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  • 1
    Abstract: We created SynSysNet, available online at http://bioinformatics.charite.de/synsysnet, to provide a platform that creates a comprehensive 4D network of synaptic interactions. Neuronal synapses are fundamental structures linking nerve cells in the brain and they are responsible for neuronal communication and information processing. These processes are dynamically regulated by a network of proteins. New developments in interaction proteomics and yeast two-hybrid methods allow unbiased detection of interactors. The consolidation of data from different resources and methods is important to understand the relation to human behaviour and disease and to identify new therapeutic approaches. To this end, we established SynSysNet from a set of approximately 1000 synapse specific proteins, their structures and small-molecule interactions. For two-thirds of these, 3D structures are provided (from Protein Data Bank and homology modelling). Drug-target interactions for 750 approved drugs and 50 000 compounds, as well as 5000 experimentally validated protein-protein interactions, are included. The resulting interaction network and user-selected parts can be viewed interactively and exported in XGMML. Approximately 200 involved pathways can be explored regarding drug-target interactions. Homology-modelled structures are downloadable in Protein Data Bank format, and drugs are available as MOL-files. Protein-protein interactions and drug-target interactions can be viewed as networks; corresponding PubMed IDs or sources are given.
    Type of Publication: Journal article published
    PubMed ID: 23143269
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  • 2
    Keywords: DISEASE ; CARE ; AGE ; WOMENS HEALTH
    Abstract: BACKGROUND: Searches for sex and gender-specific publications are complicated by the absence of a specific algorithm within search engines and by the lack of adequate archives to collect the retrieved results. We previously addressed this issue by initiating the first systematic archive of medical literature containing sex and/or gender-specific analyses. This initial collection has now been greatly enlarged and re-organized as a free user-friendly database with multiple functions: GenderMedDB (http://gendermeddb.charite.de). DESCRIPTION: GenderMedDB retrieves the included publications from the PubMed database. Manuscripts containing sex and/or gender-specific analysis are continuously screened and the relevant findings organized systematically into disciplines and diseases. Publications are furthermore classified by research type, subject and participant numbers. More than 11,000 abstracts are currently included in the database, after screening more than 40,000 publications. The main functions of the database include searches by publication data or content analysis based on pre-defined classifications. In addition, registrants are enabled to upload relevant publications, access descriptive publication statistics and interact in an open user forum. CONCLUSIONS: Overall, GenderMedDB offers the advantages of a discipline-specific search engine as well as the functions of a participative tool for the gender medicine community.
    Type of Publication: Journal article published
    PubMed ID: 24904731
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  • 3
    Keywords: INFORMATION ; MOLECULES ; PREDICTION ; CHEMISTRY ; LEADS ; UPDATE ; DRUG DISCOVERY ; MEDICINE
    Abstract: Natural products play a significant role in drug discovery and development. Many topological pharmacophore patterns are common between natural products and commercial drugs. A better understanding of the specific physicochemical and structural features of natural products is important for corresponding drug development. Several encyclopedias of natural compounds have been composed, but the information remains scattered or not freely available. The first version of the Supernatural database containing approximately 50,000 compounds was published in 2006 to face these challenges. Here we present a new, updated and expanded version of natural product database, Super Natural II (http://bioinformatics.charite.de/supernatural), comprising approximately 326,000 molecules. It provides all corresponding 2D structures, the most important structural and physicochemical properties, the predicted toxicity class for approximately 170,000 compounds and the vendor information for the vast majority of compounds. The new version allows a template-based search for similar compounds as well as a search for compound names, vendors, specific physical properties or any substructures. Super Natural II also provides information about the pathways associated with synthesis and degradation of the natural products, as well as their mechanism of action with respect to structurally similar drugs and their target proteins.
