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Structure-guided simulations illuminate the mechanism of ATP transport through VDAC1

Nature Structural & Molecular Biology volume 21, pages 626–632 (2014)Cite this article

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Abstract

The voltage-dependent anion channel (VDAC) mediates the flow of metabolites and ions across the outer mitochondrial membrane of all eukaryotic cells. The open channel passes millions of ATP molecules per second, whereas the closed state exhibits no detectable ATP flux. High-resolution structures of VDAC1 revealed a 19-stranded β-barrel with an α-helix partially occupying the central pore. To understand ATP permeation through VDAC, we solved the crystal structure of mouse VDAC1 (mVDAC1) in the presence of ATP, revealing a low-affinity binding site. Guided by these coordinates, we initiated hundreds of molecular dynamics simulations to construct a Markov state model of ATP permeation. These simulations indicate that ATP flows through VDAC through multiple pathways, in agreement with our structural data and experimentally determined physiological rates.

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Figure 1: Cartoon representations of the refined mVDAC1 in complex with ATP.
Figure 2: Simulated current-voltage curves and ion-permeation rates for mVDAC1.
Figure 3: ATP adopts many conformations in the mVDAC1 pore.
Figure 4: Comparison between experimental ATP structure and MSM configurations.
Figure 5: A high ATP flux is achieved through multiple distinct pathways.
Figure 6: ATP permeates via a network of basic residues.

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Acknowledgements

This work was supported by US National Science Foundation CAREER award MCB0845286 (M.G.) and US National Institutes of Health grants GM089740 (M.G.), T32-DK061296 (J.L.A.) and GM078844 (J.A.). O.P.C. was supported by an Andrew Mellon Predoctoral Fellowship from the University of Pittsburgh. J.-P.C. was supported by a Young International Fellowship from the Chinese Academy of Sciences. Simulations at the Texas Advanced Supercomputing Center were supported by grant MCB080011 (M.G.). The Anton special-purpose supercomputer was provided by the National Resource for Biomedical Supercomputing, the Pittsburgh Supercomputing Center and the Biomedical Technology Research Center for Multiscale Modeling of Biological Systems through grant P41GM103712-S1 from the US National Institutes of Health, and simulations on Anton were supported by grant PSCA00015P (M.G.). The Anton machine was generously made available by D.E. Shaw Research. We thank J.M. Rosenberg, K. Callenberg, F.V. Marcoline, Y. Sheng, H.Y. Wang and A. Vartanian for helpful discussions and R. Ujwal for contributions at the early stages of this work. We dedicate this work to the memory of Armand Vartanian, a colleague and friend.

Author information

Author notes

  1. Om P Choudhary, Aviv Paz, Joshua L Adelman and Jacques-Philippe Colletier: These authors contributed equally to this work.

Authors and Affiliations

  1. Joint Carnegie Mellon University–University of Pittsburgh PhD Program in Computational Biology, Pittsburgh, Pennsylvania, USA

    Om P Choudhary

  2. Department of Physiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA

    Aviv Paz & Jeff Abramson

  3. Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, USA

    Joshua L Adelman & Michael Grabe

  4. Université Grenoble Alpes, Institut de Biologie Structurale, Grenoble, France

    Jacques-Philippe Colletier

  5. Centre National de la Recherche Scientifique, Institut de Biologie Structurale, Grenoble, France

    Jacques-Philippe Colletier

  6. Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Direction des Sciences du Vivant, Institut de Biologie Structurale, Grenoble, France

    Jacques-Philippe Colletier

  7. Institute for Stem Cell Biology and Regenerative Medicine, National Centre for Biological Sciences–Tata Institute of Fundamental Research, Bangalore, India

    Jeff Abramson

  8. Department of Pharmaceutical Chemistry, Cardiovascular Research Institute, University of California, San Francisco, San Francisco, California, USA

    Michael Grabe

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  1. Om P Choudhary
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Contributions

A.P., J.-P.C. and J.A. collected and analyzed the diffraction data. O.P.C., J.L.A. and M.G. designed, conducted and analyzed the MD simulations. The manuscript was prepared by all authors.

Corresponding authors

Correspondence to Jeff Abramson or Michael Grabe.

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Integrated supplementary information

Supplementary Figure 1 Electron density maps of the mVDAC1–ATP complex.

