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GOALS
GOALS
The main aim of this project consists in filling the gap between thermodynamic data and disease-related information on protein variants. We propose to integrate theoretical/computational approaches with experimental validations to assess the impact of amino acid variations on protein structure, function and protein-protein binding affinity. We will generate a comprehensive database collecting all the structural and functional protein variants associated to diseases, with specific reference to predicted or experimentally available thermodynamic data. Then, we will use those data to implement customized methods for predicting the impact of variants on proteins associated to cancer and to genetic diseases affecting calcium signalling. Our project represents an opportunity to bring together computational and experimental scientists for creating a consortium able at characterising the effect of genetic variants at protein level and their impact on human health.
COLLABORATORS
COLLABORATORS
The project involves several research units:
Unit 1: University of Torino (Leading Unit) - Piero Fariselli.
Unit 2: University of Bologna - Emidio Capriotti and Paola Turina.
Unit 3: University of Verona - Daniele Dell'Orco and Mariapina D'Onofrio.
Unit 4: University "La Sapienza" Roma - Roberta Chiaraluce and Valerio Consalvi.
Unit 5: National Institute for Nuclear Physics (INFN) - Gaetano Salina, Silvia Morante, Giovanni La Penna.
Our research unit will mostly focus on the characterisation of the structural effects of point mutations found in the genes encoding calmodulin (CaM), which are associated with catecholaminergic polymorphic ventricular tachycardia (CPVT) and long QT syndrome (LQTS). Both conditions eventually lead to cardiac arrest. We will also investigate whether the interaction with the cardiac cell-specific target Ryanodyne receptor 2 (RyR2) is perturbed by the point mutations in CaM, by assessing the thermodynamics and the kinetics of binding.
More information on this project can be found HERE.
FUNDING
FUNDING
This project is funded by:
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