@article{KunzLiangNillaetal.2016, author = {Kunz, Meik and Liang, Chunguang and Nilla, Santosh and Cecil, Alexander and Dandekar, Thomas}, title = {The drug-minded protein interaction database (DrumPID) for efficient target analysis and drug development}, series = {Database}, volume = {2016}, journal = {Database}, doi = {10.1093/database/baw041}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147369}, pages = {baw041}, year = {2016}, abstract = {The drug-minded protein interaction database (DrumPID) has been designed to provide fast, tailored information on drugs and their protein networks including indications, protein targets and side-targets. Starting queries include compound, target and protein interactions and organism-specific protein families. Furthermore, drug name, chemical structures and their SMILES notation, affected proteins (potential drug targets), organisms as well as diseases can be queried including various combinations and refinement of searches. Drugs and protein interactions are analyzed in detail with reference to protein structures and catalytic domains, related compound structures as well as potential targets in other organisms. DrumPID considers drug functionality, compound similarity, target structure, interactome analysis and organismic range for a compound, useful for drug development, predicting drug side-effects and structure-activity relationships.}, language = {en} } @article{KaltdorfSrivastavaGuptaetal.2016, author = {Kaltdorf, Martin and Srivastava, Mugdha and Gupta, Shishir K. and Liang, Chunguang and Binder, Jasmin and Dietl, Anna-Maria and Meir, Zohar and Haas, Hubertus and Osherov, Nir and Krappmann, Sven and Dandekar, Thomas}, title = {Systematic Identification of Anti-Fungal Drug Targets by a Metabolic Network Approach}, series = {Frontiers in Molecular Bioscience}, volume = {3}, journal = {Frontiers in Molecular Bioscience}, doi = {10.3389/fmolb.2016.00022}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147396}, pages = {22}, year = {2016}, abstract = {New antimycotic drugs are challenging to find, as potential target proteins may have close human orthologs. We here focus on identifying metabolic targets that are critical for fungal growth and have minimal similarity to targets among human proteins. We compare and combine here: (I) direct metabolic network modeling using elementary mode analysis and flux estimates approximations using expression data, (II) targeting metabolic genes by transcriptome analysis of condition-specific highly expressed enzymes, and (III) analysis of enzyme structure, enzyme interconnectedness ("hubs"), and identification of pathogen-specific enzymes using orthology relations. We have identified 64 targets including metabolic enzymes involved in vitamin synthesis, lipid, and amino acid biosynthesis including 18 targets validated from the literature, two validated and five currently examined in own genetic experiments, and 38 further promising novel target proteins which are non-orthologous to human proteins, involved in metabolism and are highly ranked drug targets from these pipelines.}, language = {en} } @article{ShityakovDandekarFoerster2015, author = {Shityakov, Sergey and Dandekar, Thomas and F{\"o}rster, Carola}, title = {Gene expression profiles and protein-protein interaction network analysis in AIDS patients with HIV-associated encephalitis and dementia}, series = {HIV/AIDS: Research and Palliative Care}, volume = {7}, journal = {HIV/AIDS: Research and Palliative Care}, doi = {10.2147/HIV.S88438}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-149494}, pages = {265-276}, year = {2015}, abstract = {Central nervous system dysfunction is an important cause of morbidity and mortality in patients with human immunodeficiency virus type 1 (HIV-1) infection and acquired immunodeficiency virus syndrome (AIDS). Patients with AIDS are usually affected by HIV-associated encephalitis (HIVE) with viral replication limited to cells of monocyte origin. To examine the molecular mechanisms underlying HIVE-induced dementia, the GSE4755 Affymetrix data were obtained from the Gene Expression Omnibus database and the differentially expressed genes (DEGs) between the samples from AIDS patients with and without apparent features of HIVE-induced dementia were identified. In addition, protein-protein interaction networks were constructed by mapping DEGs into protein-protein interaction data to identify the pathways that these DEGs are involved in. The results revealed that the expression of 1,528 DEGs is mainly involved in the immune response, regulation of cell proliferation, cellular response to inflammation, signal transduction, and viral replication cycle. Heat-shock protein alpha, class A member 1 (HSP90AA1), and fibronectin 1 were detected as hub nodes with degree values >130. In conclusion, the results indicate that HSP90A and fibronectin 1 play important roles in HIVE pathogenesis.