Reverse Screening Methods to Search for the Protein Targets of Chemopreventive Compounds.

Front Chem. 2018;6:138

Authors: Huang H, Zhang G, Zhou Y, Lin C, Chen S, Lin Y, Mai S, Huang Z

Abstract
This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget, and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB, and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction.

PMID: 29868550 [PubMed]

Drug Repositioning for Effective Prostate Cancer Treatment.

Front Physiol. 2018;9:500

Authors: Turanli B, Grøtli M, Boren J, Nielsen J, Uhlen M, Arga KY, Mardinoglu A

Abstract
Drug repositioning has gained attention from both academia and pharmaceutical companies as an auxiliary process to conventional drug discovery. Chemotherapeutic agents have notorious adverse effects that drastically reduce the life quality of cancer patients so drug repositioning is a promising strategy to identify non-cancer drugs which have anti-cancer activity as well as tolerable adverse effects for human health. There are various strategies for discovery and validation of repurposed drugs. In this review, 25 repurposed drug candidates are presented as result of different strategies, 15 of which are already under clinical investigation for treatment of prostate cancer (PCa). To date, zoledronic acid is the only repurposed, clinically used, and approved non-cancer drug for PCa. Anti-cancer activities of existing drugs presented in this review cover diverse and also known mechanisms such as inhibition of mTOR and VEGFR2 signaling, inhibition of PI3K/Akt signaling, COX and selective COX-2 inhibition, NF-κB inhibition, Wnt/β-Catenin pathway inhibition, DNMT1 inhibition, and GSK-3β inhibition. In addition to monotherapy option, combination therapy with current anti-cancer drugs may also increase drug efficacy and reduce adverse effects. Thus, drug repositioning may become a key approach for drug discovery in terms of time- and cost-efficiency comparing to conventional drug discovery and development process.

PMID: 29867548 [PubMed]

Trends of Clinical Trials for Drug Development in Rare Diseases.

Curr Clin Pharmacol. 2018 Jun 03;:

Authors: Sakate R, Fukagawa A, Takagaki Y, Okura H, Matsuyama A

Abstract
BACKGROUND: Drug development for rare diseases is challenging because very few patients suffer from such diseases, and thus it is difficult to obtain relevant data. In these difficult conditions, it must be informative to assess a trend of drug development so far, to plot a new strategy such as drug repositioning.
OBJECTIVE: In this study, data from clinical trials belonging to three international registries were first outlined and compared.
METHODS: ClinicalTrials.gov (NCT), EU Clinical Trials Register (EUCTR), and the Japan Primary Registries Network (JPRN) were analyzed. Clinical trials with information on rare diseases (Orphanet) and drugs (DrugBank) were extracted by text-mining.
RESULTS: A total of 28,526 clinical trials were considered, which studied 1,535 rare diseases and 1,539 drugs. NCT had the largest number of trials, involving 1,252 diseases and 1,332 drugs. However, EUCTR and JPRN also had a considerable number of registry-specific diseases (250 and 22, respectively) and drugs (172 and 29, respectively). After analyzing all trials, it was found that most diseases had been studied in only a limited number of trials; 70% of diseases had been studied in fewer than 10 trials, and 28% had been studied in only one. It was also found that most trials were for cancer-related rare diseases. The number of trials for non-cancer-related rare diseases were much fewer.
CONCLUSION: This study revealed details of the three registries and bias among rare diseases in the number of the trials. This information could contribute to drug-repositioning and a broad range of rare disease studies.

PMID: 29866013 [PubMed - as supplied by publisher]

Drug repositioning for prostate cancer: using a data-driven approach to gain new insights.

