Ahrens V.M.,University of Leipzig |
Kostelnik K.B.,University of Leipzig |
Rennert R.,OntoChem GmbH |
Bohme D.,University of Leipzig |
And 6 more authors.
Journal of Controlled Release | Year: 2015
Abstract Myxobacterial tubulysins are promising chemotherapeutics inhibiting microtubule polymerization, however, high unspecific toxicity so far prevents their application in therapy. For selective cancer cell targeting, here the coupling of a synthetic cytolysin to the hY1-receptor preferring peptide [F7,P34]-neuropeptide Y (NPY) using a labile disulfide linker is described. Since hY1-receptors are overexpressed in breast tumors and internalize rapidly, this system has high potential as peptide-drug shuttle system. Molecular characterization of the cytolysin-[F7,P34]-NPY bioconjugate revealed potent receptor activation and receptor-selective internalization, while viability studies verified toxicity. Triple SILAC studies comparing free cytolysin with the bioconjugate demonstrated an intracellular mechanism of action regardless of the delivery pathway. Treatments resulted in a regulation of proteins implemented in cell cycle arrest confirming the tubulysin-like effect of the cytolysin. Thus, the cytolysin-peptide bioconjugate fused by a cleavable linker enables a receptor-specific delivery as well as a potent intracellular drug-release with high cytotoxic activity. © 2015 Published by Elsevier B.V.
PubMed | Hubei University, Beijing Forestry University, University of Lisbon, Manchester Institute of Biotechnology and 27 more.
Type: Journal Article | Journal: Journal of cheminformatics | Year: 2015
The automatic extraction of chemical information from text requires the recognition of chemical entity mentions as one of its key steps. When developing supervised named entity recognition (NER) systems, the availability of a large, manually annotated text corpus is desirable. Furthermore, large corpora permit the robust evaluation and comparison of different approaches that detect chemicals in documents. We present the CHEMDNER corpus, a collection of 10,000 PubMed abstracts that contain a total of 84,355 chemical entity mentions labeled manually by expert chemistry literature curators, following annotation guidelines specifically defined for this task. The abstracts of the CHEMDNER corpus were selected to be representative for all major chemical disciplines. Each of the chemical entity mentions was manually labeled according to its structure-associated chemical entity mention (SACEM) class: abbreviation, family, formula, identifier, multiple, systematic and trivial. The difficulty and consistency of tagging chemicals in text was measured using an agreement study between annotators, obtaining a percentage agreement of 91. For a subset of the CHEMDNER corpus (the test set of 3,000 abstracts) we provide not only the Gold Standard manual annotations, but also mentions automatically detected by the 26 teams that participated in the BioCreative IV CHEMDNER chemical mention recognition task. In addition, we release the CHEMDNER silver standard corpus of automatically extracted mentions from 17,000 randomly selected PubMed abstracts. A version of the CHEMDNER corpus in the BioC format has been generated as well. We propose a standard for required minimum information about entity annotations for the construction of domain specific corpora on chemical and drug entities. The CHEMDNER corpus and annotation guidelines are available at: http://www.biocreative.org/resources/biocreative-iv/chemdner-corpus/.
Bobach C.,Leibniz Institute of Plant Biochemistry |
Bobach C.,Ontochem GmbH |
Tennstedt S.,Leibniz Institute of Plant Biochemistry |
Tennstedt S.,University of Lübeck |
And 6 more authors.
European Journal of Medicinal Chemistry | Year: 2014
The androgen receptor is an important pharmaceutical target for a variety of diseases. This paper presents an in silico/in vitro screening procedure to identify new androgen receptor ligands. The two-step virtual screening procedure uses a three-dimensional pharmacophore model and a docking/scoring routine. About 39,000 filtered compounds were docked with PLANTS and scored by Chemplp. Subsequent to virtual screening, 94 compounds, including 28 steroidal and 66 nonsteroidal compounds, were tested by an androgen receptor fluorescence polarization ligand displacement assay. As a result, 30 compounds were identified that show a relative binding affinity of more than 50% in comparison to 100 nM dihydrotestosterone and were classified as androgen receptor binders. For 11 androgen receptor binders of interest IC50 and Ki values were determined. The compound with the highest affinity exhibits a Ki value of 10.8 nM. Subsequent testing of the 11 compounds in a PC-3 and LNCaP multi readout proliferation assay provides insights into the potential mode of action. Further steroid receptor ligand displacement assays and docking studies on estrogen receptors α and β, glucocorticoid receptor, and progesterone receptor gave information about the specificity of the 11 most active compounds. © 2014 Elsevier Masson SAS.
Bobach C.,Leibniz Institute of Plant Biochemistry |
Bobach C.,Ontochem GmbH |
Schurwanz J.,Leibniz Institute of Plant Biochemistry |
Franke K.,Leibniz Institute of Plant Biochemistry |
And 7 more authors.
