Catalytically Relevant Organocopper(III) Complexes Formed through Aryl-Radical-Enabled Oxidative Addition.

Stepwise oxidative addition of copper(I) complexes to form copper(III) species via single electron transfer (SET) events has been widely proposed in copper catalysis. However, direct observation and detailed investigation of these fundamental steps remain elusive owing largely to the typically slow oxidative addition rate of copper(I) complexes and the instability of the copper(III) species. We report herein a novel aryl-radical-enabled stepwise oxidative addition pathway that allows for the formation of well-defined alkyl-CuIII species from CuI complexes. The process is enabled by the SET from a CuI species to an aryl diazonium salt to form a CuII species and an aryl radical. Subsequent iodine abstraction from an alkyl iodide by the aryl radical affords an alkyl radical, which then reacts with the CuII species to form the alkyl-CuIII complex. The structure of resultant [(bpy)CuIII(CF3)2(alkyl)] complexes has been characterized by NMR spectroscopy and X-ray crystallography. Competition experiments have revealed that the rate at which different alkyl iodides undergo oxidative addition is consistent with the rate of iodine abstraction by carbon-centered radicals. The CuII intermediate formed during the SET process has been identified as a four-coordinate complex, [CuII(CH3CN)2(CF3)2], through electronic paramagnetic resonance (EPR) studies. The catalytic relevance of the high-valent organo-CuIII has been demonstrated by the C-C bond-forming reductive elimination reactivity. Finally, localized orbital bonding analysis of these formal CuIII complexes indicates inverted ligand fields in σ(Cu-CH2) bonds. These results demonstrate the stepwise oxidative addition in copper catalysis and provide a general strategy to investigate the elusive formal CuIII complexes.

Revealing the Photophysical and Photochemical Reaction Processes of Carprofen in Different Solutions via Ultrafast Femtosecond to Nanosecond Transient Absorption.

Carprofen (CP), one kind of a nonsteroidal anti-inflammatory drug, exhibits phototoxic side effects in physiology, while its phototoxic mechanism is ambiguous. To uncover CP's photophysical and photochemical reaction processes, femtosecond to nanosecond transient absorption spectroscopies were employed to directly detect excited states and transient intermediates of CP upon UV irradiation in pure acetonitrile (MeCN), MeCN/water 1:1, and acid/alkaline buffer solutions. The transient absorption data together with DFT calculations were integrated to elucidate mechanisms for photochemical reactions of CP in different solutions. The associated photophysical and photochemical reaction pathways are dependent on various solution environments. In a pure MeCN solvent, CP is excited to a singlet state (S1) and rapidly interacts with the solvent to proceed solvent rearrangement (SR). It then undergoes vibrational cooling (VC) and proceeds intersystem crossing (ISC) to produce the lowest triplet state (3CP). 3CP finally decays to the ground state. While in a MeCN/water 1:1 solution, deprotonated S1 of CP experiences SR and VC processes, and then it is promoted to a deprotonated triplet state (3CP-). 3CP- undergoes the parallel reactions: dechlorination to a phenyl radical (2CP-) and decarboxylation to a T1 anion (3CP-(de-CO2)). Finally, both intermediates produce the radical anion species 2CP-(de-CO2). In a pH = 7.4 (MeCN/PBS 1:1) solution, 3CP- can be converted into 2CP-(de-CO2) more quickly. Interestingly, we found that the dechlorination step can be promoted in an alkaline solution. Phenyl and chlorine radicals produced in an aqueous solution may be the root cause of the drug's harmful side effects on the human body. This may be useful to guide the design of related CP drugs with minimal phototoxicity in the pharmaceutical process.

Early Second-Trimester Peptidomic Identification of Serum Peptides for Potential Prediction of Gestational Diabetes Mellitus.

BACKGROUND/AIMS: Early screening and diagnosis is important for minimizing gestational adverse outcomes. Routine screening of gestational diabetes mellitus (GDM) at 24-28 weeks with 75 g oral glucose challenge test (OGCT) leaves limited time for intervention and prevention. This study aims to analyze maternal serum peptides in the early second-trimester for prediction of gestational diabetes mellitus (GDM). METHODS: Serum samples were collected from 16-18-week pregnant women that visited Nanjing Maternity and Child Health Care Hospital from April to August 2015. According to gestational outcome with or without GDM in late pregnancy, 200 of serum samples from GDM mothers and controls were randomly divided into two subgroups. Peptidomic identification of serum peptides was performed by combining ultrafiltration and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to investigate the differentially-expressed peptides between two groups. RESULTS: A total of 297 identified peptides, originating from 228 proteins, were significantly differentially expressed in the GDM group compared with control. These precursor proteins may play critical roles in cell death of cortical neurons, elongation of cellular protrusions, and stabilization of microtubules. Major networks identified included those involving lipid metabolism, molecular transport and small molecule biochemistry. CONCLUSION: We provide for the first time a validated peptidome profile of early second-trimester serum in normal and GDM mothers, and we investigated the potential serum biomarkers for GDM. We concluded that 297 peptides could serve as potential biomarkers for GDM.