AMIA Annu Symp Proc. 2017;2017:1724-1733

Authors: Wang Q, Xu R

Abstract
Prostate cancer (PC) is the most common cancer and the third leading cause of cancer death in men worldwide. Despite its high incidence and mortality, the likelihood of a cure is low for late-stages of PC. There is an unmet need for more effective agents for treating PC. Here, we present a drug repositioning system, GenoPredict, for finding innovative drug candidates for treating PC. GenoPredict leverages upon a large amount of disease genomics data and a large-scale drug treatment knowledge base (TreatKB) that we recently constructed. We first constructed a genetic disease network (GDN) that comprised of 882 nodes and 200,758 edges and applied a network-based ranking algorithm to find diseases from GDN that are genetically related to PC. We developed a drug prioritization algorithm to reposition drugs from PC-related diseases to treat PC. When evaluated in a de-novo prediction setting using 27 FDA- approved PC drugs, GenoPredict found 25 of 27 FDA-approved PC drugs and ranked them highly (recall: 0.925, mean ranking: 27.3%, median ranking: 15.6%). When compared to PREDICT, a comprehensive drug repositioning system, in novel predictions, GenoPredict performed better than PREDICT across two evaluation datasets. GenoPredict achieved a mean average precision (MAP) of 0.447 when evaluated with 172 PC drugs extracted from 172,888 clinical trial reports, representing a 164.5% improvement as compared to a MAP of 0.169 for PREDICT. When evaluated with 72 PC drugs extracted from 43,811 ongoing clinical trial reports, GenoPredict achieved a MAP of 0.278, representing a 231.1% improvement as compared to a MAP of 0.084 for PREDICT. The data is publicly available at: http://nlp.
CASE: edu/public/data/PC_GenoPredict and http: //nlp.
CASE: edu/public/data/treatKB.

PMID: 29854243 [PubMed - in process]

Word-of-Mouth Innovation: Hypothesis Generation for Supplement Repurposing based on Consumer Reviews.

AMIA Annu Symp Proc. 2017;2017:689-695

Authors: Fan JW, Lussier YA

Abstract
Dietary supplements remain a relatively underexplored source for drug repurposing. A systematic approach to soliciting responses from a large consumer population is desirable to speed up innovation. We tested a workflow that mines unexpected benefits of dietary supplements from massive consumer reviews. A (non-exhaustive) list of regular expressions was used to screen over 2 million reviews on health and personal care products. The matched reviews were manually analyzed, and one supplement-disease pair was linked to biological databases for enriching the hypothesized association. The regular expressions found 169 candidate reviews, of which 45.6% described unexpected benefits of certain dietary supplements. The manual analysis showed some of the supplement-disease associations to be novel or in agreement with evidence published later in the literature. The hypothesis enrichment was able to identify meaningful function similarity between the supplement and the disease. The results demonstrated value of the workflow in identifying candidates for supplement repurposing.

PMID: 29854134 [PubMed - in process]

Repurposing Lesogaberan to Promote Human Islet Cell Survival and β-Cell Replication.

J Diabetes Res. 2017;2017:6403539

Authors: Tian J, Dang H, Hu A, Xu W, Kaufman DL

Abstract
The activation of β-cell's A- and B-type gamma-aminobutyric acid receptors (GABAA-Rs and GABAB-Rs) can promote their survival and replication, and the activation of α-cell GABAA-Rs promotes their conversion into β-cells. However, GABA and the most clinically applicable GABA-R ligands may be suboptimal for the long-term treatment of diabetes due to their pharmacological properties or potential side-effects on the central nervous system (CNS). Lesogaberan (AZD3355) is a peripherally restricted high-affinity GABAB-R-specific agonist, originally developed for the treatment of gastroesophageal reflux disease (GERD) that appears to be safe for human use. This study tested the hypothesis that lesogaberan could be repurposed to promote human islet cell survival and β-cell replication. Treatment with lesogaberan significantly enhanced replication of human islet cells in vitro, which was abrogated by a GABAB-R antagonist. Immunohistochemical analysis of human islets that were grafted into immune-deficient mice revealed that oral treatment with lesogaberan promoted human β-cell replication and islet cell survival in vivo as effectively as GABA (which activates both GABAA-Rs and GABAB-Rs), perhaps because of its more favorable pharmacokinetics. Lesogaberan may be a promising drug candidate for clinical studies of diabetes intervention and islet transplantation.

PMID: 29018828 [PubMed - indexed for MEDLINE]

Computational Drug Repurposing: Current Trends.