}, language = {en} } @article{WolfKuonenDandekaretal.2015, author = {Wolf, Beat and Kuonen, Pierre and Dandekar, Thomas and Atlan, David}, title = {DNAseq workflow in a diagnostic context and an example of a user friendly implementation}, series = {BioMed Research International}, journal = {BioMed Research International}, number = {403497}, doi = {10.1155/2015/403497}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-144527}, year = {2015}, abstract = {Over recent years next generation sequencing (NGS) technologies evolved from costly tools used by very few, to a much more accessible and economically viable technology. Through this recently gained popularity, its use-cases expanded from research environments into clinical settings. But the technical know-how and infrastructure required to analyze the data remain an obstacle for a wider adoption of this technology, especially in smaller laboratories. We present GensearchNGS, a commercial DNAseq software suite distributed by Phenosystems SA. The focus of GensearchNGS is the optimal usage of already existing infrastructure, while keeping its use simple. This is achieved through the integration of existing tools in a comprehensive software environment, as well as custom algorithms developed with the restrictions of limited infrastructures in mind. This includes the possibility to connect multiple computers to speed up computing intensive parts of the analysis such as sequence alignments. We present a typical DNAseq workflow for NGS data analysis and the approach GensearchNGS takes to implement it. The presented workflow goes from raw data quality control to the final variant report. This includes features such as gene panels and the integration of online databases, like Ensembl for annotations or Cafe Variome for variant sharing.}, language = {en} } @article{OthmanNaseemAwadetal.2016, author = {Othman, Eman M. and Naseem, Muhammed and Awad, Eman and Dandekar, Thomas and Stopper, Helga}, title = {The Plant Hormone Cytokinin Confers Protection against Oxidative Stress in Mammalian Cells}, series = {PLoS One}, volume = {11}, journal = {PLoS One}, number = {12}, doi = {10.1371/journal.pone.0168386}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147983}, pages = {e0168386}, year = {2016}, abstract = {Modulating key dynamics of plant growth and development, the effects of the plant hormone cytokinin on animal cells gained much attention recently. Most previous studies on cytokinin effects on mammalian cells have been conducted with elevated cytokinin concentration (in the μM range). However, to examine physiologically relevant dose effects of cytokinins on animal cells, we systematically analyzed the impact of kinetin in cultured cells at low and high concentrations (1nM-10μM) and examined cytotoxic and genotoxic conditions. We furthermore measured the intrinsic antioxidant activity of kinetin in a cell-free system using the Ferric Reducing Antioxidant Power assay and in cells using the dihydroethidium staining method. Monitoring viability, we looked at kinetin effects in mammalian cells such as HL60 cells, HaCaT human keratinocyte cells, NRK rat epithelial kidney cells and human peripheral lymphocytes. Kinetin manifests no antioxidant activity in the cell free system and high doses of kinetin (500 nM and higher) reduce cell viability and mediate DNA damage in vitro. In contrast, low doses (concentrations up to 100 nM) of kinetin confer protection in cells against oxidative stress. Moreover, our results show that pretreatment of the cells with kinetin significantly reduces 4-nitroquinoline 1-oxide mediated reactive oxygen species production. Also, pretreatment with kinetin retains cellular GSH levels when they are also treated with the GSH-depleting agent patulin. Our results explicitly show that low kinetin doses reduce apoptosis and protect cells from oxidative stress mediated cell death. Future studies on the interaction between cytokinins and human cellular pathway targets will be intriguing.}, language = {en} } @article{KunzWolfSchulzeetal.2016, author = {Kunz, Meik and Wolf, Beat and Schulze, Harald and Atlan, David and Walles, Thorsten and Walles, Heike and Dandekar, Thomas}, title = {Non-Coding RNAs in Lung Cancer: Contribution of Bioinformatics Analysis to the Development of Non-Invasive Diagnostic Tools}, series = {Genes}, volume = {8}, journal = {Genes}, number = {1}, doi = {10.3390/genes8010008}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147990}, pages = {8}, year = {2016}, abstract = {Lung cancer is currently the leading cause of cancer related mortality due to late diagnosis and limited treatment intervention. Non-coding RNAs are not translated into proteins and have emerged as fundamental regulators of gene expression. Recent studies reported that microRNAs and long non-coding RNAs are involved in lung cancer development and progression. Moreover, they appear as new promising non-invasive biomarkers for early lung cancer diagnosis. Here, we highlight their potential as biomarker in lung cancer and present how bioinformatics can contribute to the development of non-invasive diagnostic tools. For this, we discuss several bioinformatics algorithms and software tools for a comprehensive understanding and functional characterization of microRNAs and long non-coding RNAs.