QSAR modeling and in silico design of small-molecule inhibitors targeting the interaction between E3 ligase VHL and HIF-1α.

Protein-protein interactions (PPIs) have attracted much attention recently because of their preponderant role in most biological processes. The prevention of the interaction between E3 ligase VHL and HIF-1[Formula: see text] may improve tolerance to hypoxia and ameliorate the prognosis of many diseases. To obtain novel potent inhibitors of VHL/HIF-1[Formula: see text] interaction, a series of hydroxyproline-based inhibitors were investigated for structural optimization using a combination of QSAR modeling and molecular docking. Here, 2D- and 3D-QSAR models were developed by genetic function approximation (GFA) and comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) methods, respectively. The top-ranked models with strict validation revealed satisfactory statistical parameters (CoMFA with [Formula: see text], 0.637; [Formula: see text], 0.955; [Formula: see text], 0.944; CoMSIA with [Formula: see text], 0.649; [Formula: see text], 0.954; [Formula: see text], 0.911; GFA with [Formula: see text], 0.721; [Formula: see text], 0.801; [Formula: see text], 0.861). The selected five 2D-QSAR descriptors were in good accordance with the 3D-QSAR results, and contour maps gave the visualization of feature requirements for inhibitory activity. A new diverse molecular database was created by molecular fragment replacement and BREED techniques for subsequent virtual screening. Eventually, 31 novel hydroxyproline derivatives stood out as potential VHL/HIF-1[Formula: see text] inhibitors with favorable predictions by the CoMFA, CoMSIA and GFA models. The reliability of this protocol suggests that it could also be applied to the exploration of lead optimization of other PPI targets.

Identification of Covalent Binding Sites Targeting Cysteines Based on Computational Approaches.

Covalent drugs have attracted increasing attention in recent years due to good inhibitory activity and selectivity. Targeting noncatalytic cysteines with irreversible inhibitors is a powerful approach for enhancing pharmacological potency and selectivity because cysteines can form covalent bonds with inhibitors through their nucleophilic thiol groups. However, most human kinases have multiple noncatalytic cysteines within the active site; to accurately predict which cysteine is most likely to form covalent bonds is of great importance but remains a challenge when designing irreversible inhibitors. In this work, FTMap was first applied to check its ability in predicting covalent binding site defined as the region where covalent bonds are formed between cysteines and irreversible inhibitors. Results show that it has excellent performance in detecting the hot spots within the binding pocket, and its hydrogen bond interaction frequency analysis could give us some interesting instructions for identification of covalent binding cysteines. Furthermore, we proposed a simple but useful covalent fragment probing approach and showed that it successfully predicted the covalent binding site of seven targets. By adopting a distance-based method, we observed that the closer the nucleophiles of covalent warheads are to the thiol group of a cysteine, the higher the possibility that a cysteine is prone to form a covalent bond. We believe that the combination of FTMap and our distance-based covalent fragment probing method can become a useful tool in detecting the covalent binding site of these targets.

Down-regulated expressed protein HMGB3 inhibits proliferation and migration, promotes apoptosis in the placentas of fetal growth restriction.

Fetal growth restriction (FGR) is one of the major complications of pregnancy, which can lead to serious short-term and long-term diseases. High-mobility group box 3 (HMGB3) has been found to contribute to the development of many cancers. However, the role of HMGB3 in the pathogenesis of FGR is blank. Here, we measured the expression level of HMGB3 in the placenta tissues of six normal pregnancies and five FGR patients by western blotting and quantitative real-time polymerase chain reaction (qRT-PCR). CCK8 assay, transwell assay and flow cytometry were used to detect the functional effects of overexpression and silencing of HMGB3 on the HTR8/SVneo trophoblast cell line. The results showed that the protein levels of HMGB3 were significantly decreased in FGR placentas compared to normal controls, while mRNA levels of HMGB3 were not significantly altered. Furthermore, when overexpressed of protein HMGB3 of the trophoblast cells, the proliferation and migration abilities were significantly promoted, and the apoptosis abilities of these cells were statistically inhibited. Cell functional experiments showed the opposite results when the expression of HMGB3 was silent. And the expression of cell function-related genes PCNA, Ki67, Tp53, Bax, MMP-2 and E-cadherin was observed to show corresponding changes by qRT-PCR. The results of mass spectrometry showed that HMGB3 may directly or indirectly interact with 71 proteins. In summary, our results indicated that HMGB3 might be of very great significance to the pathogenesis of FGR and might play the role by leading the dysfunction of placental villous trophoblast cells and through the interaction with some other proteins.

Virtual Screening Strategy Combined Bayesian Classification Model, Molecular Docking for Acetyl-CoA Carboxylases Inhibitors.