Curr Med Chem. 2018 May 29;:

Authors: Karaman B, Sippl W

Abstract
Biomedical discovery has been reshaped upon the exploding digitization of data which can be retrieved from a number of sources, ranging from clinical pharmacology to cheminformatics-driven databases. Now, supercomputing platforms and publicly available resources such as biological, physicochemical, and clinical data, can all be integrated to construct a detailed map of signaling pathways and drug mechanisms of action in relation to drug candidates. Recent advancements in computer-aided data mining have facilitated analyses of 'big data' approaches and the discovery of new indications for pre-existing drugs has been accelerated. Linking gene-phenotype associations to predict novel drug-disease signatures or incorporating molecular structure information of drugs and protein targets with other kinds of data derived from systems biology provide great potential to accelerate drug discovery and improve the success of drug repurposing attempts. In this review, we highlight commonly used computational drug repurposing strategies, including bioinformatic and cheminformatic tools, to integrate large-scale data emerging from the systems biology, and consider both the challenges and opportunities of using this approach. Moreover, we provide successful examples and cases studies that combined various in silico drug-repurposing strategies to predict potential novel uses for known therapeutics.

PMID: 29848268 [PubMed - as supplied by publisher]

Dengue Antiviral Development: A Continuing Journey.

Adv Exp Med Biol. 2018;1062:319-332

Authors: Low JG, Gatsinga R, Vasudevan SG, Sampath A

Abstract
Dengue fever is a leading cause of illness and mortality in the tropics and subtropics. There are no therapeutics currently available and a recently approved vaccine is not very efficacious demanding an urgent need to develop an effective antiviral. The path to successful dengue drug development depends on availability of relevant preclinical testing models and better understanding of dengue pathogenesis. In recent years, efforts to develop dengue therapeutics have focused on both repurposing approved drugs as well as discovery of new chemical entities that act via virus or host targeted mechanisms. Here, we discuss the various innovative approaches, their outcome, and the lessons gleaned from the development efforts.

PMID: 29845542 [PubMed - in process]

Linking drug target and pathway activation for effective therapy using multi-task learning.

Sci Rep. 2018 May 29;8(1):8322

Authors: Yang M, Simm J, Lam CC, Zakeri P, van Westen GJP, Moreau Y, Saez-Rodriguez J

Abstract
Despite the abundance of large-scale molecular and drug-response data, the insights gained about the mechanisms underlying treatment efficacy in cancer has been in general limited. Machine learning algorithms applied to those datasets most often are used to provide predictions without interpretation, or reveal single drug-gene association and fail to derive robust insights. We propose to use Macau, a bayesian multitask multi-relational algorithm to generalize from individual drugs and genes and explore the interactions between the drug targets and signaling pathways' activation. A typical insight would be: "Activation of pathway Y will confer sensitivity to any drug targeting protein X". We applied our methodology to the Genomics of Drug Sensitivity in Cancer (GDSC) screening, using gene expression of 990 cancer cell lines, activity scores of 11 signaling pathways derived from the tool PROGENy as cell line input and 228 nominal targets for 265 drugs as drug input. These interactions can guide a tissue-specific combination treatment strategy, for example suggesting to modulate a certain pathway to maximize the drug response for a given tissue. We confirmed in literature drug combination strategies derived from our result for brain, skin and stomach tissues. Such an analysis of interactions across tissues might help target discovery, drug repurposing and patient stratification strategies.

PMID: 29844324 [PubMed - in process]

Niclosamide Exhibits Potent Anticancer Activity and Synergizes with Sorafenib in Human Renal Cell Cancer Cells.

Cell Physiol Biochem. 2018 May 24;47(3):957-971

Authors: Yu X, Liu F, Zeng L, He F, Zhang R, Yan S, Zeng Z, Shu Y, Zhao C, Wu X, Lei J, Zhang W, Yang C, Wu K, Wu Y, An L, Huang S, Ji X, Gong C, Yuan C, Zhang L, Feng Y, Huang B, Liu W, Zhang B, Dai Z, Wang X, Liu B, Haydon RC, Luu HH, Gan H, He TC, Chen L

