Abstract
Toxins from marine animals offer novel drug leads for treatment of diseases involving ion channels. Computational methods could be very helpful in this endeavour in several ways, e.g., (i) constructing accurate models of the channel-toxin complexes using docking and molecular dynamics (MD) simulations; (ii) determining the binding free energies of toxins from umbrella sampling MD simulations; (iii) predicting the effect of mutations from free energy MD simulations. Using these methods, one can design new analogs of toxins with improved affinity and selectivity properties. Here we present a review of the computational methods and discuss their applications to marine toxins targeting potassium and sodium channels. Detailed examples from the potassium channel toxins—ShK from sea anemone and κ-conotoxin PVIIA—are provided to demonstrate capabilities of the computational methods to give accurate descriptions of the channel-toxin complexes and the energetics of their binding. An example is also given from sodium channel toxins (µ-conotoxin GIIIA) to illustrate the differences between the toxin binding modes in potassium and sodium channels.
Highlights
Voltage-gated ion channels play key roles in electrical signalling in cells
As shown in the present work, the accuracy of the computational methods extends to description of channel-toxin complexes
Affinity and selectivity properties of a toxin for a given channel target can be improved by making rational choices for mutations from accurate complex models, and performing free energy calculations to find the free energy change associated with the mutation
Summary
Voltage-gated ion channels play key roles in electrical signalling in cells. They function much like transistors—A change in the membrane potential opens the channel gate and allows passive diffusion of a selected type of ions such as Na+ , K+ , or Ca2+ across the cell membrane [1]. Once a toxin is identified as a potential drug lead for a target ion channel, more work needs to be done to improve its affinity and selectivity for the target This is essential to reduce the dosage and avoid side effects that may arise from binding of the drug to unintended proteins. Provided the structures of the target proteins are available—either from X-ray diffraction or via homology modelling—one can alternatively use computational methods to construct accurate models for the channel-toxin complexes and predict the effect of the mutations in silico. Of particular importance for toxin binding studies was the solution of the mammalian voltage-gated potassium channel Kv1.2 [13], which has enabled construction of homology models for other Kv1 channels. We give an example from μ-conotoxin GIIIA to illustrate how the binding modes in sodium channels differ from those in potassium channels
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