    Type of Publication: Journal article published
    PubMed ID: 25300487
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  • 4
    Keywords: ALGORITHM ; DATABASE ; MASS-SPECTROMETRY ; PEPTIDE REPERTOIRE ; HLA ; ELECTRON-TRANSFER DISSOCIATION ; DRUG HYPERSENSITIVITY ; REACTION SUBSEQUENT ; CONTACT ALLERGY ; ABACAVIR
    Abstract: Immune mediated adverse drug reactions (IM-ADRs) remain a significant source of patient morbidity that have more recently been shown to be associated with specific class I and/or II human leukocyte antigen (HLA) alleles. Abacavir-induced hypersensitivity syndrome is a CD8+ T cell dependent IM-ADR that is exclusively mediated by HLA-B*57:01. We and others have previously shown that abacavir can occupy the floor of the peptide binding groove of HLA-B*57:01 molecules, increasing the affinity of certain self peptides resulting in an altered peptide-binding repertoire. Here, we have identified another drug, acyclovir, which appears to act in a similar fashion. As with abacavir, acyclovir showed a dose dependent increase in affinity for peptides with valine and isoleucine at their C-terminus. In agreement with the binding studies, HLA-B*57:01 peptide-elution studies performed in the presence of acyclovir revealed an increased number of endogenously bound peptides with a C-terminal isoleucine. Accordingly, we have hypothesized that acyclovir acts by the same mechanism as abacavir, although our data also suggest the overall effect is much smaller: the largest changes of peptide affinity for acyclovir were 2-5 fold, whereas for abacavir this effect was as much as 1000-fold. Unlike abacavir, acyclovir is not known to cause IM-ADRs. We conclude that the modest effect of acyclovir on HLA binding affinity in contrast to the large effect of abacavir is insufficient to trigger a hypersensitivity syndrome. We further support this by functional in vitro studies where acyclovir, unlike abacavir, was unable to produce an increase in IFN-gamma upon expansion of HLA-B*57:01+ PBMCs from healthy donors. Using abacavir and acyclovir as examples we therefore propose an in vitro pre-clinical screening strategy, whereby thresholds can be applied to MHC-peptide binding assays to determine the likelihood that a drug could cause a clinically relevant IM-ADR.
    Type of Publication: Journal article published
    PubMed ID: 26024233
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  • 5
    Keywords: GROWTH ; INHIBITOR ; PHASE-I ; MOLECULES ; PREDICTION ; ADVANCED COLORECTAL-CANCER ; RECEPTOR TYROSINE KINASES ; SUPERTARGET ; PTK787/ZK 222584 ; POLY(ADP-RIBOSE)
    Abstract: BACKGROUND: Searching for two-dimensional (2D) structural similarities is a useful tool to identify new active compounds in drug-discovery programs. However, as 2D similarity measures neglect important structural and functional features, similarity by 2D might be underestimated. In the present study, we used combined 2D and three-dimensional (3D) similarity comparisons to reveal possible new functions and/or side-effects of known bioactive compounds. RESULTS: We utilised more than 10,000 compounds from the SuperTarget database with known inhibition values for twelve different anti-cancer targets. We performed all-against-all comparisons resulting in 2D similarity landscapes. Among the regions with low 2D similarity scores are inhibitors of vascular endothelial growth factor receptor (VEGFR) and inhibitors of poly ADP-ribose polymerase (PARP). To demonstrate that 3D landscape comparison can identify similarities, which are untraceable in 2D similarity comparisons, we analysed this region in more detail. This 3D analysis showed the unexpected structural similarity between inhibitors of VEGFR and inhibitors of PARP. Among the VEGFR inhibitors that show similarities to PARP inhibitors was Vatalanib, an oral "multi-targeted" small molecule protein kinase inhibitor being studied in phase-III clinical trials in cancer therapy. An in silico docking simulation and an in vitro HT universal colorimetric PARP assay confirmed that the VEGFR inhibitor Vatalanib exhibits off-target activity as a PARP inhibitor, broadening its mode of action. CONCLUSION: In contrast to the 2D-similarity search, the 3D-similarity landscape comparison identifies new functions and side effects of the known VEGFR inhibitor Vatalanib.
    Type of Publication: Journal article published
    PubMed ID: 26403354
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  • 6
    Abstract: Here, we present an updated version of CancerResource, freely available without registration at http://bioinformatics.charite.de/care. With upcoming information on target expression and mutations in patients' tumors, the need for systems supporting decisions on individual therapy is growing. This knowledge is based on numerous, experimentally validated drug-target interactions and supporting analyses such as measuring changes in gene expression using microarrays and HTS-efforts on cell lines. To enable a better overview about similar drug-target data and supporting information, a series of novel information connections are established and made available as described in the following. CancerResource contains about 91 000 drug-target relations, more than 2000 cancer cell lines and drug sensitivity data for about 50 000 drugs. CancerResource enables the capability of uploading external expression and mutation data and comparing them to the database's cell lines. Target genes and compounds are projected onto cancer-related pathways to get a better overview about how drug-target interactions benefit the treatment of cancer. Features like cellular fingerprints comprising of mutations, expression values and drug-sensitivity data can promote the understanding of genotype to drug sensitivity associations. Ultimately, these profiles can also be used to determine the most effective drug treatment for a cancer cell line most similar to a patient's tumor cells.