}, language = {en} } @article{CecilRikanovicOhlsenetal.2011, author = {Cecil, Alexander and Rikanovic, Carina and Ohlsen, Knut and Liang, Chunguang and Bernhardt, Jorg and Oelschlaeger, Tobias A. and Gulder, Tanja and Bringmann, Gerd and Holzgrabe, Ulrike and Unger, Matthias and Dandekar, Thomas}, title = {Modeling antibiotic and cytotoxic effects of the dimeric isoquinoline IQ-143 on metabolism and its regulation in Staphylococcus aureus, Staphylococcus epidermidis and human cells}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-68802}, year = {2011}, abstract = {Background: Xenobiotics represent an environmental stress and as such are a source for antibiotics, including the isoquinoline (IQ) compound IQ-143. Here, we demonstrate the utility of complementary analysis of both host and pathogen datasets in assessing bacterial adaptation to IQ-143, a synthetic analog of the novel type N,C-coupled naphthyl-isoquinoline alkaloid ancisheynine. Results: Metabolite measurements, gene expression data and functional assays were combined with metabolic modeling to assess the effects of IQ-143 on Staphylococcus aureus, Staphylococcus epidermidis and human cell lines, as a potential paradigm for novel antibiotics. Genome annotation and PCR validation identified novel enzymes in the primary metabolism of staphylococci. Gene expression response analysis and metabolic modeling demonstrated the adaptation of enzymes to IQ-143, including those not affected by significant gene expression changes. At lower concentrations, IQ-143 was bacteriostatic, and at higher concentrations bactericidal, while the analysis suggested that the mode of action was a direct interference in nucleotide and energy metabolism. Experiments in human cell lines supported the conclusions from pathway modeling and found that IQ-143 had low cytotoxicity. Conclusions: The data suggest that IQ-143 is a promising lead compound for antibiotic therapy against staphylococci. The combination of gene expression and metabolite analyses with in silico modeling of metabolite pathways allowed us to study metabolic adaptations in detail and can be used for the evaluation of metabolic effects of other xenobiotics.}, subject = {Staphylococcus aureus}, language = {en} } @article{WangorschButtMarketal.2011, author = {Wangorsch, Gaby and Butt, Elke and Mark, Regina and Hubertus, Katharina and Geiger, J{\"o}rg and Dandekar, Thomas and Dittrich, Marcus}, title = {Time-resolved in silico modeling of fine-tuned cAMP signaling in platelets: feedback loops, titrated phosphorylations and pharmacological modulation}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-69145}, year = {2011}, abstract = {Background: Hemostasis is a critical and active function of the blood mediated by platelets. Therefore, the prevention of pathological platelet aggregation is of great importance as well as of pharmaceutical and medical interest. Endogenous platelet inhibition is predominantly based on cyclic nucleotides (cAMP, cGMP) elevation and subsequent cyclic nucleotide-dependent protein kinase (PKA, PKG) activation. In turn, platelet phosphodiesterases (PDEs) and protein phosphatases counterbalance their activity. This main inhibitory pathway in human platelets is crucial for countervailing unwanted platelet activation. Consequently, the regulators of cyclic nucleotide signaling are of particular interest to pharmacology and therapeutics of atherothrombosis. Modeling of pharmacodynamics allows understanding this intricate signaling and supports the precise description of these pivotal targets for pharmacological modulation. Results: We modeled dynamically concentration-dependent responses of pathway effectors (inhibitors, activators, drug combinations) to cyclic nucleotide signaling as well as to downstream signaling events and verified resulting model predictions by experimental data. Experiments with various cAMP affecting compounds including antiplatelet drugs and their combinations revealed a high fidelity, fine-tuned cAMP signaling in platelets without crosstalk to the cGMP pathway. The model and the data provide evidence for two independent feedback loops: PKA, which is activated by elevated cAMP levels in the platelet, subsequently inhibits adenylyl cyclase (AC) but as well activates PDE3. By multi-experiment fitting, we established a comprehensive dynamic model with one predictive, optimized and validated set of parameters. Different pharmacological conditions (inhibition, activation, drug combinations, permanent and transient perturbations) are successfully tested and simulated, including statistical validation and sensitivity analysis. Downstream cyclic nucleotide signaling events target different phosphorylation sites for cAMP- and cGMP-dependent