(a) A FoATP-FoNative difference Fourier map calculated between mVDAC1 ATP co-crystal and an apo crystal contoured at 3.1 σ displayed on the refined complex coordinates. (b) A solvent annealed omit map for the ATP molecule contoured at 3.3 σ. (c) A 2Fo-Fc electron density map of the refined model contoured at 1 σ. Color scheme is the same as in Fig. 1 of the main text. See Supporting Online Material for details.

Supplementary Figure 2 ATP fails to permeate mVDAC1 on the microsecond timescale.

(a,c) The z-position of the COM of the triphosphate tail and adenine ring are plotted versus time for two simulations run with either a 0 or 50 mV electric field. The channel was centered at z = 0 and aligned along the z-axis. (b,d) The same trajectories, projected onto the x-y plane. For the simulation performed with a 50 mV field, the ATP was initiated in the upper bath; the simulation at 0 mV was initiated in the pore. Despite their different initial positions within the simulation box and applied voltage, the ATP in both simulations bind to the N-terminal helix and sample a similar set of conformations. The phosphate tail remains largely immobile over the full length of the simulation, whereas the adenine ring interacts with a number of moieties within the channel.

Supplementary Figure 3 Implied timescales for the MSM.

The 50 slowest implied timescales are plotted on a log scale for a range of lag times, τ. Implied timescales were computed using Eq. 7, and the transition probability matrix obtained from the full 40 μs dataset coupled to the continuum bath as described in Supplementary Note. The lag time chosen for all analysis in the main text was 5 ns, since the timescales plateau at this point indicating that the model is Markovian.

Supplementary Figure 4 Initial placement and ATP coverage of the channel for the MSM construction.

(a) Blue spheres represent the β-phosphate atom of all 453 ATP configurations used to initiate MD simulations. The mVDAC1 channel is represented with the β-barrel in cyan and the N-terminal helix in red. The majority of simulations start with ATP in the pore domain. Membrane boundaries are indicated by black bars, but lipid and water are not shown for clarity. (b) Blue dots represent the β-phosphate of ATP plotted every 20 ps from all MD simulations initiated in panel a. The aggregate simulation time was 40 μs, and there are 10,000,000 ATP configurations represented. The densest regions are in the channel around the helix indicating that configurations in the pore domain were highly sampled. (c) Extent of ATP motion during each individual simulation. The starting z position (blue dot) and range of motion (green bar) of the COM of the ATP for each of the 453 MD simulations. The ATP undergoes 10–20 Å movements in many simulations, but never crosses the entire channel.

Supplementary Figure 5 States in the MSM are well equilibrated.

Each state in the MSM was separately analyzed for internal barriers. To do this, all configurations in each state were isolated and clustered into two substates using the k-centers k-mediods algorithm. The transition probability matrix at a 5 ns lag time was constructed, and the second eigenvalue was used to identify the relaxation time between the substates according to Eq. 7. Of the 210 states in the full MSM, 187 states (89%) relaxed faster than the 5 ns lag time used to construct the full MSM (blue circles), while 23 states (11%) relaxed much slower or failed to relax at all (red circles). Dropping these later states from the MFPT analysis had little effect on the results (data not shown).

Supplementary Figure 6 Error analysis of MFPT calculations.

(a,c) Distributions of the MFPT of ATP permeation from the cytoplasm to the IMS, and IMS to the cytoplasm, respectively, were calculated from 1000 bootstrap samples of the simulation trajectory set. (b,d) The sorted MFPTs calculated from each bootstrap sample. The mean MFPT of the distributions in a and c are indicated by a black horizontal line, while the bounds of the 95% confidence intervals are shown as dashed lines. Varying the cluster radii and lag time used to generate the MSM illustrates the sensitivity of the model to these parameters. (e) MFPTs as a function of cluster radius size for the original data set of trajectories calculated at a fixed lag time of 5 ns. (f) MFPTs as a function of lag time for the original data set of trajectories calculated at a fixed cluster radius size of 6.5 Å.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–6, Supplementary Table 1 and Supplementary Note (PDF 3745 kb)

Animation of the longest 4.8-μs simulation from Anton in the absence of a membrane potential.

