Coupling of quinone dynamics to proton pumping in respiratory complex I

Respiratory complex I (NADH:quinone oxidoreductase) plays a central role in generating the proton electrochemical gradient in mitochondrial and bacterial membranes, which is needed to generate ATP. Several high-resolution structures of complex I have been determined, revealing its intricate architecture and complementing the biochemical and biophysical studies. However, the molecular mechanism of long-range coupling between ubiquinone (Q) reduction and proton pumping is not known. Computer simulations have been applied to decipher the dynamics of Q molecule in the similar to 30 angstrom long Q tunnel. In this short report, we discuss the binding and dynamics of Q at computationally predicted Q binding sites, many of which are supported by structural data on complex I. We suggest that the binding of Q at these sites is coupled to proton pumping by means of conformational rearrangements in the conserved loops of core subunits.Peer reviewe

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

Proton transfer reactions are complex transitions due to the size and flexibility of the hydrogen-bonded networks along which the protons may “hop”. The combination of molecular dynamics based sampling of water positions and orientations with direct sampling of proton positions is an efficient way to capture the interplay of these degrees of freedom in a transition network. The energetically most favourable pathway in the proton transfer network computed for an aspartate-water cluster shows the pre-orientation of water molecules and aspartate side chains to be a pre-requisite for the subsequent concerted proton transfer to the product state

Protonation State-Dependent Communication in Cytochrome c Oxidase

Proton transfer in cytochrome c oxidase from the cellular inside to the binuclear redox center (BNC) can occur through two distinct pathways, the D- and K-channels. For the protein to function as both a redox enzyme and a proton pump, proton transfer into the protein toward the BNC or toward a proton loading site (and ultimately through the membrane) must be highly regulated. The PR → F transition is the first step in a catalytic cycle that requires proton transfer from the bulk at the N-side to the BNC. Molecular dynamics simulations of the PR → F intermediate of this transition, with 16 different combinations of protonation states of key residues in the D- and K-channel, show the impact of the K-channel on the D-channel to be protonation-state dependent. Strength as well as means of communication, correlations in positions, or communication along the hydrogen-bonded network depends on the protonation state of the K-channel residue K362. The conformational and hydrogen-bond dynamics of the D-channel residue N139 is regulated by an interplay of protonation in the D-channel and K362. N139 thus assumes a gating function by which proton passage through the D-channel toward E286 is likely facilitated for states with protonated K362 and unprotonated E286. In contrast, proton passage through the D-channel is hindered by N139’s preference for a closed conformation in situations with protonated E286

The H channel is not a proton transfer path in yeast cytochrome c oxidase

Cytochrome c oxidases (CcOs) in the respiratory chains of mitochondria and bacteria are primary consumers of molecular oxygen, converting it to water with the concomitant pumping of protons across the membrane to establish a proton electrochemical gradient. Despite a relatively well understood proton pumping mechanism of bacterial CcOs, the role of the H channel in mitochondrial forms of CcO remains debated. Here, we used site-directed mutagenesis to modify a central residue of the lower span of the H channel, Q413, in the genetically tractable yeast Saccharomyces cerevisiae. Exchange of Q413 to several different amino acids showed no effect on rates and efficiencies of respiratory cell growth, and redox potential measurements indicated minimal electrostatic interaction between the 413 locus and the nearest redox active component heme a. These findings clearly exclude a primary role of this section of the H channel in proton pumping in yeast CcO. In agreement with the experimental data, atomistic molecular dynamics simulations and continuum electrostatic calculations on wildtype and mutant yeast CcOs highlight potential bottlenecks in proton transfer through this route. Our data highlight the preference for neutral residues in the 413 locus, precluding sufficient hydration for formation of a proton conducting wire.Peer reviewe

Opioid receptor signaling, analgesic and side effects induced by a computationally designed pH-dependent agonist

Novel pain killers without adverse effects are urgently needed. Opioids induce central and intestinal side effects such as respiratory depression, sedation, addiction, and constipation. We have recently shown that a newly designed agonist with a reduced acid dissociation constant (pK(a)) abolished pain by selectively activating peripheral mu-opioid receptors (MOR) in inflamed (acidic) tissues without eliciting side effects. Here, we extended this concept in that pK(a) reduction to 7.22 was achieved by placing a fluorine atom at the ethylidene bridge in the parental molecule fentanyl. The new compound (FF3) showed pH-sensitive MOR affinity, [S-35]-GTP gamma S binding, and G protein dissociation by fluorescence resonance energy transfer. It produced injury-restricted analgesia in rat models of inflammatory, postoperative, abdominal, and neuropathic pain. At high dosages, FF3 induced sedation, motor disturbance, reward, constipation, and respiratory depression. These results support our hypothesis that a ligand's pK(a) should be close to the pH of injured tissue to obtain analgesia without side effects

