Insights into the Inhibitory Mechanism of Viniferifuran on Xanthine Oxidase by Multiple Spectroscopic Techniques and Molecular Docking.

Viniferifuran was investigated for its potential to inhibit the activity of xanthine oxidase (XO), a key enzyme catalyzing xanthine to uric acid. An enzyme kinetics analysis showed that viniferifuran possessed a strong inhibition on XO in a typical anti-competitive manner with an IC50 value of 12.32 µM (IC50 for the first-line clinical drug allopurinol: 29.72 µM). FT-IR and CD data analyses showed that viniferifuran could induce a conformational change of XO with a decrease in the α-helix and increases in the ß-sheet, ß-turn, and random coil structures. A molecular docking analysis revealed that viniferifuran bound to the amino acid residues located within the activity cavity of XO by a strong hydrophobic interaction (for Ser1214, Val1011, Phe914, Phe1009, Leu1014, and Phe649) and hydrogen bonding (for Asn768, Ser876, and Tyr735). These findings suggested that viniferifuran might be a promising XO inhibitor with a favorable mechanism of action.

Discovery of 2-(isoxazol-5-yl)phenyl 3,4-dihydroxybenzoate as a potential inhibitor for the Wnt/ß-catenin pathway.

Carnosic acid could disrupt the ß-catenin/BCL9 protein-protein interaction and inhibit ß-catenin dependent transcription, thereby reduce the incidence of colorectal cancer induced by abnormal activation of Wnt/ß-catenin signalling pathway. However, its activity was weak (IC50 for SW480: 28.2 ± 2.05 µM) and total synthesis was difficult. During the structural simplification of natural products, S0 was revealed to be the basic pharmacophore of carnosic acid. Subsequent structural optimization of S0 led to the discovery of S11 as a possible anticancer agent with prominent proliferation inhibition effect (IC50 for SW480: 9.56 ± 0.91 µM) and best selectivity index (SI = 3.0) against Wnt hyperactive cancer cells. Futher mechanism investigation through TOP/FOP dual luciferase reporter assay, immunofluorescence, co-immunoprecipitation, microscale thermophoresis, downstream oncoprotein expression and cell apoptosis showed that compound S11 could significantly inhibit the proliferation of SW480 cells via obvioudsly decreasing the nucleus translocation of ß-catenin and effectively disrupting ß-catenin/BCL9 protein-protein interaction. Additionally, cell migration, molecule docking, in vitro stability and solubility assays were also conducted. Overall, S11 was worthy of in-depth study as a potential inhibitor for the Wnt/ß-catenin pathway and its discovery also proved that the structural simplification of natural products was still one of the effective methods to find new lead compounds or candidate drugs.

Spatiotemporal analysis of medical resource deficiencies in the U.S. under COVID-19 pandemic.

Coronavirus disease 2019 (COVID-19) was first identified in December 2019 in Wuhan, China as an infectious disease, and has quickly resulted in an ongoing pandemic. A data-driven approach was developed to estimate medical resource deficiencies due to medical burdens at county level during the COVID-19 pandemic. The study duration was mainly from February 15, 2020 to May 1, 2020 in the U.S. Multiple data sources were used to extract local population, hospital beds, critical care staff, COVID-19 confirmed case numbers, and hospitalization data at county level. We estimated the average length of stay from hospitalization data at state level, and calculated the hospitalized rate at both state and county level. Then, we developed two medical resource deficiency indices that measured the local medical burden based on the number of accumulated active confirmed cases normalized by local maximum potential medical resources, and the number of hospitalized patients that can be supported per ICU bed per critical care staff, respectively. Data on medical resources, and the two medical resource deficiency indices are illustrated in a dynamic spatiotemporal visualization platform based on ArcGIS Pro Dashboards. Our results provided new insights into the U.S. pandemic preparedness and local dynamics relating to medical burdens in response to the COVID-19 pandemic.