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Probing the sequence determinants of ion channel voltage sensing via computation: towards the design of custom-tailored voltage-sensing modules (VOLTSENS)
Start date: May 1, 2013, End date: Apr 30, 2016 PROJECT  FINISHED 

Voltage sensing is a crucial property for a variety of proteins involved in many physiological functions (selective ion transport through membranes, enzymatic catalysis…). All these proteins achieve voltage sensing through the action of a 4 alpha-helix bundle module called the voltage-sensor domain (VSD). This transmembrane module achieves its function thanks to specific features, such as the presence of a large number of conserved charged or hydrophobic residues isolating the intracellular domain from the extracellular one. Despite these common features, nature achieves a surprising variability in terms of voltage-sensing properties, i.e., the thermodynamic and kinetic properties characterizing VSD activation span a wide range of values among the VSD superfamily. What are the residues responsible for such modulation and how this variability is achieved is not yet understood and is of great interest from a medical perspective, as it would shed light onto the effect ofdisease-involved mutation of crucial residues (channelopathies).This proposal offers to use the arsenal of computational methods derived from theoretical chemistry (molecular dynamics simulations using atomistic and polarizable force fields, free energy calculations, QM/MM calculations, force matching algorithms…) and bioinformatics (homology modeling, evolutionary modeling…) to unravel this question. The proposal unfolds in three steps: the first involves developing a robust framework to evaluate the thermodynamic and kinetic properties of activation of a specific VSD. The second consists in evaluating the impact of the mutation of specific residues on the parameters determined in step 1, while validating and refining the theoretical framework through comparison of these results to experimental ones from our collaborators. The final step consists in integrating this data in an evolutionary model including a variety of VSDs.
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