Abstract
BACKGROUND/AIMS: As the most lethal urological cancers, renal cell carcinoma (RCC) comprises a heterogeneous group of cancer with diverse genetic and molecular alterations. There is an unmet clinical need to develop efficacious therapeutics for advanced, metastatic and/or relapsed RCC. Here, we investigate whether anthelmintic drug Niclosamide exhibits anticancer activity and synergizes with targeted therapy Sorafenib in suppressing RCC cell proliferation.
METHODS: Cell proliferation and migration were assessed by Crystal violet staining, WST-1 assay, cell wounding and cell cycle analysis. Gene expression was assessed by qPCR. In vivo anticancer activity was assessed in xenograft tumor model.
RESULTS: We find that Niclosamide effectively inhibits cell proliferation, cell migration and cell cycle progression, and induces apoptosis in human renal cancer cells. Mechanistically, Niclosamide inhibits the expression of C-MYC and E2F1 while inducing the expression of PTEN in RCC cells. Niclosamide is further shown to synergize with Sorafenib in suppressing RCC cell proliferation and survival. In the xenograft tumor model, Niclosamide is shown to effectively inhibit tumor growth and suppress RCC cell proliferation.
CONCLUSIONS: Niclosamide may be repurposed as a potent anticancer agent, which can potentiate the anticancer activity of the other agents targeting different signaling pathways in the treatment of human RCC.

PMID: 29843133 [PubMed - as supplied by publisher]

Targeting intracellular p-aminobenzoic acid production potentiates the anti-tubercular action of antifolates.

Sci Rep. 2016 12 01;6:38083

Authors: Thiede JM, Kordus SL, Turman BJ, Buonomo JA, Aldrich CC, Minato Y, Baughn AD

Abstract
The ability to revitalize and re-purpose existing drugs offers a powerful approach for novel treatment options against Mycobacterium tuberculosis and other infectious agents. Antifolates are an underutilized drug class in tuberculosis (TB) therapy, capable of disrupting the biosynthesis of tetrahydrofolate, an essential cellular cofactor. Based on the observation that exogenously supplied p-aminobenzoic acid (PABA) can antagonize the action of antifolates that interact with dihydropteroate synthase (DHPS), such as sulfonamides and p-aminosalicylic acid (PAS), we hypothesized that bacterial PABA biosynthesis contributes to intrinsic antifolate resistance. Herein, we demonstrate that disruption of PABA biosynthesis potentiates the anti-tubercular action of DHPS inhibitors and PAS by up to 1000 fold. Disruption of PABA biosynthesis is also demonstrated to lead to loss of viability over time. Further, we demonstrate that this strategy restores the wild type level of PAS susceptibility in a previously characterized PAS resistant strain of M. tuberculosis. Finally, we demonstrate selective inhibition of PABA biosynthesis in M. tuberculosis using the small molecule MAC173979. This study reveals that the M. tuberculosis PABA biosynthetic pathway is responsible for intrinsic resistance to various antifolates and this pathway is a chemically vulnerable target whose disruption could potentiate the tuberculocidal activity of an underutilized class of antimicrobial agents.

PMID: 27905500 [PubMed - indexed for MEDLINE]

GDA, a web-based tool for Genomics and Drugs integrated analysis.

Nucleic Acids Res. 2018 May 25;:

Authors: Caroli J, Sorrentino G, Forcato M, Del Sal G, Bicciato S

Abstract
Several major screenings of genetic profiling and drug testing in cancer cell lines proved that the integration of genomic portraits and compound activities is effective in discovering new genetic markers of drug sensitivity and clinically relevant anticancer compounds. Despite most genetic and drug response data are publicly available, the availability of user-friendly tools for their integrative analysis remains limited, thus hampering an effective exploitation of this information. Here, we present GDA, a web-based tool for Genomics and Drugs integrated Analysis that combines drug response data for >50 800 compounds with mutations and gene expression profiles across 73 cancer cell lines. Genomic and pharmacological data are integrated through a modular architecture that allows users to identify compounds active towards cancer cell lines bearing a specific genomic background and, conversely, the mutational or transcriptional status of cells responding or not-responding to a specific compound. Results are presented through intuitive graphical representations and supplemented with information obtained from public repositories. As both personalized targeted therapies and drug-repurposing are gaining increasing attention, GDA represents a resource to formulate hypotheses on the interplay between genomic traits and drug response in cancer. GDA is freely available at http://gda.unimore.it/.

