Novel compounds reducing IRS-1 serine phosphorylation for treatment of diabetes.

Activation of various interacting stress kinases, particularly the c-Jun N-terminal kinases (JNK), and a concomitant phosphorylation of insulin receptor substrate 1 (IRS-1) at serine 307 play a central role both in insulin resistance and in ß-cell dysfunction. IRS-1 phosphorylation is stimulated by elevated free fatty acid levels through different pathways in obesity. A series of novel pyrido[2,3-d]pyrimidin-7-one derivatives were synthesized as potential antidiabetic agents, preventing IRS-1 phosphorylation at serine 307 in a cellular model of lipotoxicity and type 2 diabetes.

Complex regulation of autophagy in cancer - integrated approaches to discover the networks that hold a double-edged sword.

Autophagy, a highly regulated self-degradation process of eukaryotic cells, is a context-dependent tumor-suppressing mechanism that can also promote tumor cell survival upon stress and treatment resistance. Because of this ambiguity, autophagy is considered as a double-edged sword in oncology, making anti-cancer therapeutic approaches highly challenging. In this review, we present how systems-level knowledge on autophagy regulation can help to develop new strategies and efficiently select novel anti-cancer drug targets. We focus on the protein interactors and transcriptional/post-transcriptional regulators of autophagy as the protein and regulatory networks significantly influence the activity of core autophagy proteins during tumor progression. We list several network resources to identify interactors and regulators of autophagy proteins. As in silico analysis of such networks often necessitates experimental validation, we briefly summarize tractable model organisms to examine the role of autophagy in cancer. We also discuss fluorescence techniques for high-throughput monitoring of autophagy in humans. Finally, the challenges of pharmacological modulation of autophagy are reviewed. We suggest network-based concepts to overcome these difficulties. We point out that a context-dependent modulation of autophagy would be favored in anti-cancer therapy, where autophagy is stimulated in normal cells, while inhibited only in stressed cancer cells. To achieve this goal, we introduce the concept of regulo-network drugs targeting specific transcription factors or miRNA families identified with network analysis. The effect of regulo-network drugs propagates indirectly through transcriptional or post-transcriptional regulation of autophagy proteins, and, as a multi-directional intervention tool, they can both activate and inhibit specific proteins in the same time. The future identification and validation of such regulo-network drug targets may serve as novel intervention points, where autophagy can be effectively modulated in cancer therapy.

[Developing FGFR inhibitors as potential anti-cancer agents]. / Potenciális antitumor hatású FGFR inhibitorok fejlesztése.

Fibroblast Growth Factor Receptor (FGFR) family is a sequentially highly related subgroup of membrane proteins consisting of four tyrosine kinase type enzyme: FGFR1, FGFR2, FGFR3 and FGFR4. These are kinases of great interest in a wide spectrum of physiological processes such as tissue repair via controlling cell proliferation. As initiatiors of cell proliferation, in some cases they have leading roles in several types of cancer, eg. breast cancer, pancreas cancer, gastric tumors and multiple myeloma via overexpression and/or mutation. This phenomenon makes them promising targets for drug development in order to develop signal transduction therapies based on small molecule FGFR inhibitors. We have developed two main groups of lead molecules: compounds with benzotiophene and oxindole cores utilizing numerous methods from in silico modelling via in vitro biochemichal assays and testing on relevant cell lines to cytotoxicity assays.

[Development and study of structure-activity relationship of drugs against Mycobacterium tuberculosis]. / Mycobacterium tuberculosis ellenes hatóanyagok fejlesztése és szerkezet-hatás összefüggéseinek vizsgálata.

Tuberculosis is considered to be one of the major health problem not only in the less developed countries but in the economically developed countries as well. Roughly one third of the world's population are infected with Mycobacterium tuberculosis and a significant part of them are carriers of latent tuberculosis. From ten percent of these latent infections are developing the active TB disease and fifty percent of them die from the illness without appropriate treatment. The drug-resistant Mycobacterium tuberculosis (MDR-TB, XDR-TB) and TB-HIV co-infection attracted attention to the most serious infectious disease. Inhibition of alternative signaling pathways were an important part of the research strategies for cancer and inflammatory diseases in recent years. In case of Mycobacterium tuberculosis such pathways were also identified, for example, three serine-threonine kinases (PknA, PknB, PknG) which are necessary and essential for bacterial growth. In this paper we summarize our best anti-TB active compounds, their biological effects and structure-activity relationships using in silico modeling, biochemical measurements and tests on active bacteria.

Targeted drug combination therapy design based on driver genes.

Targeted therapies against cancer types with more than one driver gene hold bright but elusive promise, since approved drugs are not available for all driver mutations and monotherapies often result in resistance. Targeting multiple driver genes in different pathways at the same time may provide an impact extensive enough to fight resistance. Our goal was to find synergistic drug combinations based on the availability of targeted drugs and their biological activity profiles and created an associated compound library based on driver gene-related protein targets. In this study, we would like to show that driver gene pattern based customized combination therapies are more effective than monotherapies on six cell lines and patient-derived primary cell cultures. We tested 55-102 drug combinations targeting driver genes and driver pathways for each cell line and found 25-85% of these combinations highly synergistic. Blocking 2-5 cancer pathways using only 2-3 targeted drugs was sufficient to reach high rates of tumor cell eradication at remarkably low concentrations. Our results demonstrate that the efficiency of cancer treatment may be significantly improved by combining drugs against multiple tumor specific drivers.

SignaLink 2 - a signaling pathway resource with multi-layered regulatory networks.

BACKGROUND: Signaling networks in eukaryotes are made up of upstream and downstream subnetworks. The upstream subnetwork contains the intertwined network of signaling pathways, while the downstream regulatory part contains transcription factors and their binding sites on the DNA as well as microRNAs and their mRNA targets. Currently, most signaling and regulatory databases contain only a subsection of this network, making comprehensive analyses highly time-consuming and dependent on specific data handling expertise. The need for detailed mapping of signaling systems is also supported by the fact that several drug development failures were caused by undiscovered cross-talk or regulatory effects of drug targets. We previously created a uniformly curated signaling pathway resource, SignaLink, to facilitate the analysis of pathway cross-talks. Here, we present SignaLink 2, which significantly extends the coverage and applications of its predecessor. DESCRIPTION: We developed a novel concept to integrate and utilize different subsections (i.e., layers) of the signaling network. The multi-layered (onion-like) database structure is made up of signaling pathways, their pathway regulators (e.g., scaffold and endocytotic proteins) and modifier enzymes (e.g., phosphatases, ubiquitin ligases), as well as transcriptional and post-transcriptional regulators of all of these components. The user-friendly website allows the interactive exploration of how each signaling protein is regulated. The customizable download page enables the analysis of any user-specified part of the signaling network. Compared to other signaling resources, distinctive features of SignaLink 2 are the following: 1) it involves experimental data not only from humans but from two invertebrate model organisms, C. elegans and D. melanogaster; 2) combines manual curation with large-scale datasets; 3) provides confidence scores for each interaction; 4) operates a customizable download page with multiple file formats (e.g., BioPAX, Cytoscape, SBML). Non-profit users can access SignaLink 2 free of charge at http://SignaLink.org. CONCLUSIONS: With SignaLink 2 as a single resource, users can effectively analyze signaling pathways, scaffold proteins, modifier enzymes, transcription factors and miRNAs that are important in the regulation of signaling processes. This integrated resource allows the systems-level examination of how cross-talks and signaling flow are regulated, as well as provide data for cross-species comparisons and drug discovery analyses.