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Voltage sensor domains (VSD) of voltage-dependent ion channels share a basic molecular structure with a voltage-sensing phosphatase and a voltage-gated proton channel. The VSD senses and responds to changes in the membrane potential by undergoing conformational changes associated with the movement of the charged arginines located on the S4 segment. Although several functional and structural studies have provided useful information about the conformational changes in many ion channels, a detailed and unambiguous explanation has not been published. Therefore, understanding the principle of voltage-dependent gating at an atomic level is required. In this study, we took advantage of the available spin labeling electron paramagnetic resonance spectrometry data and computational methods to investigate the structure and dynamic properties of the Up-state (activated) and Down-state (resting) conformations of the VSD by means of all-atom molecular dynamics (MD) simulations. The MD results of the Down conformation determined in bilayers with and without lipid phosphates both revealed a different shape of the aqueous crevice, in which more water molecules surround and fill the intracellular crevice in its Down state than in its Up state. The solvent accessible surface within the crevice has a complementary shape that can account for water-mediated interactions between the voltage sensor and the lipid bilayer. The results support the previously reported experimental data.

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Because of the rapid progress in biochemical and structural studies of membrane proteins, considerable attention has been given on developing efficient computational methods for solving low-to-medium resolution structures using sparse structural data. In this study, we demonstrate a novel algorithm, max-min ant system (MMAS), designed to find an assembly of α-helical transmembrane proteins using a rigid helix arrangement guided by distance constraints. The new algorithm generates a large variety with finite number of orientations of transmembrane helix bundle and finds the solution that is matched with the provided distance constraints based on the behavior of ants to search for the shortest possible path between their nest and the food source. To demonstrate the efficiency of the novel search algorithm, MMAS is applied to determine the transmembrane packing of KcsA and MscL ion channels from a limited distance information extracted from the crystal structures, and the packing of KvAP voltage sensor domain using a set of 10 experimentally determined constraints, and the results are compared with those of two popular used stochastic methods, simulated annealing Monte Carlo method and genetic algorithm.