Ontologies for Models and Algorithms in Applied Mathematics and Related Disciplines

In applied mathematics and related disciplines, the modeling-simulation-optimization workflow is a prominent scheme, with mathematical models and numerical algorithms playing a crucial role. For these types of mathematical research data, the Mathematical Research Data Initiative has developed, merged and implemented ontologies and knowledge graphs. This contributes to making mathematical research data FAIR by introducing semantic technology and documenting the mathematical foundations accordingly. Using the concrete example of microfracture analysis of porous media, it is shown how the knowledge of the underlying mathematical model and the corresponding numerical algorithms for its solution can be represented by the ontologies.Comment: Preprint of a Conference Paper to appear in the Proceeding of the 17th International Conference on Metadata and Semantics Researc

Research-Data Management Planning in the German Mathematical Community

In this paper we discuss the notion of research data for the field of mathematics and report on the status quo of research-data management and planning. A number of decentralized approaches are presented and compared to needs and challenges faced in three use cases from different mathematical subdisciplines. We highlight the importance of tailoring research-data management plans to mathematicians' research processes and discuss their usage all along the data life cycle

Optimale Bestimmung von Netzwerken für die Simulation von Protonen Transfer Prozessen

The oxidative phosphorylation is the most important step of the aerobic respiration. Here, electrons are transferred along several membrane-embedded enzyme complexes to finally reduce molecular oxygen to water in Cytochrome c Oxidase. The energy released by the electron flow and the oxygen reduction is used to translocate protons across the membrane. Thereby, an electro-chemical gradient is established which subsequently drives the synthesis of the biological energy carrier Adenosine Triphosphate. Numerous diseases, e.g. Alzheimer or Parkinson, are partially assigned to malfunctions of the oxidative phosphorylation, rendering a detailed understanding of this step indispensable. Common computational investigations, employing Molecular Dynamics simulations, enhanced sampling techniques, or transition pathway finding algorithms, are limited in their description of quantum effects and often only provide a limited, or biased, description of complex reactions. The alternative Transition Network approach, divides a complex reaction of interest into numerous simpler transitions, connecting various local potential energy minima of the potential energy surface by minimum energy pathways, yielding a Transition Network, or simple graph, which can be analyzed in terms of optimal transition pathways by standard graph theoretical algorithms. A major drawback of the Transition Network approach is the exponential increase of stationary points of the potential energy surface with increasing numbers of degrees of freedom to sample, rendering the Transition Network approach infeasible for most complex reactions. Within the framework of this thesis two methods optimizing the Transition Network approach are developed and extensively tested in small proton transfer model systems. These are: 1) the TN-MD method coupling the discrete sampling of states separated by substantial energy barriers with Molecular Dynamics simulations for the sampling of states separated by minor energy barriers, e.g. amino acid side chain dihedral angle rotations or water molecule translations, respectively, and 2) the TN prediction method using a known, initial Transition Network and an excessive two-step coarse-graining procedure for the determination of an unknown Transition Network in a perturbed environment, e.g. different protonation states. Both methods provide significant cost reductions, while important properties of the proton transfer reactions, e.g. rate-determining, maximal transition barriers and the variability of transition pathways or mechanisms, are maintained. Furthermore, the TN-MD method is used to investigate the proton transfer through the D-channel of Cytochrome c Oxidase in a minimal model system, providing various proton transfer pathways with rate-determining, maximal transition barriers which are in agreement to computational results from Liang et al using a much more involved model and simulation setup. Other decisive aspects of previous proton transfer investigations along the D-channel, e.g. the identity of the rate-determining, maximal transition state and the behavior of the proposed asparagine gate, are reproduced and extended. Overall, this thesis provides a methodical leap forward in terms of the Transition Network approach as well as another piece of analysis required for the understanding of the proton translocation along the oxidative phosphorylation

Replication Data for: Prediction of perturbed proton transfer networks

Replication Data for PLOS ONE article "Prediction of perturbed proton transfer networks". Documentation in several ReadMe files

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