Ryan L. Hayes

Magnesium fluctuations modulate RNA dynamics in the SAM-I riboswitch.

Experiments demonstrate that Mg(2+) is crucial for structure and function of RNA systems, yet the detailed molecular mechanism of Mg(2+) action on RNA is not well understood. We investigate the interplay between RNA and Mg(2+) at atomic resolution through ten 2-μs explicit solvent molecular dynamics simulations of the SAM-I riboswitch with varying ion concentrations. The structure, including three stemloops, is very stable on this time scale. Simulations reveal that outer-sphere coordinated Mg(2+) ions fluctuate on the same time scale as the RNA, and that their dynamics couple. Locally, Mg(2+) association affects RNA conformation through tertiary bridging interactions; globally, increasing Mg(2+) concentration slows RNA fluctuations. Outer-sphere Mg(2+) ions responsible for these effects account for 80% of Mg(2+) in our simulations. These ions are transiently bound to the RNA, maintaining interactions, but shuttled from site to site. Outer-sphere Mg(2+) are separated from the RNA by a single hydration shell, occupying a thin layer 3-5 Å from the RNA. Distribution functions reveal that outer-sphere Mg(2+) are positioned by electronegative atoms, hydration layers, and a preference for the major groove. Diffusion analysis suggests transient outer-sphere Mg(2+) dynamics are glassy. Since outer-sphere Mg(2+) ions account for most of the Mg(2+) in our simulations, these ions may change the paradigm of Mg(2+)-RNA interactions. Rather than a few inner-sphere ions anchoring the RNA structure surrounded by a continuum of diffuse ions, we observe a layer of outer-sphere coordinated Mg(2+) that is transiently bound but strongly coupled to the RNA.

SMOG 2: A Versatile Software Package for Generating Structure-Based Models

Molecular dynamics simulations with coarse-grained or simplified Hamiltonians have proven to be an effective means of capturing the functionally important long-time and large-length scale motions of proteins and RNAs. Originally developed in the context of protein folding, structure-based models (SBMs) have since been extended to probe a diverse range of biomolecular processes, spanning from protein and RNA folding to functional transitions in molecular machines. The hallmark feature of a structure-based model is that part, or all, of the potential energy function is defined by a known structure. Within this general class of models, there exist many possible variations in resolution and energetic composition. SMOG 2 is a downloadable software package that reads user-designated structural information and user-defined energy definitions, in order to produce the files necessary to use SBMs with high performance molecular dynamics packages: GROMACS and NAMD. SMOG 2 is bundled with XML-formatted template files that define commonly used SBMs, and it can process template files that are altered according to the needs of each user. This computational infrastructure also allows for experimental or bioinformatics-derived restraints or novel structural features to be included, e.g. novel ligands, prosthetic groups and post-translational/transcriptional modifications. The code and user guide can be downloaded at http://smog-server.org/smog2.

Reduced Model Captures Mg2+-RNA Interaction Free Energy of Riboswitches

The stability of RNA tertiary structures depends heavily on Mg(2+). The Mg(2+)-RNA interaction free energy that stabilizes an RNA structure can be computed experimentally through fluorescence-based assays that measure Γ2+, the number of excess Mg(2+) associated with an RNA molecule. Previous explicit-solvent simulations predict that the majority of excess Mg(2+) ions interact closely and strongly with the RNA, unlike monovalent ions such as K(+), suggesting that an explicit treatment of Mg(2+) is important for capturing RNA dynamics. Here we present a reduced model that accurately reproduces the thermodynamics of Mg(2+)-RNA interactions. This model is able to characterize long-timescale RNA dynamics coupled to Mg(2+) through the explicit representation of Mg(2+) ions. KCl is described by Debye-Hückel screening and a Manning condensation parameter, which represents condensed K(+) and models its competition with condensed Mg(2+). The model contains one fitted parameter, the number of condensed K(+) ions in the absence of Mg(2+). Values of Γ2+ computed from molecular dynamics simulations using the model show excellent agreement with both experimental data on the adenine riboswitch and previous explicit-solvent simulations of the SAM-I riboswitch. This agreement confirms the thermodynamic accuracy of the model via the direct relation of Γ2+ to the Mg(2+)-RNA interaction free energy, and provides further support for the predictions from explicit-solvent calculations. This reduced model will be useful for future studies of the interplay between Mg(2+) and RNA dynamics.

