Computational Study of Binding of µ-Conotoxin GIIIA to Bacterial Sodium Channels NaVAb and NaVRh.

Structures of several voltage-gated sodium (NaV) channels from bacteria have been determined recently, but the same feat might not be achieved for the mammalian counterparts in the near future. Thus, at present, computational studies of the mammalian NaV channels have to be performed using homology models based on the bacterial crystal structures. A successful homology model for the mammalian NaV1.4 channel was recently constructed using the extensive mutation data for binding of µ-conotoxin GIIIA to NaV1.4, which was further validated through studies of binding of other µ-conotoxins and ion permeation. Understanding the similarities and differences between the bacterial and mammalian NaV channels is an important issue, and the NaV1.4-GIIIA system provides a good opportunity for such a comparison. To this end, we study the binding of GIIIA to the bacterial channels NaVAb and NaVRh. The complex structures are obtained using docking and molecular dynamics simulations, and the dissociation of GIIIA is studied through umbrella sampling simulations. The results are compared to those obtained from the NaV1.4-GIIIA system, and the differences in the binding modes arising from the changes in the selectivity filters are highlighted.

Why the Drosophila Shaker K+ channel is not a good model for ligand binding to voltage-gated Kv1 channels.

The Drosophila Shaker K(+) channel is the first cloned voltage-gated potassium channel and has, therefore, played an important role in structural and functional studies of those channels. While such a role is well justified for ion permeation, it is not clear whether this also extends to ligand binding. Despite the high degree of homology among Shaker and Kv1 channels, κ-conotoxin PVIIA (κ-PVIIA) binds to Shaker with high affinity but not to Kv1 channels. Here we address this issue by studying binding of κ-PVIIA to Shaker and Kv1 channels using molecular dynamics (MD) simulations. The structures of the channel-toxin complexes are constructed via docking and refinement with MD. The binding mode of each complex is characterized and compared to available mutagenesis data to validate the complex models. The potential of mean force for dissociation of the Shaker-κ-PVIIA complex is calculated from umbrella sampling MD simulations, and the corresponding binding free energy is determined, which provides further validation of the complex structure. Comparison of the Shaker and Kv1 complex models shows that a few mutations in the turret and extended regions are sufficient to abolish the observed sensitivity of Shaker to κ-PVIIA. This study demonstrates that Shaker is not always a good model for Kv1 channels for ligand binding. It also provides insights into the binding of the toxin to potassium channels that will be useful for improving affinity and selectivity properties of Kv1 channels.

Computational studies of marine toxins targeting ion channels.

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.

Dynamic behavior of gap junctions in each cardiac cycle: a novel view on the electrical coupling of normal cardiocytes.

Two main mechanisms have been suggested for the propagation of action potentials in cardiac muscle cells: (1) the free flow of local circuit current through gap junctions and (2) the effect of electrical field. Different evidences confirm each of two mechanisms. We think that gap junctions are not continuously open in a normal heart cycle; instead, they open and close intermittently. In other words, gap junction has a dynamic behavior in each cardiac cycle, managing different routes of propagation in the diverse moments of normal cycle. Gap junctions could be open in phases 0, 1, 3, 4 and close in phase 2 (plateau) of action potential. Whenever gap junction is open, conduction can be fulfilled rapidly by current flow and whenever it is closed, the electrical field will be the main route of propagation. When the prejunctional cell is in the peak of action potential(AP), gap junction is closed and the postjunctional cell should use the electrical field to be stimulated. Then, when the prejunctional cell comes to the end of AP, the gap junction opens and current will potentiate the rising phase of AP in the postjunctional cell. Moreover, this process causes accumulation of calcium in the postjunctional cell near phase 2. We believe that our hypothesis on the mechanism of cardiac action potential propagation may have exciting advantages. This novel view on gap junction dynamic behavior may be useful for better exploitation of drugs or designing new remedies in arrhythmias. We also hypothesize that in conditions as cardiac failure, in which cardiac contractility is diminished and increasing intracellular calcium concentration is needed, gap junction closing drugs may be effective. It is worth noting that future clinical studies are needed to validate these predictions.