INTRODUCTION: Acetyl-CoA Carboxylases (ACC) have been an important target for the therapy of metabolic syndrome, such as obesity, hepatic steatosis, insulin resistance, dyslipidemia, non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), type 2 diabetes (T2DM), and some other diseases. METHODS: In this study, virtual screening strategy combined with Bayesian categorization modeling, molecular docking and binding site analysis with protein ligand interaction fingerprint (PLIF) was adopted to validate some potent ACC inhibitors. First, the best Bayesian model with an excellent value of Area Under Curve (AUC) value (training set AUC: 0.972, test set AUC: 0.955) was used to screen compounds of validation library. Then the compounds screened by best Bayesian model were further screened by molecule docking again. RESULTS: Finally, the hit compounds evaluated with four percentages (1%, 2%, 5%, 10%) were verified to reveal enrichment rates for the compounds. The combination of the ligandbased Bayesian model and structure-based virtual screening resulted in the identification of top four compounds which exhibited excellent IC 50 values against ACC in top 1% of the validation library. CONCLUSION: In summary, the whole strategy is of high efficiency, and would be helpful for the discovery of ACC inhibitors and some other target inhibitors.

In silico Prediction of Inhibitory Constant of Thrombin Inhibitors Using Machine Learning.

BACKGROUND: Thrombin is the central protease of the vertebrate blood coagulation cascade, which is closely related to cardiovascular diseases. The inhibitory constant Ki is the most significant property of thrombin inhibitors. METHOD: This study was carried out to predict Ki values of thrombin inhibitors based on a large data set by using machine learning methods. Taking advantage of finding non-intuitive regularities on high-dimensional datasets, machine learning can be used to build effective predictive models. A total of 6554 descriptors for each compound were collected and an efficient descriptor selection method was chosen to find the appropriate descriptors. Four different methods including multiple linear regression (MLR), K Nearest Neighbors (KNN), Gradient Boosting Regression Tree (GBRT) and Support Vector Machine (SVM) were implemented to build prediction models with these selected descriptors. RESULTS: The SVM model was the best one among these methods with R2=0.84, MSE=0.55 for the training set and R2=0.83, MSE=0.56 for the test set. Several validation methods such as yrandomization test and applicability domain evaluation, were adopted to assess the robustness and generalization ability of the model. The final model shows excellent stability and predictive ability and can be employed for rapid estimation of the inhibitory constant, which is full of help for designing novel thrombin inhibitors.

The influence of different debridement methods on the prognosis of elderly patients with diabetic foot ulcers and sepsis.

BACKGROUND: We evaluated the influence of different debridement methods on the prognosis of elderly patients with diabetic foot ulcers complicated with sepsis. METHODS: Retrospective study was adopted to study 65 hospitalized elderly patients with Wagner Grade-4 diabetic foot ulcer and sepsis in Vascular Disease Department of Shanghai TCM-Integrated Hospital. Thirty-two cases were included in the thorough debridement group and the other 33 were included in the minor debridement group. We compared the mortality rates on the 7th day and 14th day after debridement, and monitored changes of sepsis-related organ failure assessment (SOFA) Score as well as C-reactive protein (CRP), procalcitonin (PCT) and D-Dimer (D-D) levels. Cox regression analysis and Kaplan-Meier analysis were used to analyze the mortality rates. Binary logistic regression analysis was employed to screen relevant prognostic factors to see the prognostic value of SOFA Score, PCT and D-D. RESULTS: Fatality rates of the thorough debridement group on the 7th day and 14th day of the debridement were higher than those in the minor debridement group and such a difference has statistical significance. The CRP, PCT, and D-D of patients within seven days after thorough debridement were obviously higher than those of patients after minor debridement. CONCLUSIONS: Damage control should be provided for elderly patients with diabetic foot ulcers and sepsis when debridement is being performed. Palliative debridement methods such as small-scale incision and drainage are less likely to affect systematic inflammatory response and coagulation function, and thus can buy time for further treatment to improve clinical effect.

The effect of dietary soyabean isoflavones on photodynamic therapy in K562 leukemia cells.

The soyabean isoflavones genistein (GEN) and daidzein (DA) are popular presented in diet. Isoflavones have a variety of biological activities including antioxidant and anticancer properties. On account of its antioxidant activity, isoflavones might protect cancer cells from free radical damage in photodynamic (PDT) during which reactive oxygen species (ROS) production was stimulated leading to irreversible tumor cell injury. In this study, the influence of GEN and DA on K562 cells in 5-aminolevulinic acid (ALA)-based PDT was demonstrated. The results showed that GEN inhibited cell proliferation and enhance cell apoptosis, lipid peroxidation, and DNA damage in ALA-PDT on K562 cells. However, DA did not enhance cell apoptosis, lipid peroxidation, and DNA damage in ALA-PDT. In conclusion, the results suggested that soy consumption during PDT did not decrease the effectiveness of cancer therapy on malignant cells.