Intercellular Stress Reconstitution from Traction Force Data

Cells migrate collectively during development, wound healing, and cancer metastasis. Recently, a method has been developed to recover intercellular stress in monolayers from measured traction forces upon the substrate. To calculate stress maps in two dimensions, the cell sheet was assumed to behave like an elastic material, and it remains unclear to what extent this assumption is valid. In this study, we simulate our recently developed model for collective cell migration, and compute intercellular stress maps using the method employed in the experiments. We also compute these maps using a method that does not depend on the traction forces or material properties. The two independently obtained stress patterns agree well for the parameters we have probed and provide a verification of the validity of the experimental method.

A magnesium-induced triplex pre-organizes the SAM-II riboswitch

Our 13C- and 1H-chemical exchange saturation transfer (CEST) experiments previously revealed a dynamic exchange between partially closed and open conformations of the SAM-II riboswitch in the absence of ligand. Here, all-atom structure-based molecular simulations, with the electrostatic effects of Manning counter-ion condensation and explicit magnesium ions are employed to calculate the folding free energy landscape of the SAM-II riboswitch. We use this analysis to predict that magnesium ions remodel the landscape, shifting the equilibrium away from the extended, partially unfolded state towards a compact, pre-organized conformation that resembles the ligand-bound state. Our CEST and SAXS experiments, at different magnesium ion concentrations, quantitatively confirm our simulation results, demonstrating that magnesium ions induce collapse and pre-organization. Agreement between theory and experiment bolsters microscopic interpretation of our simulations, which shows that triplex formation between helix P2b and loop L1 is highly sensitive to magnesium and plays a key role in pre-organization. Pre-organization of the SAM-II riboswitch allows rapid detection of ligand with high selectivity, which is important for biological function.

Calculating Intercellular Stress in a Model of Collectively Moving Cells

Cells move together in groups during development, wound healing, and cancer metastasis. It remains unclear how collectively moving cells coordinate their motion. In addition to external chemoattractants and exchanging signaling molecules, cells may also respond to mechanical cues. We developed a model of collective cell migration under the assumption that cells align their motility force with the direction of their velocity. This simple mechanism leads to large scale velocity correlations, swirling motion in the bulk of monolayers, and finger-like protrusions at the edge [1]. In experimental studies, the inter- and intracellular stress in the monolayer has been calculated from measured traction forces between the cells and the substrate. Stress builds up successively towards the center of the tissue as the majority of the cells pull outwards [2]. While one dimensional stress profiles are based on a simple force balance, two dimensional stress maps require the additional assumption of an elastic tissue [3], and the validity of this assumption remains disputable. In our model simulations, both the forces on the substrate and the intercellular forces are accessible. We can therefore apply a second method to calculate the stress based on forces between cells. Stress patterns calculated with both methods agree, showing that recovery of the intercellular stress is indeed mostly independent of specific material properties.1. Basan, M., J. Elgeti, E. Hannezo, W.-J. Rappel and H. Levine. PNAS. 2013.2. Trepat, X., M. R. Wasserman, T. E. Angelini, E. Millet, D. A. Weitz, J. P. Butler and J. J. Fredberg. Nat. Phys. 2009.3. Tambe, D. T., C. Corey Hardin, T. E. Angelini, K. Rajendran, C. Y. Park, X. Serra-Picamal, E. H. Zhou, M. H. Zaman, J. P. Butler, D. A. Weitz, J. J. Fredberg and X. Trepat. Nat. Mater. 2011.