Medicinal herbs Oenanthe javanica (Blume) DC., Casuarina equisetifolia L. and Sorghum bicolor (L.) Moench protect human cells from MPP+ damage via inducing FBXO7 expression.

BACKGROUND: The F-box protein 7 (FBXO7) mutations have been identified in families with early-onset parkinsonism and pyramidal tract signs, and designated as PARK15. In addition, FBXO7 mutations were found in typical and young onset Parkinson's disease (PD). Evidence has also shown that FBXO7 plays an important role in the development of dopaminergic neurons and increased stability and overexpression of FBXO7 may be beneficial to PD. PURPOSE: We screened extracts of medicinal herbs to enhance FBXO7 expression for neuroprotection in MPP+-treated cells. METHODS: Promoter reporter assay in HEK-293 cells was used to examine the cis/trans elements controlling FBXO7 expression and to screen extracts of medicinal herbs enhancing FBXO7 expression. MTT assay was performed to assess cell viability of MPP+-treated HEK-293/SH-SY5Y cells. In addition, proteasome activity, mitochondrial membrane potential and FBXO7/TRAF2/GATA2 protein expression were evaluated. RESULTS: We demonstrated that -202--57 region of the FBXO7 promoter is likely to contain sequences that are bound by positive trans protein factors to activate FBXO7 expression and GATA2 is the main trans protein factor enhancing FBXO7 expression. Extracts of medicinal herbs Oenanthe javanica (Blume) DC. (Umbelliferae), Casuarina equisetifolia L. (Casuarinaceae), and Sorghum bicolor (L.) Moench (Gramineae) improved cell viability of both MPP+-treated HEK-293 and SH-SY5Y cells, rescued proteasome activity in MPP+-treated HEK-293 cells, and restored mitochondrial membrane potential in MPP+-treated SH-SY5Y cells. These protection effects of herbal extracts are acting through enhancing FBXO7 and decreasing TRAF2 expression, which is probably mediated by GATA2 induction. CONCLUSION: Collectively, our study provides new targets, FBXO7 and its regulator GATA2, for the development of potential treatments of PD.

Epicatechin isolated from Tripterygium wilfordii extract reduces tau-GFP-induced neurotoxicity in zebrafish embryo through the activation of Nrf2.

Tau plays important roles in the assembly and stabilization of the microtubule structure to facilitate axonal transport in mammalian brain. The intracellular tau aggregates to form paired helical filaments leading to neurodegenerative disorders, collectively called tauopathies. In our previous report, we established a zebrafish model to express tau-GFP to induce neuronal death, which could be directly traced in vivo. Recently, we used this model to screen 400 herbal extracts and found 45 of them to be effective on reducing tau-GFP-induced neuronal death. One of the effective herbal extracts is the Tripterygium wilfordii stem extract. HPLC analysis and functional assay demonstrated that epicatechin (EC) is the major compound of Tripterygium wilfordii stem extract to decrease the neurotoxicity induced by tau-GFP. Using a luciferase reporter assay in the zebrafish, we confirmed that EC could activate Nrf2-dependent antioxidant responses to significantly increase the ARE-controlled expression of luciferase reporter gene. These data suggest that EC from the Tripterygium wilfordii stem extract could diminish tau-GFP-induced neuronal death through the activation of Nrf2.

Development of novel 3D-QSAR combination approach for screening and optimizing B-Raf inhibitors in silico.

B-Raf is a member of the RAF family of serine/threonine kinases: it mediates cell division, differentiation, and apoptosis signals through the RAS-RAF-MAPK pathway. Thus, B-Raf is of keen interest in cancer therapy, such as melanoma. In this study, we propose the first combination approach to integrate the pharmacophore (PhModel), CoMFA, and CoMSIA models for B-Raf, and this approach could be used for screening and optimizing potential B-Raf inhibitors in silico. Ten PhModels were generated based on the HypoGen BEST algorithm with the flexible fit method and diverse inhibitor structures. Each PhModel was designated to the alignment rule and screening interface for CoMFA and CoMSIA models. Therefore, CoMFA and CoMSIA models could align and recognize diverse inhibitor structures. We used two quality validation methods to test the predication accuracy of these combination models. In the previously proposed combination approaches, they have a common factor in that the number of training set inhibitors is greater than that of testing set inhibitors. In our study, the 189 known diverse series B-Raf inhibitors, which are 7-fold the number of training set inhibitors, were used as a testing set in the partial least-squares validation. The best validation results were made by the CoMFA09 and CoMSIA09 models based on the Hypo09 alignment model. The predictive r(2)(pred) values of 0.56 and 0.56 were derived from the CoMFA09 and CoMSIA09 models, respectively. The CoMFA09 and CoMSIA09 models also had a satisfied predication accuracy of 77.78% and 80%, and the goodness of hit test score of 0.675 and 0.699, respectively. These results indicate that our combination approach could effectively identify diverse B-Raf inhibitors and predict the activity.