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Towards a Complete Quantitative Model of the FOF1 ATP Synthase

Periodic Reporting for period 1 - F-ATPase (Towards a Complete Quantitative Model of the FOF1 ATP Synthase)

Reporting period: 2016-03-01 to 2018-02-28

Adenosine triphosphate (ATP) is the energy-currency of cells. This small molecule “stores” energy in a form that is readily consumable by the majority of biomolecular machines. It is synthesized primarily by the mitochondrial F-ATPase, a protein complex. We sought to understand the kinetics and thermodynamics by which this machine operates by building a numerical model to explain the function of this biomotor. This knowledge is crucial to understanding cellular energy production.

We also studied an ATP-driven molecule that harnesses this energy to perform a task crucial to cell vitality. This protein (ABCE1, the sole member of the ATP Binding Cassette family E) utilizes energy from the hydrolysis of ATP and the release of its constituent parts. ABCE1 is responsible for turnover of the ribosomal machinery (which itself is the machinery that makes protein biomolecules).

Studying these molecules is crucial to understanding how energy is stored and used by cells, including in the human mitochondria. This also includes understanding the differences between human and bacterial forms of these cellular components—which may facilitate our ability to exploit these differences. Additionally, our study will help us better understand how biomolecular systems produce asymmetric responses from highly symmetric systems, which is vital to developing and designing future nano-systems that can use rotary motors or be fueled by ATP.
Our study of both systems began by building ground-up models of function using a minimal scheme of system function. These models were then used to make quantitative hypotheses about rate-limiting processes in the two systems. For the ABCE1, we aimed to model an experimentally observed ten-fold difference in its rate of function. This ten-fold difference was highly unusual: it appeared to occur asymmetrically in one of two highly symmetric domains of the system. From our initial model, we were able to identify seven hypotheses that potentially described this asymmetry.

The ABCE1 contains structural motifs similar to the F-ATPase, but it exhibits an irregular behaviour. This highly symmetric two-domain molecule has an asymmetric behaviour: mutations that inhibit ATP hydrolysis in the first domain cut the overall hydrolysis rate in half, while mutations inhibiting hydrolysis in the second domain lead to an ten-fold increase in the overall rate. We aimed to determine how these two domains worked together and independently to produce the observed difference in ABCE1 hydrolysis rates.

Our first hypothesis was that the energy required for the system to transition from its inactive to its active state was altered by the mutations in question. The major difference was that mutated ABCE1 domains were unable to release ATP (and thus unable to bind a new ATP molecule). We calculated the energy required for the system to transition in four systems: ATP bound to both domains, ATP bound only in the first domain, ATP bound only in the second domain, or in the absence of ATP. We found that ABCE1 was only meta-stable if both binding pockets contained ATP. This suggested that even if the mutations themselves altered the probability of obtaining the closed active state, ATP binding in both pockets was a prerequisite to activation.

We therefore tested whether the mutations themselves stabilized or destabilized bound ATP and found no significant difference. However, we did observe that ATPs bound in the two domains had drastically different kinetics. ATP bound to domain 1 was more dynamic than ATP bound to domain 2—the ligand sampled three meta-stable states.

This difference led us to consider a non-intuitive solution to the difference in ATP hydrolysis. Based on our minimal models of ABCE1 function, we could envision a scenario where the domains themselves had intrinsically different rates and that mutations were able to “short-circuit” (that is, completely bypass) several intermediates. In the case of domain 2, this would lead to bypassing what would otherwise be the slowest step, while the mutation in domain 1 would create a symmetrically related short circuit but would still encounter the putative slowest step.

To test this hypothesis we computed the energetic contributions to mutating key regions responsible for ATP binding. We observed that these mutations only resulted in energetic differences when they altered the ATP’s dynamics.

With this knowledge in hand, we then identified key individual components of the system that were thought to be responsible for the asymmetric ATP dynamics. We performed a further set of simulations where these components were perturbed, and this perturbation eliminated the asymmetry.

We worked to disseminate the results of our work through four conferences and an invited talk given at the University of Bristol. The conferences included the “Workshop on Computer Simulation and Theory of Macromolecules” at Hunfeld, Germany in both 2016 and 2017; the European Biophysical Societies Association held in Dresden, Germany; and the international Gordon Research Conference on Computational Chemistry held in Girona, Spain. Nicholas Leioatts also served as chair and organizer for the associated Gordon Research Seminar on Computational Chemistry, also held in Girona, Spain.
During this project we were able to design a comprehensive model of the ABCE1 and a tentative model of the F-ATPase. We produced an enormous dataset that led to the elimination of several hypotheses as defined in section two. By the end of the project we hope to have eliminated all alternative possibilities to show quantitatively how these biomotors harness and produce energy. This model is informed by all available experimental data and so far has been able to predict in broad terms how specific mutations alter the overall activity of the system. We expect that our further work until the end of this project will result in a highly predictive model, where expected outcomes can be linked to correlated perturbations of the system.
ABCE1 structure with binding domains highlighted. Inset shows ATP close up. Image made with pymol.