ATP entered the channel and contacted the N-terminal α-helix during equilibration. The phosphate tail remained in contact with basic residues on the N-terminal helix except for the first few frames. The adenosine ring aggressively explored different regions of the channel including residues on the barrel wall opposite the helix. This simulation corresponds to data in Supplementary Fig. 2a,b. The left panel is the cytoplasmic view, while the right view is from the membrane. The right panel is oriented with the IMS at the bottom and the cytoplasm at the top. This orientation is used for Supplementary Movies 2, 3, 4, 5. Strands were clipped from the channel in the right panel to reveal the ATP. Mg2+ is the gold sphere adjacent to the phosphate tail. The coloring scheme for all movies is the same as images in the main text. Water and lipids were removed for clarity. (MPG 8630 kb)

Rate-limiting step along the highest-probability permeation pathway, path 1.

The rate limiting step along paths 1–4 is ATP detachment from the helix. For path 1, the phosphate tail initially interacted with just Arg15 on the helix, followed by temporary interactions with Arg15 and Arg218 on the barrel wall near the cytoplasmic mouth of the channel. Next, the interaction with Arg15 was broken, and ATP moved toward the cytosol. Supplementary Movies 2, 3, 4, 5 are continuous, representative simulations selected from the 453 simulations used for MSM construction. The frames in Supplementary Movies 2, 3, 4, 5 are spaced 200 ps apart. (MPG 5550 kb)

Rate-limiting step along paths 2–4.

ATP dissociated from the N-terminal α-helix and moved to residues Lys113 and Lys115 on the β-barrel wall. At the beginning of this movie, the phosphate tail was more closely associated with Arg15 on the helix, but it gradually broke this connection and fully interacted with Lys113 and Lys115. At this point, ATP is stretched across the pore because the adenosine ring continues to interact with the N-terminal helix. Finally, the ring broke free, and ATP moved to the barrel wall. (MPG 5537 kb)

ATP entry to the channel from the IMS.

ATP passed to Lys12 and Lys20 on the N-terminal α-helix via Lys174 on the β-barrel wall. This entry mechanism is common for paths 1–4. (MPG 6125 kb)

ATP exit to the cytosol along path 4.

ATP exited the channel along path 4 by breaking its interaction with Lys109 and diffusing into the cytoplasm. (MPG 3641 kb)

Permeation of ATP through mVDAC1 (path 1).

A complete depiction of permeation along the highest flux pathway, path 1. ATP was sequentially moved through a series of states 1, 2, 3,... N determined from the TPT analysis. Each state was defined by its generator, and the configurations from generator i to i+1 were constructed as follows. The RMSD of all snapshots in states i and i+1 were calculated with respect to the generator of state i+1. Next, we removed all snapshots that had a COM with a z-position less the z value for generator i or greater than z-position of generator i+1. We sorted the remaining snapshots in decreasing RMSD, with initial configurations closest to i and final configurations closest to i+1. This was repeated for all transitions from state 1 to state N. For capture from the IMS, we identified a single trajectory starting in bulk solution that arrived at state 1, and likewise for release to the cytoplasm, we identified a continuous trajectory starting in state N that released to the cytoplasm. The full set of ordered snapshots were then averaged in 200 ps blocks to make the final movie. ATP entered the channel from the IMS through interactions with the N-terminal methionine and Lys174 on the barrel wall. ATP subsequently moved to the center of the N-terminal helix and made contact with several basic residues. After dissociating from the helix, ATP interacted with Arg218 before exiting to the cytosol. (MPG 14026 kb)

Permeation of ATP through mVDAC1 (path 2).

A complete ATP permeation event along a flux pathway from the path 2 class of transitions. The method of movie construction is identical to the method described for Supplementary Movie 6. Initially, ATP transitioned from interacting with residue Lys174 and the N-terminal methionine to the basic residues on the N-terminal helix. The ATP then moved across the channel, where it interacted with residues Lys113 and Lys115 before transitioning to Lys161 and Arg163 at the outer mouth of the channel. Finally, ATP was released and entered the cytosol. (MPG 16317 kb)

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Choudhary, O., Paz, A., Adelman, J. et al. Structure-guided simulations illuminate the mechanism of ATP transport through VDAC1. Nat Struct Mol Biol 21, 626–632 (2014). https://doi.org/10.1038/nsmb.2841

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