Key result
Free energy simulations of ShK toxin binding to Kv1 channels yielded computed binding free energies in good agreement with experimental data, providing insights for developing selective analogues.
Free energy simulations of ShK toxin binding to Kv1 channels provide structural insights that may guide the development of selective analogues for autoimmune diseases.
May guide selective Kv1 blocker design for autoimmunity; hypothesis-generating and requires experimental validation before clinical consideration.
The voltage-gated potassium channel Kv1.3 is an attractive target for treatment of autoimmune diseases. ShK toxin from sea anemone is one of the most potent blockers of Kv1.3, and therefore ShK and its analogues have been proposed as therapeutic leads for such diseases. Increasing the selectivity of the proposed leads for Kv1.3 over other Kv1 channels is a major issue in this endeavor. Here we study binding of ShK toxin to Kv1 channels using free energy simulation methods. Homology models for Kv1.1 and Kv1.3 channels are constructed using the crystal structure of Kv1.2. The initial poses for the Kv1.x-ShK complexes are obtained using HADDOCK, which are then refined via molecular dynamics simulations. The binding mode in each complex is characterized by identifying the strongly interacting residues, which compare well with available mutagenesis studies. For each complex, the potential of mean force is calculated from umbrella sampling simulations, and the corresponding absolute binding free energy is determined. The computed binding free energies are in good agreement with the experimental data, which increases the confidence on the model complexes. The insights gained on Kv1.x-ShK binding modes will be valuable in the development of new ShK analogues with better selectivity properties.
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Rashid et al. (2012) studied Autoimmune diseases. ShK toxin was evaluated on Binding free energy of ShK toxin to Kv1 channels. Free energy simulations of ShK toxin binding to Kv1 channels yielded computed binding free energies in good agreement with experimental data, providing insights for developing selective analogues.
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