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.

A New Era for Cancer Target Therapies: Applying Systems Biology and Computer-Aided Drug Design to Cancer Therapies.

In recent years, many systems biology approaches have been used with various cancers. The materials described here can be used to build bases to discover novel cancer therapy targets in connection with computer-aided drug design (CADD). A deeper understanding of the mechanisms of cancer will provide more choices and correct strategies in the development of multiple target drug therapies, which is quite different from the traditional cancer single target therapy. Targeted therapy is one of the most powerful strategies against cancer and can also be applied to other diseases. Due to the large amount of progress in computer hardware and the theories of computational chemistry and physics, CADD has been the main strategy for developing novel drugs for cancer therapy. In contrast to traditional single target therapies, in this review we will emphasize the future direction of the field, i.e., multiple target therapies. Structure-based and ligand-based drug designs are the two main topics of CADD. The former needs both 3D protein structures and ligand structures, while the latter only needs ligand structures. Ordinarily it is estimated to take more than 14 years and 800 million dollars to develop a new drug. Many new CADD software programs and techniques have been developed in recent decades. We conclude with an example where we combined and applied systems biology and CADD to the core networks of four cancers and successfully developed a novel cocktail for drug therapy that treats multiple targets.

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.

Multiple target drug cocktail design for attacking the core network markers of four cancers using ligand-based and structure-based virtual screening methods.

BACKGROUND: Computer-aided drug design has a long history of being applied to discover new molecules to treat various cancers, but it has always been focused on single targets. The development of systems biology has let scientists reveal more hidden mechanisms of cancers, but attempts to apply systems biology to cancer therapies remain at preliminary stages. Our lab has successfully developed various systems biology models for several cancers. Based on these achievements, we present the first attempt to combine multiple-target therapy with systems biology. METHODS: In our previous study, we identified 28 significant proteins--i.e., common core network markers--of four types of cancers as house-keeping proteins of these cancers. In this study, we ranked these proteins by summing their carcinogenesis relevance values (CRVs) across the four cancers, and then performed docking and pharmacophore modeling to do virtual screening on the NCI database for anti-cancer drugs. We also performed pathway analysis on these proteins using Panther and MetaCore to reveal more mechanisms of these cancer house-keeping proteins. RESULTS: We designed several approaches to discover targets for multiple-target cocktail therapies. In the first one, we identified the top 20 drugs for each of the 28 cancer house-keeping proteins, and analyzed the docking pose to further understand the interaction mechanisms of these drugs. After screening for duplicates, we found that 13 of these drugs could target 11 proteins simultaneously. In the second approach, we chose the top 5 proteins with the highest summed CRVs and used them as the drug targets. We built a pharmacophore and applied it to do virtual screening against the Life-Chemical library for anti-cancer drugs. Based on these results, wet-lab bio-scientists could freely investigate combinations of these drugs for multiple-target therapy for cancers, in contrast to the traditional single target therapy. CONCLUSIONS: Combination of systems biology with computer-aided drug design could help us develop novel drug cocktails with multiple targets. We believe this will enhance the efficiency of therapeutic practice and lead to new directions for cancer therapy.

Applying NGS Data to Find Evolutionary Network Biomarkers from the Early and Late Stages of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a major liver tumor (~80%), besides hepatoblastomas, angiosarcomas, and cholangiocarcinomas. In this study, we used a systems biology approach to construct protein-protein interaction networks (PPINs) for early-stage and late-stage liver cancer. By comparing the networks of these two stages, we found that the two networks showed some common mechanisms and some significantly different mechanisms. To obtain differential network structures between cancer and noncancer PPINs, we constructed cancer PPIN and noncancer PPIN network structures for the two stages of liver cancer by systems biology method using NGS data from cancer cells and adjacent noncancer cells. Using carcinogenesis relevance values (CRVs), we identified 43 and 80 significant proteins and their PPINs (network markers) for early-stage and late-stage liver cancer. To investigate the evolution of network biomarkers in the carcinogenesis process, a primary pathway analysis showed that common pathways of the early and late stages were those related to ordinary cancer mechanisms. A pathway specific to the early stage was the mismatch repair pathway, while pathways specific to the late stage were the spliceosome pathway, lysine degradation pathway, and progesterone-mediated oocyte maturation pathway. This study provides a new direction for cancer-targeted therapies at different stages.

Selecting tyrosine kinase inhibitors for gastrointestinal stromal tumor with secondary KIT activation-loop domain mutations.

