Proton transfer pathways in an aspartate-water cluster sampled by a network of discrete states

Proton transfer in the D-channel of cytochrome c oxidase modeled by a transition network approach

BACKGROUND

Determination of proton uptake pathways in Cytochrome c Oxidase is difficult due to the complexity of the system. The transition networks approach allows sampling of proton transfer pathways without predefined reaction coordinate.

METHODS

Computation of the proton transfer pathways in a model of the D-channel of cytochrome c oxidase has been performed by a transition network approach that combines discrete, optimisation based and molecular dynamics based sampling.

RESULTS

The optimal pathway involves an opening of the so-called asparagine gate, hydration of the asparagine region, the formation of a hydrogen-bonded chain, and finally concerted proton hole transport along this chain. The optimal pathway finds the protonation of residue H26 close to the channel entrance favourable for lowering the transition energies of subsequent steps, in particular, opening of the Asn gate and formation of a hydrogen-bonded chain. Residue Y33 plays an important role in shuttling the transferred proton hole.

CONCLUSIONS

The optimal pathway found by the transition network approach shows the same important characteristics as pathways determined earlier by other methods. The computed barrier and reaction energies are also in good agreement with previous studies. The transition network approach provides an alternative to explore pathways in complex systems.

GENERAL SIGNIFICANCE

The correct function of the enzyme as oxidase and proton pump depends on the interplay of several redox and proton transport steps. Understanding the proton transport mechanism is therefore key to understanding the protein's function. The complex nature of long- distances proton transfer through a protein requires a non-trivial simulation strategy.

Prediction of perturbed proton transfer networks

The transfer of protons through proton translocating channels is a complex process, for which direct samplings of different protonation states and side chain conformations in a transition network calculation provide an efficient, bias-free description. In principle, a new transition network calculation is required for every unsampled change in the system of interest, e.g. an unsampled protonation state change, which is associated with significant computational costs. Transition networks void of or including an unsampled change are termed unperturbed or perturbed, respectively. Here, we present a prediction method, which is based on an extensive coarse-graining of the underlying transition networks to speed up the calculations. It uses the minimum spanning tree and a corresponding sensitivity analysis of an unperturbed transition network as initial guess and refinement parameter for the determination of an unknown, perturbed transition network. Thereby, the minimum spanning tree defines a sub-network connecting all nodes without cycles and minimal edge weight sum, while the sensitivity analysis analyzes the stability of the minimum spanning tree towards individual edge weight reductions. Using the prediction method, we are able to reduce the calculation costs in a model system by up to 80%, while important network properties are maintained in most predictions.