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Molecular dynamics simulations of the CLC-2 ion channel
McKiernan, Keri A.2019This work reports a dynamical Markov state model of CLC-2 "fast" (pore) gating, based on 600 microseconds of molecular dynamics (MD) simulation. In the starting conformation of our CLC-2 model, both outer and inner channel gates are closed. The first conformational change in our dataset involves rotation of the inner-gate backbone along residues S168-G169-I170. This change is strikingly similar to that observed in the cryo-EM structure of the bovine CLC-K channel, though the volume of the intracellular (inner) region of the ion conduction pathway is further expanded in our model. From this state (inner gate open and outer gate closed), two additional states are observed, each involving a unique rotameric flip of the outer-gate residue GLUex. Both additional states involve conformational changes that orient GLUex away from the extracellular (outer) region of the ion conduction pathway. In the first additional state, the rotameric flip of GLUex results in an open, or near-open, channel pore. The equilibrium population of this state is low (about one percent), consistent with the low open probability of CLC-2 observed experimentally in the absence of a membrane potential stimulus (0 mV). In the second additional state, GLUex rotates to occlude the channel pore. This state, which has a low equilibrium population (about one percent), is only accessible when GLUex is protonated. Together, these pathways model the opening of both an inner and outer gate within the CLC-2 selectivity filter, as a function of GLUex protonation. Collectively, our findings are consistent with published experimental analyses of CLC-2 gating and provide a high-resolution structural model to guide future investigations.
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Improving and applying atomistic simulation to study biophysical conformational dynamics
McKiernan, Keri A.[Stanford, California] : [Stanford University], 2018.Models are tools used to interpret and draw conclusions from nature. Molecular dynamics (MD) simulation is a powerful technique for modeling complex atomistic systems such as biomolecules. In this dissertation, I discuss how one can improve and apply MD simulation in order to learn about biophysical phenomena. I first discuss how to improve the representation of the underlying physical interactions in a simulation. Chapter 2 discusses the optimization method, and 3 discusses how to rigorously characterize a resultant potential function. I then discuss how to use Markov state modeling to derive an interpretable mechanistic characterization of a simulation dataset. Chapters 4 and 5 apply this framework to study the conformational dynamics of the TREK-2 and CLC-2 ion channels, respectively. A brief introduction to the topics of MD simulation, force field optimization, and Markov state modeling is given in chapter 1. There remains a lot of work to be done before simulations are able to mimic reality with high fidelity. However, I am optimistic that with increasing data availability and improvements in optimization methodology, simulation will prove itself progressively more useful for studying dynamics at atomic resolution.
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