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SUMMARY:CNN seminar: Network Pharmacology for Parkinson's Disease - Harrie
 t Keane (University of Oxford) 
DTSTART:20140304T163000Z
DTEND:20140304T173000Z
UID:TALK51120@talks.cam.ac.uk
CONTACT:Petra Vertes
DESCRIPTION:Network pharmacology offers a new approach to identifying pote
 ntial drug targets in diseases with complex aetiology. Parkinson’s disea
 se (PD) is used as an exemplar of such a disease due to its sporadic natur
 e and the involvement of multiple cellular pathways. PD is the second most
  common neurodegenerative disease with a prevalence of 5% at age 85. Despi
 te this\, there is currently no cure for PD or treatment capable of slowin
 g disease progression. Many of the key features of PD can be reproduced us
 ing the neurotoxin MPP+\, a complex I inhibitor that induces cytotoxicity 
 via a programmed cell death (apoptotic) mechanism. Although key processes 
 in MPP+ toxicity have been characterised\, analysis of the underlying biol
 ogical network can offer an insight into the interplay of these individual
  processes and pathways.\n\nI will discuss the construction of protein-pro
 tein interaction networks (PPN) to model MPP+ induced cell death\, using i
 RefIndex as a consolidated source of protein-protein interaction data. I a
 nalysed these networks to identify nodes whose deletion was expected to ha
 ve a significant effect on MPP+ induced cell death and validated these pre
 dictions using our in vitro system. I further demonstrated that a partial 
 rescue from MPP+ neurotoxicity can be achieved using the combined overexpr
 ession of four network targets. However\, no single intervention is effect
 ive: we need multiple\, targeted interventions to alter the biological out
 come of the system. As well as the biological insights into the MPP+   mod
 el of PD\, this was an exciting opportunity to directly test the approach 
 of network pharmacology in vitro\, and I will discuss the opportunities an
 d challenges presented.\n
LOCATION:Keynes Hall in King's College
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