In this study, a series of 4-[(quinolin-4-yl)amino]benzamide derivatives as the novel anti-influenza agents were designed and synthesized. Cytotoxicity assay, cytopathic effect assay and plaque inhibition assay were performed to evaluate the anti-influenza virus A/WSN/33 (H1N1) activity of the target compounds. The target compound G07 demonstrated significant anti-influenza virus A/WSN/33 (H1N1) activity both in cytopathic effect assay (EC50 = 11.38 ± 1.89 µM) and plaque inhibition assay (IC50 = 0.23 ± 0.15 µM). G07 also exhibited significant anti-influenza virus activities against other three different influenza virus strains A/PR/8 (H1N1), A/HK/68 (H3N2) and influenza B virus. According to the result of ribonucleoprotein reconstitution assay, G07 could interact well with ribonucleoprotein with an inhibition rate of 80.65% at 100 µM. Furthermore, G07 exhibited significant activity target PA−PB1 subunit of RNA polymerase according to the PA−PB1 inhibitory activity prediction by the best pharmacophore Hypo1. In addition, G07 was well drug-likeness based on the results of Lipinski’s rule and ADMET prediction. All the results proved that 4-[(quinolin-4-yl)amino]benzamide derivatives could generate potential candidates in discovery of anti-influenza virus agents.
Chemical investigation of Fritillaria verticillata Willd. led to the isolation of eight novel isosteroidal alkaloids (1-4, 6, 9-11) and four known alkaloids (5, 7-8, 12), including three unprecedented cis-fused D/E (13α, 17α) cevanine alkaloids (1-3), one rarely cis-fused E/F (22α) cevanine alkaloid (6), and one uncommon 5β-jervine-type isosteroidal alkaloid featuring a cis-fused A/B ring moiety (11). In order to establish the structures of 1, the calculated NMR with DP4+ evaluation was applied from the plausible structure candidates. The characteristic proton signals for distinguishing D/E conjunction of cevanine alkaloids were summarized. In addition, some proton and carbon signals α to nitrogen in 6 and 7 are unobservable due to the 14 N nuclear quadrupolar relaxation, based on the NMR experiments in different solvents, calculated NMR method and X-ray technology, their structures were determined. The NMR characteristics of cevanine alkaloids to distinguish orientation of long-pair on nitrogen atom with β-hydroxyl at C-20 were also concluded. The anti-inflammatory effects of compounds 1 and 4 were evaluated in LPS-activated RAW 264.7 macrophages. Compound 4 decreased LPS-induced releases of IL-1β and IL-17α in RAW264.7 cells in a dose-dependent manner. Further mechanistic study revealed that 4 suppressed the phosphorylation of IκBα and p65 subunit to regulate the NF-κB signaling pathway.
CD73, as a surface enzyme anchored on the outside of the cell membrane via glycosylphosphatidylinositol (GPI), can convert the AMP in the tumor cell microenvironment into adenosine to promote the growth of tumor cells. It has been overexpressed in many different types of human tumors, such as gastric cancer, pancreatic cancer, liver cancer and other tumor cells. Therefore, targeted inhibitors of CD73 are considered as potential tumor treatment methods. Due to the low bioavailability of nucleoside CD73 inhibitors, it is necessary to develop new inhibitors. In this study, through molecular docking, three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular dynamics (MD) simulations, a series of CD73 inhibitors were calculated and studied to reveal their structure-activity relationships. Through molecular docking studies, explore the possible mode of interaction between inhibitors and protein. Subsequently, a 3D-QSAR model was established by comparative molecular eld analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). For the best CoMFA model, the Q 2 and R 2 values are 0.708 and 0.983, respectively, while for the best CoMSIA model, the Q 2 and R 2 values are 0.809 and 0.992, respectively. In addition, the stability of the complex formed by the two inhibitors and CD73 was evaluated by molecular dynamics simulation, and the results are consistent with the results of molecular docking and 3D-QSAR research. Finally, the binding free energy was calculated by the surface area method (MM-GBSA), and the results are consistent with the activities that Van Der Waals and Coulomb contribute the most during the binding process of the molecule to the CD73 protein. In conclusion, our research provides valuable information for the further development of CD73 inhibitors.
The interactions of Toll‐like receptor 4 (TLR4) with competitive inhibitors were investigated by a combined ligand‐based and target‐based approach. Firstly, the ligand‐based pharmacophore model of the reported TLR4 inhibitors was constructed by utilizing the common feature method, which included three hydrophobic groups and a hydrogen bond receptor. The Schrödinger software suite glide module was used to dock inhibitors with proteins and verify the importance of these four interaction points from the target level. Then, molecular dynamics, alanine scanning mutagenesis, and binding free energy calculation were used to identify the key amino acids in the binding mode. In addition, blind docking proved that the TLR4 inhibitor does not bind to TLR4 itself like other TLR family proteins. Based on this, we also screened a class of sesquiterpene coumarins which possibly have TLR4 inhibitory activity and will conduct a detailed study later. Together, this study revealed the interactions between TLR4 protein and its competitive inhibitors, which shed light on better access for developing its novel inhibitors.
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