4B inhibitors. This makes the development of PDE4B subtype selective inhibitors a desirable research goal. Thus, in the present study, molecular docking, molecular dynamic simulations and binding free energy were performed to explore potential selective PDE4B inhibitors based on ginger phenolic compounds. The results of docking studies indicate that some of the ginger phenolic compounds demonstrate higher selective PDE4B inhibition than existing selective PDE4B inhibitors. Additionally, 6-gingerol showed the highest PDE4B inhibitory activity as well as selectivity. The comparison of binding mode of PDE4B/6-gingerol and PDE4D/6-gingerol complexes revealed that 6-gingerol formed additional hydrogen bond and hydrophobic interactions with active site and control region 3 (CR3) residues in PDE4B, which were primarily responsible for its PDE4B selectivity. The results of binding free energy demonstrated that electrostatic energy is the primary factor in elucidating the mechanism of PDE4B inhibition by 6-gingerol. Dynamic cross-correlation studies also supported the results of docking and molecular dynamics simulation. Finally, a small library of molecules were designed based on the identified structural features, majority of designed molecules showed higher PDE4B selectivity than 6-gingerol. These results provide important structural features for designing new selective PDE4B inhibitors as anti-inflammatory drugs and promising candidates for synthesis and pre-clinical pharmacological investigations.
Edible bird's nest (EBN) is a high-value health food with various nutrients and bioactive components. With increasing demand for EBN, they are often adulterated with cheaper ingredients or falsely labeled by the origin information, thus harming consumer interests. In this study, high- and low-field nuclear magnetic resonance (HF/LF-NMR) technology combined with multivariate statistical analysis was used to identify the geographical marker of EBN from different origins and authenticate the adulterated EBN with various adulterants at different adulteration rates. Authentic EBN samples from Malaysia were used to simulate adulteration using gelatin (GL), agar (AG) and starch (ST) at 10 %, 20 %, 40 %, 60 %, 80 %, and 100 % w/w, respectively. The results showed significant differences in composition among EBN from different origins, with isocaproate and citric acid serving as geographical markers for Malaysia and Vietnam, respectively. Leucine, glutamic acid, and N-acetylglycoprotein serving as geographical markers for Indonesia. In addition, PLS model further verified the accuracy of origin identification of EBN. The LF-NMR results of adulteration EBN showed a linear correlation between the transverse relaxation (T2, S2) and the adulterated ratio. The OPLS-DA based on T2 spectra could accurately identify authentic EBN from adulterated with GL, AG and ST at 40 %, 20 %, and 20 %, respectively. Fisher discrimination model was able to differentiate at 20 %, 20 %, and 40 %, respectively. These results show that the 1H NMR combined with multivariate statistical analysis method could be a potential tool for the detection of origin and adulteration of EBN.