SCG
Systematic Chemical Genetic Interrogation of Biological Networks
| Coordinatore | THE UNIVERSITY OF EDINBURGH
Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie. |
| Nazionalità Coordinatore | United Kingdom [UK] |
| Totale costo | 2˙400˙000 € |
| EC contributo | 2˙400˙000 € |
| Programma | FP7-IDEAS-ERC
Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | ERC-2008-AdG |
| Funding Scheme | ERC-AG |
| Anno di inizio | 2009 |
| Periodo (anno-mese-giorno) | 2009-08-01 - 2014-07-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
THE UNIVERSITY OF EDINBURGH
Organization address
address: OLD COLLEGE, SOUTH BRIDGE contact info |
UK (EDINBURGH) | hostInstitution | 2˙400˙000.00 |
| 2 |
THE UNIVERSITY OF EDINBURGH
Organization address
address: OLD COLLEGE, SOUTH BRIDGE contact info |
UK (EDINBURGH) | hostInstitution | 2˙400˙000.00 |
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Obiettivo del progetto (Objective)
'Recent genome-scale studies have revealed the massive redundancies and functional interconnectivities encoded by the genome. For example, the budding yeast Saccharomyces cerevisiae is predicted to harbor 200,000 synthetic lethal interactions. This genetic density has profound implications for both understanding the architecture of living systems and drug discovery. In particular, the dense connections of biological networks mandate a multi-node strategy to selectively manipulate any given biological response, whether it be to probe system level properties or for therapeutic intervention in human disease. By analogy to Ehrlich s magic bullet concept, we term this approach the magic shotgun . We propose to systematically identify chemical-genetic interactions that selectively disrupt any specific mutant genotype and chemical-chemical interactions that selectively kill pathogenic species. Our five main objectives are: (i) construct a comprehensive Chemical Genetic Matrix (CGM) of small molecule-gene interactions in order to predict chemical synergies and manipulate network function in a species-specific manner; (ii) elaborate the CGM with a set of ~5,000 yeast bioactive molecules derived from high throughput/high content screens; (iii) identify small molecule combinations that modulate stem cell and cancer cell renewal and differentiation; (iv) define compound mechanisms of action by functional genomics; (v) integrate chemical-genetic, genetic and protein interaction datasets to predict gene function, small molecule targets and network properties. This research will cross-connect genetic pathways through chemical space, identify species-specific combinations of agents as therapeutic leads and provide a repository of small molecule probes for cell biological and systems-level analysis. The principles developed through the course of this work will raise our understanding of biological networks and help establish a new approach to drug discovery.'