Cavity hydration dynamics in cytochrome c oxidase and functional implications

Tutorial on how to build non-Markovian dynamic models from molecular dynamics simulations for studying protein conformational changes

Protein conformational changes play crucial roles in their biological functions. In recent years, the Markov State Model (MSM) constructed from extensive Molecular Dynamics (MD) simulations has emerged as a powerful tool for modeling complex protein conformational changes. In MSMs, dynamics are modeled as a sequence of Markovian transitions among metastable conformational states at discrete time intervals (called lag time). A major challenge for MSMs is that the lag time must be long enough to allow transitions among states to become memoryless (or Markovian). However, this lag time is constrained by the length of individual MD simulations available to track these transitions. To address this challenge, we have recently developed Generalized Master Equation (GME)-based approaches, encoding non-Markovian dynamics using a time-dependent memory kernel. In this Tutorial, we introduce the theory behind two recently developed GME-based non-Markovian dynamic models: the quasi-Markov State Model (qMSM) and the Integrative Generalized Master Equation (IGME). We subsequently outline the procedures for constructing these models and provide a step-by-step tutorial on applying qMSM and IGME to study two peptide systems: alanine dipeptide and villin headpiece. This Tutorial is available at https://github.com/xuhuihuang/GME_tutorials. The protocols detailed in this Tutorial aim to be accessible for non-experts interested in studying the biomolecular dynamics using these non-Markovian dynamic models.

Efficient Sampling of Cavity Hydration in Proteins with Nonequilibrium Grand Canonical Monte Carlo and Polarizable Force Fields

Prediction of the hydration levels of protein cavities and active sites is important to both mechanistic analysis and ligand design. Due to the unique microscopic environment of these buried water molecules, a polarizable model is expected to be crucial for an accurate treatment of protein internal hydration in simulations. Here we adapt a nonequilibrium candidate Monte Carlo approach for conducting grand canonical Monte Carlo simulations with the Drude polarizable force field. The GPU implementation enables the efficient sampling of internal cavity hydration levels in biomolecular systems. We also develop an enhanced sampling approach referred to as B-walking, which satisfies detailed balance and readily combines with grand canonical integration to efficiently calculate quantitative binding free energies of water to protein cavities. Applications of these developments are illustrated in a solvent box and the polar ligand binding site in trypsin. Our simulation results show that including electronic polarization leads to a modest but clear improvement in the description of water position and occupancy compared to the crystal structure. The B-walking approach enhances the range of water sampling in different chemical potential windows and thus improves the accuracy of water binding free energy calculations.

The catalytic reaction of cytochrome c oxidase probed by in situ gas titrations and FTIR difference spectroscopy

Cytochrome c oxidase (CcO) is a transmembrane heme‑copper metalloenzyme that catalyzes the reduction of O2 to H2O at the reducing end of the respiratory electron transport chain. To understand this reaction, we followed the conversion of CcO from Rhodobacter sphaeroides between several active-ready and carbon monoxide-inhibited states via attenuated total reflection Fourier-transform infrared (ATR FTIR) difference spectroscopy. Utilizing a novel gas titration setup, we prepared the mixed-valence, CO-inhibited R2CO state as well as the fully-reduced R4 and R4CO states and induced the "active ready" oxidized state OH. These experiments are performed in the dark yielding FTIR difference spectra exclusively triggered by exposure to O2, the natural substrate of CcO. Our data demonstrate that the presence of CO at heme a3 does not impair the catalytic oxidation of CcO when the cycle starts from the fully-reduced states. Interestingly, when starting from the R2CO state, the release of the CO ligand upon purging with inert gas yield a product that is indistinguishable from photolysis-induced states. The observed changes at heme a3 in the catalytic binuclear center (BNC) result from the loss of CO and are unrelated to electronic excitation upon illumination. Based on our experiments, we re-evaluate the assignment of marker bands that appear in time-resolved photolysis and perfusion-induced experiments on CcO.