PMID: 29800349 [PubMed - as supplied by publisher]

Polypharmacological Drug-target Inference for Chemogenomics.

Mol Inform. 2018 May 24;:

Authors: Schneider P, Schneider G

Abstract
Pharmacological drug actions are often caused by multi-target effects. While most of the currently approved synthetic drugs were designed to interact with a single 'on-target', these chemical agents often interact with additional 'off-targets'. Understanding and rationalizing these multiple interactions will be indispensable for the design of future precision medicines. We employed computational predictions of drug-target interactions to analyze functional drug-drug relationships. 900 approved drugs were represented in terms of their predicted activity fingerprints, considering 1158 potential target activities. A drug relationship network was constructed based on fingerprint similarity. The resulting network graph highlights clusters of compounds sharing similar predicted on- and off-targets, and allows to identify mutual targets of drugs that were originally developed for different therapeutic indications. Such an analysis offers straightforward access to spotting potential off-target liabilities and drug-drug interactions, as well as drug repurposing opportunities.

PMID: 29797496 [PubMed - as supplied by publisher]

Advocating for mutually beneficial access to shelved compounds.

Future Med Chem. 2018 May 23;:

Authors: Pulley JM, Jerome RN, Shirey-Rice JK, Zaleski NM, Naylor HM, Pruijssers AJ, Jackson JC, Bernard GR, Holroyd KJ

PMID: 29788759 [PubMed - as supplied by publisher]

RepTB: a gene ontology based drug repurposing approach for tuberculosis.

J Cheminform. 2018 May 21;10(1):24

Authors: Passi A, Rajput NK, Wild DJ, Bhardwaj A

Abstract
Tuberculosis (TB) is the world's leading infectious killer with 1.8 million deaths in 2015 as reported by WHO. It is therefore imperative that alternate routes of identification of novel anti-TB compounds are explored given the time and costs involved in new drug discovery process. Towards this, we have developed RepTB. This is a unique drug repurposing approach for TB that uses molecular function correlations among known drug-target pairs to predict novel drug-target interactions. In this study, we have created a Gene Ontology based network containing 26,404 edges, 6630 drug and 4083 target nodes. The network, enriched with molecular function ontology, was analyzed using Network Based Inference (NBI). The association scores computed from NBI are used to identify novel drug-target interactions. These interactions are further evaluated based on a combined evidence approach for identification of potential drug repurposing candidates. In this approach, targets which have no known variation in clinical isolates, no human homologs, and are essential for Mtb's survival and or virulence are prioritized. We analyzed predicted DTIs to identify target pairs whose predicted drugs may have synergistic bactericidal effect. From the list of predicted DTIs from RepTB, four TB targets, namely, FolP1 (Dihydropteroate synthase), Tmk (Thymidylate kinase), Dut (Deoxyuridine 5'-triphosphate nucleotidohydrolase) and MenB (1,4-dihydroxy-2-naphthoyl-CoA synthase) may be selected for further validation. In addition, we observed that in some cases there is significant chemical structure similarity between predicted and reported drugs of prioritized targets, lending credence to our approach. We also report new chemical space for prioritized targets that may be tested further. We believe that with increasing drug-target interaction dataset RepTB will be able to offer better predictive value and is amenable for identification of drug-repurposing candidates for other disease indications too.

PMID: 29785561 [PubMed]

Identification and validation of uterine stimulant methylergometrine as a potential inhibitor of caspase-1 activation.

Apoptosis. 2017 Oct;22(10):1310-1318

Authors: García-Laínez G, Sancho M, García-Bayarri V, Orzáez M

Abstract
Inflammasomes are intracellular multiprotein complexes of the innate immune system. Upon an inflammatory insult, such as infection or intracellular damage, a nucleotide-binding oligomerization domain-like receptor (NLR) sensor protein and the adaptor protein ASC (apoptosis-associated speck-like protein containing a caspase activation and recruitment domain) are assembled to activate protease procaspase-1. This protease processes pro-IL-1β and pro-IL-18 cytokines, which are released to induce the inflammatory response. De-regulation of inflammasome contributes to the progression of several diseases, such as Alzheimer's disease, diabetes, cancer, inflammatory and autoimmune disorders. We herein describe the identification of methylergometrine (MEM), a drug currently used as a smooth muscle constrictor during postpartum hemorrhage, as an inhibitor of the inflammasome complex in ASC-mediated procaspase-1 activation screening. MEM inhibits the activation of the nucleotide-binding oligomerization domain-like receptor protein 1 (NLRP1) and nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3) inflammasomes in cellular models upon different pro-inflammatory stimuli. Our results suggest that MEM has the potential to reposition in the treatment of inflammatory diseases with the advantages of established safety and clinical data.

