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Protein signalling pathways elucidated via novel correlation analysis of molecular dynamics simulations (PROTSIGN)
Start date: 01 Jun 2009, End date: 31 May 2011 PROJECT  FINISHED 

"Signal transduction enables biological cells to respond to external stimuli such as light, odours, hormones, or growth factors. Signalling is involved in numerous biological processes and dysfunction of signalling has been associated to severe conditions such as cancer or Alzheimer’s disease. Whereas the knowledge of signal transduction on the cellular level has seen impressive progress within the last years, the molecular mechanisms involved in signalling remain mostly unknown. Intra-protein signalling is accomplished by subtle configurational changes and/or rapid dynamic processes which are difficult to assess experimentally. Therefore, we aim to employ molecular dynamics (MD) simulations to elucidate intra-protein signalling pathways and molecular mechanisms involved in signalling. Two important classes of signalling proteins will be studied: G-protein coupled receptors (GPCRs) and PDZ protein binding domains. The key to elucidate the signalling pathways will be to identify the correlations in protein dynamics and ensembles which transmit the biological signal. We plan to employ procedures from information theory and multivariate analysis to directly assess the propagation of the signal in the protein motions. The approach promises to clearly separate intra-protein processes involved in signalling from motions and interactions which may be important (e.g. for protein stability), but which do not contribute to the signal. Moreover, the simulations will allow us to distinguish between the “induced-fit” and the “conformational selection” model for signal transduction. By applying these methods to GPCRs and different PDZ domains we aim to determine common routes of information transfer within these important classes of proteins. Understanding how information is transferred within living organisms is a prerequisite for interfering with signalling, and hence our approach may contribute to novel therapies in the future."
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