A NOVEL PARADIGM FOR EFFECTIVE AND SAFER TREATMENT OF SCHIZOPHRENIA: BIASED (ANT)AGONISTS WITH A CHARACTERIZED POLYPHARMACOLOGICAL PROFILE
Abstract
Project aim: The treatment of schizophrenia remains an utmost challenge: Up to 30% of patients are resistant and up to an additional 30% respond only partially to antipsychotic treatment. Most of the patients that receive treatment suffer diverse side effects. The aim of this project is to elaborate a framework for improved medication. We will use a multidisciplinary approach grounded in novel concepts such as signaling bias and polypharmacology applied to antipsychotic drug targets. Specifically, we will tackle two main objectives: On one hand, we will interrogate the implication of specific signaling pathways in distinct symptoms of SZ. Ultimately, we will translate obtained insights into lead- and drug-like candidates with an improved therapeutic profile.
Work plan & exploitation of results: First research efforts will be dedicated to the detection of signaling probes that are specific to individual signaling pathways applying newest computer technology, simulation/screening algorithms and validation in living cells with BRET-based biosensors. Obtained signaling probes will be used to study in vivo the association of specific pathways to symptoms of SZ (positive, negative and cognitive deficits). From here, we will develop molecular candidates which act only on SZ-implicated pathways with a characterized polypharmacological profile. This will be the starting point for the development of antipsychotic drugs superior to current treatments in terms of efficacy and safety.
Keywords
schizophrenia, (epi)genetic approaches
Molecular modelling techniques
Behavioural methodologies
Pharmacology
Computational neurosciences
Animal studies, G protein coupled receptors, drug discovery, biased signaling, polypharmacology
Call topic
Mental Disorders
Proposed runtime
2019 - 2022
Project team
Jana Selent (Coordinator)
Spain (ISCIII)
Peter Kolb
Germany (BMBF)
Michel Bouvier
Canada (CIHR-INMHA)