PMID: 28755170 [PubMed - indexed for MEDLINE]

Mevalonate pathway blockage enhances the efficacy of mTOR inhibitors with the activation of retinoblastoma protein in renal cell carcinoma.

Cancer Lett. 2018 May 17;:

Authors: Hagiwara N, Watanabe M, Iizuka-Ohashi M, Yokota I, Toriyama S, Sukeno M, Tomosugi M, Sowa Y, Hongo F, Mikami K, Soh J, Fujito A, Miyashita H, Morioka Y, Miki T, Ukimura O, Sakai T

Abstract
Renal cell carcinoma (RCC) is the most common malignancy of kidney and remains largely intractable once it recurs after resection. mTOR inhibitors have been one of the mainstays used against recurrent RCC; however, there has been a major problem of the resistance to mTOR inhibitors, and thus new combination treatments with mTOR inhibitors are required. We here retrospectively showed that regular use of antilipidemic drug statins could provide a longer progression free survival (PFS) in RCC patients prescribed with an mTOR inhibitor everolimus than without statins (median PFS, 7.5 months vs. 3.2 months, respectively; hazard ratio, 0.52; 95% CI, 0.22-1.11). In order to give a rationale for this finding, we used RCC cell lines and showed the combinatorial effects of an mTOR inhibitor with statins induced a robust activation of retinoblastoma protein, whose mechanisms were involved in statins-mediated hindrance of KRAS or Rac1 protein prenylation. Finally, statins treatment also enhanced the efficacy of an mTOR inhibitor in RCC xenograft models. Thus, we provide molecular and (pre)clinical data showing that statins use could be a drug repositioning for RCC patients to enhance the efficacy of mTOR inhibitors.

PMID: 29778569 [PubMed - as supplied by publisher]

Repositioning of anti-cancer drug candidate, AZD7762, to an anti-allergic drug suppressing IgE-mediated mast cells and allergic responses via the inhibition of Lyn and Fyn.

Biochem Pharmacol. 2018 May 16;:

Authors: Park YH, Kim DK, Kim HW, Kim HS, Lee D, Lee MB, Young Min K, Koo J, Kim SJ, Kang C, Mi Kim Y, Kim HS, Choi WS

Abstract
Mast cells are critical effector cells in IgE-mediated allergic responses. The aim of this study was to investigate the anti-allergic effects of 3-[(aminocarbonyl)amino]-5-(3-fluorophenyl)-N-(3S)-3-piperidinyl-2-thiophenecarboxamide (AZD7762) in vitro and in vivo. AZD7762 inhibited the antigen-stimulated degranulation from RBL-2H3 (IC50, ∼ 27.9 nM) and BMMCs (IC50, ∼ 99.3 nM) in a dose-dependent manner. AZD7762 also inhibited the production of TNF-α and IL-4. As the mechanism of its action, AZD7762 inhibited the activation of Syk and its downstream signaling proteins, such as Linker of activated T cells (LAT), phospholipase (PL) Cγ1, Akt, and mitogen-activated protein (MAP) kinases (Erk1 / 2, p38, and JNK) in mast cells. In in vitro protein kinase assay, AZD7762 inhibited the activity of Lyn and Fyn kinases, which are important for the activation of Syk in mast cells. Furthermore, AZD7762 also suppressed the degranulation of LAD2 human mast cells (IC50, ∼ 49.9 nM) and activation of Syk in a dose-dependent manner. As observed in experiments with mast cells in vitro, AZD7762 inhibited antigen-mediated passive cutaneous anaphylaxis in mice (ED50, ∼ 35.8 mg/kg). Altogether, these results suggest that AZD7762 could be used as a new therapeutic agent for mast cell-mediated allergic diseases.