Journal of Ethnopharmacology | Year: 2014
Ethnopharmacological relevance Prostate cancer is one of the most diagnosed forms of cancer among men in western regions. Many traditional applications or phytotherapeutic concepts propose to inhibit the proliferation of prostate cancer cells. In order to detect influences of plant or fungal extracts and derived fractions on androgen receptor signaling pathways, a differentiating cell proliferation assay was established, which enables the simultaneous detection of hormonal and cytotoxic effects. Material and methods The well characterized prostate cancer cell lines LNCaP and PC-3 were used in a multiple readout assay. In all, 186 fractions of 23 traditionally used organisms were screened regarding their effects on proliferation of the two prostate cancer cell lines. The fractions were prepared by accelerated solvent extraction followed by gradient extrography. Extracts of the potential hormonally active plants Cibotium barometz, Heteropterys chrysophylla, and Sideroxylon obtusifolium (= Bumelia sartorum) were phytochemically investigated. Results Fractions from Cibotium barometz, Cortinarius rubellus, Cyrtomium falcatum, Heteropterys chrysophylla, Nephrolepis exaltata, Salvia miltiorrhiza, Sideroxylon obtusifolium, Trichilia emetica, and Trimeria grandifolia exhibited hormonal influences on prostate cancer cells. Cytotoxic activity towards human cell lines was detected for the first time for fractions from Aglaia spectabilis (A. gigantea), Nephrolepis exaltata and Cortinarius brunneus. Conclusions The differential behavior of the two prostate cancer cell lines allows the discrimination between potential androgenic or antiandrogenic activities and effects on the estrogen or glucocorticoid receptor as well as cytotoxic activities. The combined cell lines assay can help to assess the biological activities of material used in traditional medicine. © 2014 Elsevier Ireland Ltd. All rights reserved.
Mittag K.,OntoChem GmbH |
Hinneburg A.,Martin Luther University of Halle Wittenberg
INFORMATIK 2010 - Service Science - Neue Perspektiven fur die Informatik, Beitrage der 40. Jahrestagung der Gesellschaft fur Informatik e.V. (GI) | Year: 2010
Information needs like searching scientific literature that involve high recall rates are difficult to satisfy with ad hoc keyword search. We propose to state queries implicitly by the specification of a set of query documents. The result of such a query is a set of answer documents that are ranked within the answer set. We describe efficient techniques to process such queries. Preliminary experiments using data from the TREC Genomics track 2005 are reported.
Bobach C.,OntoChem GmbH |
Bohme T.,OntoChem GmbH |
Laube U.,OntoChem GmbH |
Puschel A.,OntoChem GmbH |
Weber L.,OntoChem GmbH
Journal of Cheminformatics | Year: 2012
Background Classification of chemical compounds into compound classes by using structure derived descriptors is a well-established method to aid the evaluation and abstraction of compound properties in chemical compound databases. MeSH and recently ChEBI are examples of chemical ontologies that provide a hierarchical classification of compounds into general compound classes of biological interest based on their structural as well as property or use features. In these ontologies, compounds have been assigned manually to their respective classes. However, with the ever increasing possibilities to extract new compounds from text documents using name-to-structure tools and considering the large number of compounds deposited in databases, automated and comprehensive chemical classification methods are needed to avoid the error prone and time consuming manual classification of compounds. © 2012 Bachrach; licensee Chemistry Central Ltd.
OntoChem GmbH | Date: 2010-10-27
A treatment using a hydroxysteroid dehydrogenase reductase inhibitor combined with a mineralocorticoid receptor antagonist is provided which overcomes the problem that manipulating cortisol levels by a single compound therapy induces other pathologies or side effects, while the original condition that required treatment is ameliorated.
OntoChem GmbH | Date: 2014-03-19
The present invention relates to conjugates comprising cytotoxic compounds conjugated via a linker moiety to neuropeptide Y1 receptor ligands and their use for the treatment of cancer and other diseases.
Ontochem Gmbh | Date: 2013-09-17
The present invention refers to neuropeptide Y receptor 1 (NPY-1) binding ligands linked to cytotoxic molecules and their use for the treatment of cancer and other diseases.
PubMed | OntoChem GmbH
Type: Journal Article | Journal: Pharmaceutical patent analyst | Year: 2013
Ontology-based semantic text analysis methods allow to automatically extract knowledge relationships and data from text documents. In this review, we have applied these technologies for the systematic analysis of pharmaceutical patents. Hierarchical concepts from the knowledge domains of chemical compounds, diseases and proteins were used to annotate full-text US patent applications that deal with pharmacological activities of chemical compounds and filed in the years 2001-2010. Compounds claimed in these applications have been classified into their respective compound classes to review the distribution of scaffold types or general compound classes such as natural products in a time-dependent manner. Similarly, the target proteins and claimed utility of the compounds have been classified and the most relevant were extracted. The method presented allows the discovery of the main areas of innovation as well as emerging fields of patenting activities - providing a broad statistical basis for competitor analysis and decision-making efforts.