Research Report 2010 - MDC Title

Scientific-Technical Staff
Anja Fritzsche*
Ronny Kalis*
Sandra Neuendorf
Stephanie Plaßmann
Kirstin Rau
Anke Thieme
Franziska Schiele*
Martina Zenkner
Technical Assistants
Nouhad Benlasfer*
Anna Happe-Kramer*
Daniela Kleckers
Susanne Köppen*
Susanne Rautenberg
aggregation intermediates into large amyloid structures
might be a powerful therapeutic approach to
treat protein misfolding diseases.
In order to investigate whether the small molecules
that modulate amyloid formation pathways in vitro and
in vivo are useful for therapy development, a drug discovery
program for AD and HD was started in 2007 in
the framework of the GO-Bio initiative of the German
Federal Ministry for Education and Research. The aim of
this program is to promote the establishment of innovative
start-up companies out of the academic sector. In
the first funding phase of the Go-Bio project, we have
discovered a number of novel drug candidates for both
AD and HD and developed them up to in vivo proof of
concept in transgenic mouse models of the two diseases.
At the moment, derivatisation and further in vivo
testing are in progress in the framework of lead optimisation.
Identification of proteins that modulate polyQmediated
huntingtin aggregation
HD is an inherited neurodegenerative disorder that is
caused by an expansion of a polyQ tract in the protein
huntingtin, which leads to a characteristic accumulation
of insoluble Htt aggregates in affected neurons
and eventually to cellular dysfunction and toxicity.
However, the molecular pathways underlying brainspecific,
polyQ-induced neurodegeneration in HD are
still unknown. Recently, a large number of interaction
partners were identified that associate with the N-terminal
domain of huntingtin, which harbours the aggregation-prone
polyQ tract. We hypothesized that perturbation
of functional huntingtin protein complexes in
neurons induces protein misfolding and neurotoxicity.
To identify tissue-specific, dysregulated huntingtin protein
interactions, a bioinformatic approach was developed.
By filtering publically available protein-protein
interaction (PPI) data with information from gene
expression studies of brain and non-brain tissues as
well as clinical case-control studies, a brain-specific
huntingtin PPI network was created, linking 14 poten-
184 Function and Dysfunction of the Nervous System
Alexandra Redel
Dana Rotte*
Kati Scharf*
Nancy Schugardt
Jan Timm
Carsta Werner*
Projekt Management
(NGFN2 SMP Protein)
Dr. Patrick Umbach*
Project Management
(NGFN-Plus/NeuroNet)
Dr. Paul Schultze-Motel*
tially dysregulated proteins directly or indirectly to the
disease protein. Analysis of published data confirmed
the predictive value of this network modelling strategy.
Moreover, systematic investigations with in vitro and
Drosophila model systems of HD demonstrated that
the potentially dysregulated huntingtin interaction
partners influence polyQ-mediated protein misfolding
and neurodegeneration. The neuron-specific protein
CRMP1 e.g. is recruited to inclusion bodies with aggregated
huntingtin protein in brains of HD transgenic
mice and efficiently inhibits polyQ-mediated huntingtin
exon 1 aggregation in cell free assays. Our results
offer a new strategy for identifying perturbed, tissuespecific
human PPIs and modulators of protein misfolding
and aggregation (Bounab et al., 2009, submitted).
Development of interactome databases and
novel quality standards for systematic protein
interaction studies
Human protein interaction maps have become important
tools of biomedical research for the elucidation of
molecular mechanisms and the identification of new
modulators of disease processes. We developed a comprehensive
interactome database termed Unified
Human Interactome (UniHI). It provides researchers
with a comprehensive integrated platform to query and
access human PPI data. Since its first release, UniHI has
considerably increased in size. The latest update of
UniHI includes over 250,000 interactions between
~23,000 unique proteins collected from 14 major
sources. However, this wealth of data also poses new
challenges for researchers due to the size and complexity
of interaction networks retrieved from the database.
We therefore developed several new tools to query, analyze
and visualize human PPI networks. Most importantly,
UniHI now allows the construction of tissue-specific
interaction networks and focused searches of
canonical pathways. This will enable researchers to target
their analysis and to prioritize candidate proteins
for follow-up studies. UniHI 4 can be accessed at
http://www.mdc-berlin.de/unihi (Chaurasisa et al.,
2008).