Potassium channels modulate various cellular functions through efficient and selective conduction of K+ions. The mechanism of ion conduction in potassium channels has recently emerged as a topic of debate. Crystal structures of potassium channels show four K+ions bound to adjacent binding sites in the selectivity filter, while chemical intuition and molecular modeling suggest that the direct ion contacts are unstable. Molecular dynamics (MD) simulations have been instrumental in the study of conduction and gating mechanisms of ion channels. Based on MD simulations, two hypotheses have been proposed, in which the four-ion configuration is an artifact due to either averaged structures or low temperature in crystallographic experiments. The two hypotheses have been supported or challenged by different experiments. Here, MD simulations with polarizable force fields validated byab initiocalculations were used to investigate the ion binding thermodynamics. Contrary to previous beliefs, the four-ion configuration was predicted to be thermodynamically stable after accounting for the complex electrostatic interactions and dielectric screening. Polarization plays a critical role in the thermodynamic stabilities. As a result, the ion conduction likely operates through a simple single-vacancy and water-free mechanism. The simulations explained crystal structures, ion binding experiments and recent controversial mutagenesis experiments. This work provides a clear view of the mechanism underlying the efficient ion conduction and demonstrates the importance of polarization in ion channel simulations.
We apply density functional theory (DFT) and the DFT+U technique to study the adsorption of transition metal porphine molecules on atomistically flat Au(111) surfaces. DFT calculations using the Perdew?Burke?Ernzerhof exchange correlation functional correctly predict the palladium porphine (PdP) low-spin ground state. PdP is found to adsorb preferentially on gold in a flat geometry, not in an edgewise geometry, in qualitative agreement with experiments on substituted porphyrins. It exhibits no covalent bonding to Au(111), and the binding energy is a small fraction of an electronvolt. The DFT+U technique, parametrized to B3LYP-predicted spin state ordering of the Mn d-electrons, is found to be crucial for reproducing the correct magnetic moment and geometry of the isolated manganese porphine (MnP) molecule. Adsorption of Mn(II)P on Au(111) substantially alters the Mn ion spin state. Its interaction with the gold substrate is stronger and more site-specific than that of PdP. The binding can be partially reversed by applying an electric potential, which leads to significant changes in the electronic and magnetic properties of adsorbed MnP and 0.1 {angstrom} changes in the Mn-nitrogen distances within the porphine macrocycle. We conjecture that this DFT+U approach may be a useful general method for modeling first-row transition metal ion complexes in a condensed-matter setting.
This LDRD project has involved the development and application of Sandia's massively parallel materials modeling software to several significant biophysical systems. They have been successful in applying the molecular dynamics code LAMMPS to modeling DNA, unstructured proteins, and lipid membranes. They have developed and applied a coupled transport-molecular theory code (Tramonto) to study ion channel proteins with gramicidin A as a prototype. they have used the Towhee configurational bias Monte-Carlo code to perform rigorous tests of biological force fields. they have also applied the MP-Sala reacting-diffusion code to model cellular systems. Electroporation of cell membranes has also been studied, and detailed quantum mechanical studies of ion solvation have been performed. In addition, new molecular theory algorithms have been developed (in FasTram) that may ultimately make protein solvation calculations feasible on workstations. Finally, they have begun implementation of a combined molecular theory and configurational bias Monte-Carlo code. They note that this LDRD has provided a basis for several new internal (e.g. several new LDRD) and external (e.g. 4 NIH proposals and a DOE/Genomes to Life) proposals.