protein kinases (PKA, PKG) in the vasodilator-stimulated phosphoprotein (VASP). VASP phosphorylation as well as cAMP levels resulting from different drug strengths and combined stimulants were quantitatively modeled. These predictions were again experimentally validated. High sensitivity of the signaling pathway at low concentrations is involved in a fine-tuned balance as well as stable activation of this inhibitory cyclic nucleotide pathway. Conclusions: On the basis of experimental data, literature mining and database screening we established a dynamic in silico model of cyclic nucleotide signaling and probed its signaling sensitivity. Thoroughly validated, it successfully predicts drug combination effects on platelet function, including synergism, antagonism and regulatory loops.}, subject = {Vasodilatator-stimuliertes Phosphoprotein}, language = {en} } @article{BeisserGrohmeKopkaetal.2012, author = {Beisser, Daniela and Grohme, Markus A. and Kopka, Joachim and Frohme, Marcus and Schill, Ralph O. and Hengherr, Steffen and Dandekar, Thomas and Klau, Gunnar W. and Dittrich, Marcus and M{\"u}ller, Tobias}, title = {Integrated pathway modules using time-course metabolic profiles and EST data from Milnesium tardigradum}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-75241}, year = {2012}, abstract = {Background: Tardigrades are multicellular organisms, resistant to extreme environmental changes such as heat, drought, radiation and freezing. They outlast these conditions in an inactive form (tun) to escape damage to cellular structures and cell death. Tardigrades are apparently able to prevent or repair such damage and are therefore a crucial model organism for stress tolerance. Cultures of the tardigrade Milnesium tardigradum were dehydrated by removing the surrounding water to induce tun formation. During this process and the subsequent rehydration, metabolites were measured in a time series by GC-MS. Additionally expressed sequence tags are available, especially libraries generated from the active and inactive state. The aim of this integrated analysis is to trace changes in tardigrade metabolism and identify pathways responsible for their extreme resistance against physical stress. Results: In this study we propose a novel integrative approach for the analysis of metabolic networks to identify modules of joint shifts on the transcriptomic and metabolic levels. We derive a tardigrade-specific metabolic network represented as an undirected graph with 3,658 nodes (metabolites) and 4,378 edges (reactions). Time course metabolite profiles are used to score the network nodes showing a significant change over time. The edges are scored according to information on enzymes from the EST data. Using this combined information, we identify a key subnetwork (functional module) of concerted changes in metabolic pathways, specific for de- and rehydration. The module is enriched in reactions showing significant changes in metabolite levels and enzyme abundance during the transition. It resembles the cessation of a measurablemetabolism (e.g. glycolysis and amino acid anabolism) during the tun formation, the production of storage metabolites and bioprotectants, such as DNA stabilizers, and the generation of amino acids and cellular components from monosaccharides as carbon and energy source during rehydration. Conclusions: The functional module identifies relationships among changed metabolites (e.g. spermidine) and reactions and provides first insights into important altered metabolic pathways. With sparse and diverse data available, the presented integrated metabolite network approach is suitable to integrate all existing data and analyse it in a combined manner.}, subject = {Milnesium tardigradum}, language = {en} } @article{ShityakovDandekar2010, author = {Shityakov, Sergey and Dandekar, Thomas}, title = {Lead expansion and virtual screening of Indinavir derivate HIV-1 protease inhibitors using pharmacophoric - shape similarity scoring function}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-67824}, year = {2010}, abstract = {Indinavir (Crivaxan®) is a potent inhibitor of the HIV (human immunodeficiency virus) protease. This enzyme has an important role in viral replication and is considered to be very attractive target for new antiretroviral drugs. However, it becomes less effective due to highly resistant new viral strains of HIV, which have multiple mutations in their proteases. For this reason, we used a lead expansion method to create a new set of compounds with a new mode of action to protease binding site. 1300 compounds chemically diverse from the initial hit were generated and screened to determine their ability to interact with protease and establish their QSAR properties. Further computational analyses revealed one unique compound with different protease binding ability from the initial hit and its role for possible new class of protease inhibitors is discussed in this report.}, subject = {Proteasen}, language = {en} }