    Type of Publication: Journal article published
    PubMed ID: 26590406
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  • 7
    Abstract: Post-marketing drug withdrawals can be associated with various events, ranging from safety issues such as reported deaths or severe side-effects, to a multitude of non-safety problems including lack of efficacy, manufacturing, regulatory or business issues. During the last century, the majority of drugs voluntarily withdrawn from the market or prohibited by regulatory agencies was reported to be related to adverse drug reactions. Understanding the underlying mechanisms of toxicity is of utmost importance for current and future drug discovery. Here, we present WITHDRAWN, a resource for withdrawn and discontinued drugs publicly accessible at http://cheminfo.charite.de/withdrawn. Today, the database comprises 578 withdrawn or discontinued drugs, their structures, important physico-chemical properties, protein targets and relevant signaling pathways. A special focus of the database lies on the drugs withdrawn due to adverse reactions and toxic effects. For approximately one half of the drugs in the database, safety issues were identified as the main reason for withdrawal. Withdrawal reasons were extracted from the literature and manually classified into toxicity types representing adverse effects on different organs. A special feature of the database is the presence of multiple search options which will allow systematic analyses of withdrawn drugs and their mechanisms of toxicity.
    Type of Publication: Journal article published
    PubMed ID: 26553801
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  • 8
    Abstract: FSGS is a CKD with heavy proteinuria that eventually progresses to ESRD. Hereditary forms of FSGS have been linked to mutations in the transient receptor potential cation channel, subfamily C, member 6 (TRPC6) gene encoding a nonselective cation channel. Most of these TRPC6 mutations cause a gain-of-function phenotype, leading to calcium-triggered podocyte cell death, but the underlying molecular mechanisms are unclear. We studied the molecular effect of disease-related mutations using tridimensional in silico modeling of tetrameric TRPC6. Our results indicated that G757 is localized in a domain forming a TRPC6-TRPC6 interface and predicted that the amino acid exchange G757D causes local steric hindrance and disruption of the channel complex. Notably, functional characterization of model interface domain mutants suggested a loss-of-function phenotype. We then characterized 19 human FSGS-related TRPC6 mutations, the majority of which caused gain-of-function mutations. However, five mutations (N125S, L395A, G757D, L780P, and R895L) caused a loss-of-function phenotype. Coexpression of wild-type TRPC6 and TRPC6 G757D, mimicking heterozygosity observed in patients, revealed a dominant negative effect of TRPC6 G757D. Our comprehensive analysis of human disease-causing TRPC6 mutations reveals loss of TRPC6 function as an additional concept of hereditary FSGS and provides molecular insights into the mechanism responsible for the loss-of-function phenotype of TRPC6 G757D in humans.
    Type of Publication: Journal article published
    PubMed ID: 26892346
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  • 9
    Abstract: MACC1 (Metastasis Associated in Colon Cancer 1) is a key driver and prognostic biomarker for cancer progression and metastasis in a large variety of solid tumor types, particularly colorectal cancer (CRC). However, no MACC1 inhibitors have been identified yet. Therefore, we aimed to target MACC1 expression using a luciferase reporter-based high-throughput screening with the ChemBioNet library of more than 30,000 compounds. The small molecules lovastatin and rottlerin emerged as the most potent MACC1 transcriptional inhibitors. They remarkably inhibited MACC1 promoter activity and expression, resulting in reduced cell motility. Lovastatin impaired the binding of the transcription factors c-Jun and Sp1 to the MACC1 promoter, thereby inhibiting MACC1 transcription. Most importantly, in CRC-xenografted mice, lovastatin and rottlerin restricted MACC1 expression and liver metastasis. This is-to the best of our knowledge-the first identification of inhibitors restricting cancer progression and metastasis via the novel target MACC1. This drug repositioning might be of therapeutic value for CRC patients.
    Type of Publication: Journal article published
    PubMed ID: 28570591
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  • 10
    Abstract: Kinase inhibitors are important cancer therapeutics. Polypharmacology is commonly observed, requiring thorough target deconvolution to understand drug mechanism of action. Using chemical proteomics, we analyzed the target spectrum of 243 clinically evaluated kinase drugs. The data revealed previously unknown targets for established drugs, offered a perspective on the "druggable" kinome, highlighted (non)kinase off-targets, and suggested potential therapeutic applications. Integration of phosphoproteomic data refined drug-affected pathways, identified response markers, and strengthened rationale for combination treatments. We exemplify translational value by discovering SIK2 (salt-inducible kinase 2) inhibitors that modulate cytokine production in primary cells, by identifying drugs against the lung cancer survival marker MELK (maternal embryonic leucine zipper kinase), and by repurposing cabozantinib to treat FLT3-ITD-positive acute myeloid leukemia. This resource, available via the ProteomicsDB database, should facilitate basic, clinical, and drug discovery research and aid clinical decision-making.
    Type of Publication: Journal article published
    PubMed ID: 29191878
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