Biomedical subjects

Evangelos Hytopoulos

Publications and source records attributed to Evangelos Hytopoulos.

5 recordsLinked to original sources

PubMed2005

Characterization of compound mechanisms and secondary activities by BioMAP analysis.

INTRODUCTION: Unexpected drug activities account for many of the failures of new chemical entities in clinical trials. These activities can be target-dependent, resulting from feedback mechanisms downstream of the primary target, or they can occur as a result of unanticipated secondary target(s). Methods that would provide rapid and efficient characterization of compounds with respect to a broad range of biological pathways and mechanisms relevant to human disease have the potential to improve preclinical and clinical success rates. METHODS: BioMAP assays containing primary human cells (endothelial cells and co-cultures with peripheral blood leukocytes) were stimulated in complex formats (specific combinations of inflammatory mediators) for 24 h in the presence or absence of test agents (drugs, experimental compounds, etc.). The levels of selected protein readouts (adhesion receptors, cytokines, enzymes, etc.) were measured and activity profiles (normalized data sets comprising BioMAP profiles) were generated for each test agent. The resulting profiles were compared by statistical methods to identify similarities and mechanistic insights. RESULTS: Compounds with known mechanisms including inhibitors of histamine H1 receptor, angiotensin converting enzyme, IkappaB kinase-2, beta2 adrenergic receptor and others were shown to generate reproducible and distinguishable BioMAP activity profiles. Similarities were observed between compounds targeting components within the same signal transduction pathway (e.g. NFkappaB), and also between compounds that share secondary targets (e.g. ibuprofen and FMOC-L-leucine, a PPARgamma agonist). DISCUSSION: Complex primary cell-based assays can be applied for detecting and distinguishing unexpected activities that may be of relevance to drug action in vivo. The ability to rapidly test compounds prior to animal or clinical studies may reduce the number of compounds that unexpectedly fail in preclinical or clinical studies.

Butadienes↗

PubMed2005

Approaches to the analysis of cell signaling networks and their application in drug discovery.

The ability to predict the safety and efficacy of novel drugs prior to clinical testing is a key goal in pharmaceutical drug discovery. Gaining a mechanistic understanding of the complex cell signaling networks (CSNs) underlying disease processes promises to help reduce the number of clinical failures by identifying points of intervention as well as redundancies and feedback mechanisms that contribute to toxicities, lack of efficacy and unexpected biological activities. Experimental and computational approaches to analyzing and modeling CSNs are currently being validated using simple organisms and cell lines. In vitro cell systems of sufficient complexity to resemble human disease physiology, but which are also amenable to chemical and genetic perturbations on a large scale, are now required for deciphering the signaling networks operating in human disease. In this review, experimental and computational methods for modeling complex CSNs and the applications of these approaches to pharmaceutical drug discovery are discussed.

Animals↗

PubMed2004

An integrative biology approach for analysis of drug action in models of human vascular inflammation.

Unexpected drug activities discovered during clinical testing establish the need for better characterization of compounds in human disease-relevant conditions early in the discovery process. Here, we describe an approach to characterize drug function based on statistical analysis of protein expression datasets from multiple primary human cell-based models of inflammatory disease. This approach, termed Biologically Multiplexed Activity Profiling (BioMAP), provides rapid characterization of drug function, including mechanism of action, secondary or off-target activities, and insights into clinical phenomena. Using three model systems containing primary human endothelial cells and peripheral blood mononuclear cells in different environments relevant to vascular inflammation and immune activation, we show that BioMAP profiles detect and discriminate multiple functional drug classes, including glucocorticoids; TNF-alpha antagonists; and inhibitors of HMG-CoA reductase, calcineurin, IMPDH, PDE4, PI-3 kinase, hsp90, and p38 MAPK, among others. The ability of cholesterol lowering HMG-CoA reductase inhibitors (statins) to improve outcomes in rheumatic disease patients correlates with the activities of these compounds in our BioMAP assays. In addition, the activity profiles identified for the immunosuppressants mycophenolic acid, cyclosporin A, and FK-506 provide a potential explanation for a reduced incidence of posttransplant cardiovascular disease in patients receiving mycophenolic acid. BioMAP profiling can allow integration of meaningful human biology into drug development programs.

Anti-Inflammatory Agents↗

PubMed2004

Method for analyzing signaling networks in complex cellular systems.

Now that the human genome has been sequenced, the challenge of assigning function to human genes has become acute. Existing approaches using microarrays or proteomics frequently generate very large volumes of data not directly related to biological function, making interpretation difficult. Here, we describe a technique for integrative systems biology in which: (i) primary cells are cultured under biologically meaningful conditions; (ii) a limited number of biologically meaningful readouts are measured; and (iii) the results obtained under several different conditions are combined for analysis. Studies of human endothelial cells overexpressing different signaling molecules under multiple inflammatory conditions show that this system can capture a remarkable range of functions by a relatively small number of simple measurements. In particular, measurement of seven different protein levels by ELISA under four different conditions is capable of reconstructing pathway associations of 25 different proteins representing four known signaling pathways, implicating additional participants in the NF-kappaBorRAS/mitogen-activated protein kinase pathways and defining additional interactions between these pathways.

Cells, Cultured↗

PubMed2004

Rapid structure-activity and selectivity analysis of kinase inhibitors by BioMAP analysis in complex human primary cell-based models.

Rapid, quantitative methods for characterizing the biological activities of kinase inhibitors in complex human cell systems could allow the biological consequences of differential target selectivity to be monitored early in development, improving the selection of drug candidates. We have previously shown that Biologically Multiplexed Activity Profiling (BioMAP) permits rapid characterization of drug function based on statistical analysis of protein expression data sets from complex primary human cellbased models of disease biology. Here, using four such model systems containing primary human endothelial cells and peripheral blood mononuclear cells in which multiple signaling pathways relevant to inflammation and immune responses are simultaneously activated, we demonstrate that BioMAP analysis can detect and distinguish a wide range of inhibitors directed against different kinase targets. Using a panel of p38 mitogen-activated protein kinase antagonists as a test set, we show further that related compounds can be distinguished by unique features of the biological responses they induce in complex systems, and can be classified according to their induction of shared (on-target) and secondary activities. Statistical comparisons of quantitative BioMAP profiles and analysis of profile features allow correlation of induced biological effects with chemical structure and mapping of biological responses to chemical series or substituents on a common scaffold. Integration of automated BioMAP analysis for prioritization of hits and for structure-activity relationship studies may improve and accelerate the design and selection of optimal therapeutic candidates.

Animals↗