Advanced gastrointestinal stromal tumors (GIST), a KIT oncogene-driven tumor, on imatinib mesylate (IM) treatment may develop secondary KIT mutations to confer IM-resistant phenotype. Second-line sunitinib malate (SU) therapy is largely ineffective for IM-resistant GISTs with secondary exon 17 (activation-loop domain) mutations. We established an in vitro cell-based platform consisting of a series of COS-1 cells expressing KIT cDNA constructs encoding common primary±secondary mutations observed in GISTs, to compare the activity of several commercially available tyrosine kinase inhibitors on inhibiting the phosphorylation of mutant KIT proteins at their clinically achievable plasma steady-state concentration (Css). The inhibitory efficacies on KIT exon 11/17 mutants were further validated by growth inhibition assay on GIST48 cells, and underlying molecular-structure mechanisms were investigated by molecular modeling. Our results showed that SU more effectively inhibited mutant KIT with secondary exon 13 or 14 mutations than those with secondary exon 17 mutations, as clinically indicated. On contrary, at individual Css, nilotinib and sorafenib more profoundly inhibited the phosphorylation of KIT with secondary exon 17 mutations and the growth of GIST48 cells than IM, SU, and dasatinib. Molecular modeling analysis showed fragment deletion of exon 11 and point mutation on exon 17 would lead to a shift of KIT conformational equilibrium toward active form, for which nilotinib and sorafenib bound more stably than IM and SU. In current preclinical study, nilotinib and sorafenib are more active in IM-resistant GISTs with secondary exon 17 mutation than SU that deserve further clinical investigation.

Effects of alpha-mangostin on the expression of anti-inflammatory genes in U937 cells.

BACKGROUND: α-Mangostin (α-MG) is a main constituent of the fruit hull of the mangosteen. Previous studies have shown that α-MG has pharmacological activities such as antioxidant, antitumor, anti-inflammatory, antiallergic, antibacterial, antifungal and antiviral effects. This study aims to investigate the anti-inflammatory molecular action of α-MG on gene expression profiles. METHODS: U937 and EL4 cells were treated with different concentrations of α-MG in the presence of 0.1 ng/mL lipopolysaccharide (LPS) for 4 h. The anti-inflammatory effects of α-MG were measured by the levels of tumor necrosis factor (TNF)-α and interleukin (IL)-4 in cell culture media, which were determined with enzyme-linked immunosorbent assay kits. The gene expression profiles of all samples were analyzed with a whole human genome microarray, Illumina BeadChip WG-6 version 3, containing 48804 probes. The protein levels were determined by Western blotting analyses. RESULTS: α-MG decreased the LPS induction of the inflammatory cytokines TNF-α (P = 0.038) and IL-4 (P = 0.04). α-MG decreased the gene expressions in oncostatin M signaling via mitogen-activated protein kinase (MAPK) pathways, including extracellular signal-regulated kinases (P = 0.016), c-Jun N-terminal kinase (P = 0.01) , and p38 (P = 0.008). α-MG treatment of U937 cells reduced the phosphorylation of MAPK kinase 3 / MAPK kinase 6 (P = 0.0441), MAPK-activated protein kinase-2 (P = 0.0453), signal transducers and activators of transcription-1 (STAT1) (P = 0.0012), c-Fos (P = 0.04), c-Jun (P = 0.019) and Ets-like molecule 1 (Elk-1) (P = 0.038). CONCLUSION: This study demonstrates that α-MG attenuates LPS-mediated activation of MAPK, STAT1, c-Fos, c-Jun and EIK-1, inhibiting TNF-α and IL-4 production in U937 cells.

A rare storm in a psychiatric ward: thyroid storm.

We present the case of a previously healthy man in whom acute psychosis masked the major symptomatology of thyroid storm. This patient highlights the importance of taking into consideration a life-threatening condition, thyroid storm, in the differential diagnosis of acute psychosis, even in the absence of a history of thyrotoxicosis.

Design of novel FLT-3 inhibitors based on dual-layer 3D-QSAR model and fragment-based compounds in silico.

FMS-like tyrosine kinase 3 (FLT-3) is strongly correlated with acute myeloid leukemia, but no FLT-3-inhibitor cocomplex structure is available to assist the design of therapeutic inhibitors. Hence, we propose a dual-layer 3D-QSAR model for FLT-3 that integrates the pharmacophore, CoMFA, and CoMSIA. We then coupled the model with the fragment-based design strategy to identify novel FLT-3 inhibitors. In the first layer, the previously established model, Hypo02, was evaluated in terms of its correlation coefficient (r), RMS, cost difference, and configuration cost, with values of 0.930, 1.24, 106.45, and 16.44, respectively. Moreover, Fischer's cross-validation test of data generated by Hypo02 yielded a 98% confidence level, and the validation of the testing set yielded a best r value of 0.87. The features of Hypo02 were separated into two parts and then used to screen the MiniMaybridge fragment compound database. Nine novel FLT-3 inhibitors were generated in this layer. In the second layer, Hypo02 was subjected to an alignment rule to generate CoMFA- and CoMSIA-based models, for which the partial least-squares validation method was utilized. The values of q(2), r(2), and predictive r(2) were 0.58, 0.98, and 0.76, respectively, derived from the CoMFA model with steric and electrostatic fields. The CoMSIA model with five different fields yielded values of 0.54, 0.97, and 0.76 for q(2), r(2), and predictive r(2), respectively. The CoMFA and CoMSIA models were used to constrain 3D structures of the nine novel FLT-3 inhibitors. This dual-layer 3D-QSAR model constitutes a valuable tool to easily and quickly screen and optimize novel potential FLT-3 inhibitors for the treatment of acute myeloid leukemia.

