1-Alkyl-3-amino-5-aryl-1H-[1,2,4]triazoles: novel synthesis via cyclization of N-acyl-S-methylisothioureas with alkylhydrazines and their potent corticotropin-releasing factor-1 (CRF(1)) receptor antagonist activities.

Cyclizations of alkylhydrazines with N-acyl-S-methylisothioureas, readily synthesized from acyl chlorides, sodium thioisocyanate, dialkylamines then methyl iodide in a one-pot reaction, gave 1-alkyl-3-dialkylamino-5-phenyltriazoles 7 as major products. The regioisomers were assigned through the use of NOE NMR experiments. While bearing a N-bis(cyclopropyl)methyl-N-propylamino group, this series of compounds shows very good binding affinity on the human CRF₁ receptor. Among them, 1-methyl-3-[N-bis(cyclopropyl)methyl-N-propylamino]-5-(2,4-dichlorophenyl)-1H-[1,2,4]triazole 7a had the best binding affinity for the CRF₁ receptor (K_i=9 nM).     

Screening of Drug Metabolizing Enzymes for the Ginsenoside Compound K In Vitro: An Efficient Anti-Cancer Substance Originating from Panax Ginseng

Ginsenoside compound K (CK), a rare ginsenoside originating from Panax Ginseng, has been found to possess unique pharmacological activities specifically as anti-cancers. However, the role of cytochrome P450s (CYPs) in the metabolism of CK is unclear. In this study, we screened the CYPs for the metabolism of CK in vitro using human liver microsomes (HLMs) or human recombinant CYPs. The results showed that CK inhibited the enzyme activities of CYP2C9 and CYP3A4 in the HLMs. The K_m and V_max values of CK were 84.20±21.92 μM and 0.28±0.04 nmol/mg protein/min, respectively, for the HLMs; 34.63±10.48 μM and 0.45±0.05 nmol/nmol P450/min, respectively, for CYP2C9; and 27.03±5.04 μM and 0.68±0.04 nmol/nmol P450/min, respectively, for CYP3A4. The IC₅₀ values were 16.00 μM and 9.83 μM, and K_i values were 14.92 μM and 11.42μM for CYP2C9 and CYP3A4, respectively. Other human CYP isoforms, including CYP1A2, CYP2A6, CYP2D6, CYP2E1, and CYP2C19, showed minimal or no effect on CK metabolism. The results suggested that CK was a substrate and also inhibitors for both CYP2C9 and CYP3A4. Patients using CK in combination with therapeutic drugs that are substrates of CYP2C9 and CYP3A4 for different reasons should be careful, although the inhibiting potency of CK is much poorer than that of enzyme-specific inhibitors.     

In memoriam: Professor Ray WU

<正>During the Chinese New Year holidays in 2008, Professor Zhang Nai-Heng, former chair of the Department of Biochemistry, Beijing Medical College, informed me of the sad news that Professor Ray Wu had passed away in Ithaca, New York on     

Probing the U-Shaped Conformation of Caveolin-1 in a Bilayer

Caveolin induces membrane curvature and drives the formation of caveolae that participate in many crucial cell functions such as endocytosis. The central portion of caveolin-1 contains two helices (H1 and H2) connected by a three-residue break with both N- and C-termini exposed to the cytoplasm. Although a U-shaped configuration is assumed based on its inaccessibility by extracellular matrix probes, caveolin structure in a bilayer remains elusive. This work aims to characterize the structure and dynamics of caveolin-1 (D82–S136; Cav1_82–136) in a DMPC bilayer using NMR, fluorescence emission measurements, and molecular dynamics simulations. The secondary structure of Cav1_82–136 from NMR chemical shift indexing analysis serves as a guideline for generating initial structural models. Fifty independent molecular dynamics simulations (100 ns each) are performed to identify its favorable conformation and orientation in the bilayer. A representative configuration was chosen from these multiple simulations and simulated for 1 μs to further explore its stability and dynamics. The results of these simulations mirror those from the tryptophan fluorescence measurements (i.e., Cav1_82–136 insertion depth in the bilayer), corroborate that Cav1_82–136 inserts in the membrane with U-shaped conformations, and show that the angle between H1 and H2 ranges from 35 to 69°, and the tilt angle of Cav1_82–136 is 27 ± 6°. The simulations also reveal that specific faces of H1 and H2 prefer to interact with each other and with lipid molecules, and these interactions stabilize the U-shaped conformation.     

Extracellular vesicles in bone and tooth: A state-of-art paradigm in skeletal regeneration

Bone and tooth, fundamental parts of the craniofacial skeleton, are anatomically and developmentally interconnected structures. Notably, pathological processes in these tissues underwent together and progressed in multilevels. Extracellular vesicles (EVs) are cell-released small organelles and transfer proteins and genetic information into cells and tissues. Although EVs have been identified in bone and tooth, particularly EVs have been identified in the bone formation and resorption, the concrete roles of EVs in bone and tooth development and diseases remain elusive. As such, we review the recent progress of EVs in bone and tooth to highlight the novel findings of EVs in cellular communication, tissue homeostasis, and interventions. This will enhance our comprehension on the skeletal biology and shed new light on the modulation of skeletal disorders and the potential of genetic treatment.     

Predicting Metabolic Pathways of Small Molecules and Enzymes Based on Interaction Information of Chemicals and Proteins

Metabolic pathway analysis, one of the most important fields in biochemistry, is pivotal to understanding the maintenance and modulation of the functions of an organism. Good comprehension of metabolic pathways is critical to understanding the mechanisms of some fundamental biological processes. Given a small molecule or an enzyme, how may one identify the metabolic pathways in which it may participate? Answering such a question is a first important step in understanding a metabolic pathway system. By utilizing the information provided by chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions, a novel method was proposed by which to allocate small molecules and enzymes to 11 major classes of metabolic pathways. A benchmark dataset consisting of 3,348 small molecules and 654 enzymes of yeast was constructed to test the method. It was observed that the first order prediction accuracy evaluated by the jackknife test was 79.56% in identifying the small molecules and enzymes in a benchmark dataset. Our method may become a useful vehicle in predicting the metabolic pathways of small molecules and enzymes, providing a basis for some further analysis of the pathway systems.