PMID: 29777684 [PubMed - as supplied by publisher]

Down-regulating IL-6/GP130 targets improved the anti-tumor effects of 5-fluorouracil in colon cancer.

Apoptosis. 2018 May 18;:

Authors: Li S, Tian J, Zhang H, Zhou S, Wang X, Zhang L, Yang J, Zhang Z, Ji Z

Abstract
Recent studies have confirmed that IL-6/GP130 targets are closely associated with tumor growth, metastasis and drug resistance. 5-Fluorouracil (5-FU) is the most common chemotherapeutic agent for colon cancer but is limited due to chemoresistance and high cytotoxicity. Bazedoxifene (BZA), a third-generation selective estrogen receptor modulator, was discovered by multiple ligand simultaneous docking and drug repositioning approaches to have a novel function as an IL-6/GP130 target inhibitor. Thus, we speculated that in colon cancer, the anti-tumor efficacy of 5-FU might be increased in combination with IL-6/GP130 inhibitors. CCK8 assay and colony formation assay were used to detect the cell proliferation and colony formation. We measured the IC50 value of 5-FU alone and in combination with BZA by cell viability inhibition. Cell migration and invasion ability were tested by scratch migration assays and transwell invasion assays. Flow cytometric analysis for cell apoptosis and cell cycle. Quantitative real-time PCR was used to detect Bad, Bcl-2 and Ki-67 mRNA expression and western blotting (WB) assay analyzed protein expression of Bad/Bcl-2 signaling pathway. Further mechanism study, WB analysis detected the key proteins level in IL-6/GP130 targets and JAK/STAT3, Ras/Raf/MEK/ERK, and PI3K/AKT/mTOR signaling pathway. A colon cancer xenograft model was used to further confirm the efficacy of 5-FU and BZA in vivo. The GP130, P-STAT3, P-AKT, and P-ERK expression levels were detected by immunohistochemistry in the xenograft tumor. BZA markedly potentiates the anti-tumor function of 5-FU in vitro and in vivo. Conversely, 5-FU activation is reduced following exogenous IL-6 treatment in cells. Further mechanistic studies determined that BZA treatment enhanced 5-FU anti-tumor activation by inhibiting the IL-6/GP130 signaling pathway and the phosphorylation status of the downstream effectors AKT, ERK and STAT3. In contrast, IL-6 can attenuate 5-FU function via activating IL-6R/GP130 signaling and the P-AKT, P-ERK and P-STAT3 levels. This study firstly verifies that targeting IL-6/GP130 signaling can increase the anti-tumor function of 5-FU; in addition, this strategy can sensitize cancer cell drug sensitivity, implying that blocking IL-6/GP130 targets can reverse chemoresistance. Therefore, combining 5-FU and IL-6/GP130 target inhibitors may be a promising approach for cancer treatment.

PMID: 29777330 [PubMed - as supplied by publisher]

Systems Pharmacology-Based Approach of Connecting Disease Genes in Genome-Wide Association Studies with Traditional Chinese Medicine.

Int J Genomics. 2018;2018:7697356

Authors: Kim J, Yoo M, Shin J, Kim H, Kang J, Tan AC

Abstract
Traditional Chinese medicine (TCM) originated in ancient China has been practiced over thousands of years for treating various symptoms and diseases. However, the molecular mechanisms of TCM in treating these diseases remain unknown. In this study, we employ a systems pharmacology-based approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. We studied 102 TCM components and their target genes by analyzing microarray gene expression experiments. We constructed disease-gene networks from 2558 GWAS studies. We applied a systems pharmacology approach to prioritize disease-target genes. Using this bioinformatics approach, we analyzed 14,713 GWAS disease-TCM-target gene pairs and identified 115 disease-gene pairs with q value < 0.2. We validated several of these GWAS disease-TCM-target gene pairs with literature evidence, demonstrating that this computational approach could reveal novel indications for TCM. We also develop TCM-Disease web application to facilitate the traditional Chinese medicine drug repurposing efforts. Systems pharmacology is a promising approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. The computational approaches described in this study could be easily expandable to other disease-gene network analysis.

PMID: 29765977 [PubMed]