Project without external funding

Identifizierung therapeutischer Substanzen, die zielgerichtet kompartimentierte cAMP Signalnetzwerke in humanen Krankheiten ansprechen


Project Details
Project duration: 11/20062008


Abstract
Major diseases including cardiovascular and renal diseases, diabetes mellitus, obesity, diseases of the immune system, cancer and neurological disorders are caused or are associated with disturbances of compartmentalization cAMP signalling networks. Key players in cAMP signalling are adenylyl cyclases (AC) synthesizing cAMP, phosphodiesterases (PDE) hydrolysing it, and A-kinase anchoring proteins (AKAP) tethering protein kinase A (PKA), the principal effector of cAMP, to cellular compartments.
In a multidisciplinary approach based on postgenomic research, we will use established and novel cell lines to identify small "druggable" therapeutic molecules derived from small molecule libraries which i.) displace PKA, AKAPs and PDEs from their cognate intracellular location and ii.) disrupt protein-protein interactions involving ACs, PDEs, AKAPs and PKA in cellular disease models. The disease models represent cardiovascular diseases, nephrogenic diabetes insipidus (NDI), asthma, chronic obstructive pulmonary disease (COPD), AIDS, obesity, and schizophrenia. Screening of compound libraries will be performed in living cells and in vitro with purified components of the cAMP signalling system. We aim to identify the molecular targets of small molecules using established and to be developed tools and bioassays. Cell signature responses to challenges with small molecules will be defined in order to gain mechanistic insight into the effects on the disease phenotypes and to anticipate side effects of identified substances. The small molecules will be valuable tools to investigate compartmentalised cAMP signalling. Moreover, this approach may lead to alternative strategies for the treatment of diseases associated with altered cAMP signalling that are not addressed effectively by conventional pharmacotherapy.

Last updated on 2017-11-07 at 14:24