Pharmacophore modeling and virtual screening to identify potential RET kinase inhibitors.

Chemical features based 3D pharmacophore model for REarranged during Transfection (RET) tyrosine kinase were developed by using a training set of 26 structurally diverse known RET inhibitors. The best pharmacophore hypothesis, which identified inhibitors with an associated correlation coefficient of 0.90 between their experimental and estimated anti-RET values, contained one hydrogen-bond acceptor, one hydrogen-bond donor, one hydrophobic, and one ring aromatic features. The model was further validated by a testing set, Fischer's randomization test, and goodness of hit (GH) test. We applied this pharmacophore model to screen NCI database for potential RET inhibitors. The hits were docked to RET with GOLD and CDOCKER after filtering by Lipinski's rules. Ultimately, 24 molecules were selected as potential RET inhibitors for further investigation.

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.

Novel azulene-based derivatives as potent multi-receptor tyrosine kinase inhibitors.

A series of azulene-based derivatives were synthesized as potent inhibitors for receptor tyrosine kinases such as FMS-like tyrosine kinase 3 (FLT-3). Systematic side chain modification of prototype 1a was carried out through SAR studies. Analogue 22 was identified from this series and found to be one of the most potent FLT-3 inhibitors, with good pharmaceutical properties, superior efficacy, and tolerability in a tumor xenograft model.

Structures of heparin-derived tetrasaccharide bound to cobra cardiotoxins: heparin binding at a single protein site with diverse side chain interactions.

Cobra cardiotoxins (CTXs) are three-fingered polypeptides with positively charged domains that have been shown to bind to anionic ligands of snake venom citrate, glycosaminoglycans, sulfoglycosphingolipid, and nucleotide triphosphate with various biochemical effects including toxin dimerization, cell surface retention, membrane pore formation, cell internalization and blocking of enzymatic activities of kinase and ATPase. The reported anionic binding sites, however, are found to be different among different CTX homologues for potentially different CTX activities. Herein, by NMR studies of the binding of inorganic phosphate, dATP (stable form of ATP), and heparin-derived tetrasaccharide to Naja atra CTX A1, a novel CTX molecule exhibiting in vivo necrotic activity on skeletal muscle, we demonstrate that diverse ligands binding to CTXs could also occur at a single protein site with flexible side chain interactions. The flexibility of such an interaction is also illustrated by the available heparin-CTX A3 complex structures with different heparin chain lengths binding at the same site. Our results provide a likely structural explanation on how the interaction between heparan sufate and proteins depends more on the overall charge cluster organization rather than on their fine structures. We also suggest that the ligand binding site of CTX homologues can be fine-tuned by nonconserved residues near the binding pocket because of their flexible side chain interaction and dimerization ability, even for the rigid CTX molecules tightened by four disulfide bonds.

Structural difference between group I and group II cobra cardiotoxins: X-ray, NMR, and CD analysis of the effect of cis-proline conformation on three-fingered toxins.

Natural homologues of cobra cardiotoxins (CTXs) were classified into two structural subclasses of group I and II based on the amino acid sequence and circular dichroism analysis, but the exact differences in their three-dimensional structures and biological significance remain elusive. We show by circular dichroism, NMR spectroscopic, and X-ray crystallographic analyses of a newly purified group I CTX A6 from eastern Taiwan cobra (Naja atra) venoms that its loop I conformation adopts a type VIa turn with a cis peptide bond located between two proline residues of PPxY. A similar "banana-twisted" conformation can be observed in other group I CTXs and also in cyclolinopeptide A and its analogues. By binding to the membrane environment, group I CTX undergoes a conformational change to adopt a more extended hydrophobic domain with beta-sheet twisting closer to the one adopted by group II CTX. This result resolves a discrepancy in the CTX structural difference reported previously between solution as well as crystal state and shows that, in addition to the hydrophobicity, the exact loop I conformation also plays an important role in CTX-membrane interaction. Potential protein targets of group I CTXs after cell internalization are also discussed on the basis of the determined loop I conformation.