Mechanism of Ion Permeation in Mammalian Voltage-Gated Sodium Channels.

Recent determination of the crystal structures of bacterial voltage-gated sodium (NaV) channels have raised hopes that modeling of the mammalian counterparts could soon be achieved. However, there are substantial differences between the pore domains of the bacterial and mammalian NaV channels, which necessitates careful validation of mammalian homology models constructed from the bacterial NaV structures. Such a validated homology model for the NaV1.4 channel was constructed recently using the extensive mutagenesis data available for binding of µ-conotoxins. Here we use this NaV1.4 model to study the ion permeation mechanism in mammalian NaV channels. Linking of the DEKA residues in the selectivity filter with residues in the neighboring domains is found to be important for keeping the permeation pathway open. Molecular dynamics simulations and potential of mean force calculations reveal that there is a binding site for a Na+ ion just inside the DEKA locus, and 1-2 Na+ ions can occupy the vestibule near the EEDD ring. These sites are separated by a low free energy barrier, suggesting that inward conduction occurs when a Na+ ion in the vestibule goes over the free energy barrier and pushes the Na+ ion in the filter to the intracellular cavity, consistent with the classical knock-on mechanism. The NaV1.4 model also provides a good description of the observed Na+/K+ selectivity.

Systematic study of binding of µ-conotoxins to the sodium channel NaV1.4.

Voltage-gated sodium channels (NaV) are fundamental components of the nervous system. Their dysfunction is implicated in a number of neurological disorders, such as chronic pain, making them potential targets for the treatment of such disorders. The prominence of the NaV channels in the nervous system has been exploited by venomous animals for preying purposes, which have developed toxins that can block the NaV channels, thereby disabling their function. Because of their potency, such toxins could provide drug leads for the treatment of neurological disorders associated with NaV channels. However, most toxins lack selectivity for a given target NaV channel, and improving their selectivity profile among the NaV1 isoforms is essential for their development as drug leads. Computational methods will be very useful in the solution of such design problems, provided accurate models of the protein-ligand complex can be constructed. Using docking and molecular dynamics simulations, we have recently constructed a model for the NaV1.4-µ-conotoxin-GIIIA complex and validated it with the ample mutational data available for this complex. Here, we use the validated NaV1.4 model in a systematic study of binding other µ-conotoxins (PIIIA, KIIIA and BuIIIB) to NaV1.4. The binding mode obtained for each complex is shown to be consistent with the available mutation data and binding constants. We compare the binding modes of PIIIA, KIIIA and BuIIIB to that of GIIIA and point out the similarities and differences among them. The detailed information about NaV1.4-µ-conotoxin interactions provided here will be useful in the design of new NaV channel blocking peptides.

Molecular dynamics study of binding of µ-conotoxin GIIIA to the voltage-gated sodium channel Na(v)1.4.

Homology models of mammalian voltage-gated sodium (NaV) channels based on the crystal structures of the bacterial counterparts are needed to interpret the functional data on sodium channels and understand how they operate. Such models would also be invaluable in structure-based design of therapeutics for diseases involving sodium channels such as chronic pain and heart diseases. Here we construct a homology model for the pore domain of the NaV1.4 channel and use the functional data for the binding of µ-conotoxin GIIIA to NaV1.4 to validate the model. The initial poses for the NaV1.4-GIIIA complex are obtained using the HADDOCK protein docking program, which are then refined in molecular dynamics simulations. The binding mode for the final complex is shown to be in broad agreement with the available mutagenesis data. The standard binding free energy, determined from the potential of mean force calculations, is also in good agreement with the experimental value. Because the pore domains of NaV1 channels are highly homologous, the model constructed for NaV1.4 will provide an excellent template for other NaV1 channels.