Hello, A yearly allocation for the LCRC cluster has been requested with the following updated information: Submitter/PI: Benoit Roux Project Name: kv Division: BIO Project title: Studies of voltage-vgated potassium channel Associated funding: NIH/NIGMS, R01-GM062342 "Computational studies of ion channels" INCITE from Office of Science Other Systems: BG/P, NCSA, PSC, KBT Science: Molecular dynamics of membrane proteins that are affected by the transmembrane voltage Project description: Voltage-gated potassium (Kv) channels are membrane proteins that respond to changes in the transmembrane potential by altering their conformation to allow the passive conduction of K+ ions across the cell membrane. These channels are tetrameric proteins, in which each subunit comprises six transmembrane (TM) helical segments (S1-S6). The ion conduction pore is located at the center of the tetrameric structure and is formed by the S5 and S6 helices from the four subunits. The first four segments (S1-S4) in each subunit form a voltage-sensing domain (VSD) that is located in the lipid membrane at the periphery of the central pore domain (PD). Upon depolarization of the membrane, the VSD in each subunit undergoes a voltage-dependent transition from a resting to an active conformation, which then leads the opening of the intracellular gate of the ion conduction pore. The conformational changes associated with the activation of Kv channels result in the transfer of an electric charge Delta-Q across the membrane, that can be measured experimentally as a small transient capacitive current. In the Shaker K+ channel, the "gating charge" corresponds to the transfer of 12-14 elementary charge (e) along the transmembrane electric field. Correspondingly, a change V in the membrane potential shifts the relative free energy of the closed and open conformations by V*Delta-Q. The gating charge DeltaQ is, thus, a key concept to explain how channel activation is coupled to the membrane potential. Initially postulated by Hodgkin and Huxley in 1952, it was first detected and measured more than 20 years later by Armstrong and Bezanilla. Ultimately, explaining the voltage-gating mechanism of Kv channels in molecular terms requires gaining knowledge of the active and resting conformations, and then showing how those conformations are able to account for the experimentally observed gating charge Delta-Q. Our strategy is to first carefully construct atomic models of the active and resting states of Kv channels that are consistent with all available experimental information using protein structure prediction algorithms. We also have a novel method to compute the gating charge using all-atom MD. Recently, Pathak et al. have generated detailed atomic models of Kv1.2 in the open/active and closed/resting states using the Rosetta-Membrane structure prediction program. The model of the open/active state complements the information missing from the X-ray structure of the Kv1.2 channel used as a template, while the S1-S2, S2-S3, and S3-S4 loops in the voltage sensing domain were modeled de novo. These results offer a promising starting point to expand our understanding of voltage gating in Kv channels. Some critical issues must be addressed. In particular, the stability of those structural models in the complex dynamical environment of the lipid bilayer has not be ascertained. Furthermore, the gating charge associated with the models was only evaluated within a continuum approximation where the water and membrane were treated as featureless dielectric media. Recently, we have developed the string method with swarms of trajectories that is able to determine dynamically relevant transition pathways in complex macromolecular systems. The method, which was directly inspired from the work of Maragliano et al. (2006), aims to discover the optimal minimum free energy path between the two end-states represented as a "chain of state" by an ordered sequence of M discrete "images"", {z1,z2 ..., zM}. Briefly, the algorithm consists in evolving the chain of state towards optimal paths by making small adjustments Delta-z to the images. In the strategy developed by us, the Delta-z is calculated as the average drift for an ensemble (swarms) of unbiased short trajectories of length tau initiated from each of the images. The algorithm refine each of the M images until the "dynamical propagation" is such that each image evolves only along the path on average. The string method with swarms-of-trajectories is based on the reasonable assumption th at, on the timescale tau, the set of collective variables evolved as an overdamped Browninan dynamics guided by a free energy landscape. Nevertheless, we emphasize that the true dynamical evolution of the atomistic degrees of freedom of the real system undelies the method. Our goal is to refine the atomic models of the closed/resting and open/activated states and test their ability to account for the experimentally observed gating charge using all-atom MD and explicit lipid membrane environment. REFERENCES M. M. Pathak, V. Yarov-Yarovoy, G. Agarwal, B. Roux, P. Barth, S. Kohout, F. Tombola, and E. Y. Isacoff. (2007). "Closing in on the Resting State of the Shaker K+ Channel." Neuron 56, 124-140. F. V. Campos, B. Chanda, B. Roux, and F. Bezanilla. (2007). "Two Atomic Constraints Unambiguously Position the S4 Segment Relative to S1 and S2 Segments in the Closed State of Shaker K Channel." Proceedings of the National Academy of Sciences of the United States of America 104, 7904-7909. A. C. Pan, D. Sezer, and B. Roux. (2008). "Finding Transition Pathways Using the String Method with Swarms of Trajectories." J Phys Chem B 112, 3432-3440. B. Roux. (2008). "The Membrane Potential and Its Representation by a Constant Electric Field in Computer Simulations." Biophys J 95, 4205-4216. Project URL: http://thallium.bsd.uchicago.edu/RouxLab/ Current FY Hours Used: undetermined amount New FY Requested allocation: 250000 Justification: For the resources, we expect to be using MPI runs of 16-32 CPU over the next year. This easily amounts to: 32 CPU times 24 hours * 325 days = 250,000 Fusion will be an excellent platform to establish and execute the string method algorithm. Thank You, The LCRC Accounts System