Integrative generalized master equation: A method to study long-timescale biomolecular dynamics via the integrals of memory kernels

The generalized master equation (GME) provides a powerful approach to study biomolecular dynamics via non-Markovian dynamic models built from molecular dynamics (MD) simulations. Previously, we have implemented the GME, namely the quasi Markov State Model (qMSM), where we explicitly calculate the memory kernel and propagate dynamics using a discretized GME. qMSM can be constructed with much shorter MD trajectories than the MSM. However, since qMSM needs to explicitly compute the time-dependent memory kernels, it is heavily affected by the numerical fluctuations of simulation data when applied to study biomolecular conformational changes. This can lead to numerical instability of predicted long-time dynamics, greatly limiting the applicability of qMSM in complicated biomolecules. We present a new method, the Integrative GME (IGME), in which we analytically solve the GME under the condition when the memory kernels have decayed to zero. Our IGME overcomes the challenges of the qMSM by using the time integrations of memory kernels, thereby avoiding the numerical instability caused by explicit computation of time-dependent memory kernels. Using our solutions of the GME, we have developed a new approach to compute long-time dynamics based on MD simulations in a numerically stable, accurate and efficient way. To demonstrate its effectiveness, we have applied the IGME in three biomolecules: the alanine dipeptide, FIP35 WW-domain, and Taq RNA polymerase. In each system, the IGME achieves significantly smaller fluctuations for both memory kernels and long-time dynamics compared to the qMSM. We anticipate that the IGME can be widely applied to investigate biomolecular conformational changes.

An Efficient Path Classification Algorithm Based on Variational Autoencoder to Identify Metastable Path Channels for Complex Conformational Changes

Conformational changes (i.e., dynamic transitions between pairs of conformational states) play important roles in many chemical and biological processes. Constructing the Markov state model (MSM) from extensive molecular dynamics (MD) simulations is an effective approach to dissect the mechanism of conformational changes. When combined with transition path theory (TPT), MSM can be applied to elucidate the ensemble of kinetic pathways connecting pairs of conformational states. However, the application of TPT to analyze complex conformational changes often results in a vast number of kinetic pathways with comparable fluxes. This obstacle is particularly pronounced in heterogeneous self-assembly and aggregation processes. The large number of kinetic pathways makes it challenging to comprehend the molecular mechanisms underlying conformational changes of interest. To address this challenge, we have developed a path classification algorithm named latent-space path clustering (LPC) that efficiently lumps parallel kinetic pathways into distinct metastable path channels, making them easier to comprehend. In our algorithm, MD conformations are first projected onto a low-dimensional space containing a small set of collective variables (CVs) by time-structure-based independent component analysis (tICA) with kinetic mapping. Then, MSM and TPT are constructed to obtain the ensemble of pathways, and a deep learning architecture named the variational autoencoder (VAE) is used to learn the spatial distributions of kinetic pathways in the continuous CV space. Based on the trained VAE model, the TPT-generated ensemble of kinetic pathways can be embedded into a latent space, where the classification becomes clear. We show that LPC can efficiently and accurately identify the metastable path channels in three systems: a 2D potential, the aggregation of two hydrophobic particles in water, and the folding of the Fip35 WW domain. Using the 2D potential, we further demonstrate that our LPC algorithm outperforms the previous path-lumping algorithms by making substantially fewer incorrect assignments of individual pathways to four path channels. We expect that LPC can be widely applied to identify the dominant kinetic pathways underlying complex conformational changes.

Hybrid Quantum Mechanical/Molecular Mechanical Methods For Studying Energy Transduction in Biomolecular Machines

Hybrid quantum mechanical/molecular mechanical (QM/MM) methods have become indispensable tools for the study of biomolecules. In this article, we briefly review the basic methodological details of QM/MM approaches and discuss their applications to various energy transduction problems in biomolecular machines, such as long-range proton transports, fast electron transfers, and mechanochemical coupling. We highlight the particular importance for these applications of balancing computational efficiency and accuracy. Using several recent examples, we illustrate the value and limitations of QM/MM methodologies for both ground and excited states, as well as strategies for calibrating them in specific applications. We conclude with brief comments on several areas that can benefit from further efforts to make QM/MM analyses more quantitative and applicable to increasingly complex biological problems.

Memory Unlocks the Future of Biomolecular Dynamics: Transformative Tools to Uncover Physical Insights Accurately and Efficiently

Conformational changes underpin function and encode complex biomolecular mechanisms. Gaining atomic-level detail of how such changes occur has the potential to reveal these mechanisms and is of critical importance in identifying drug targets, facilitating rational drug design, and enabling bioengineering applications. While the past two decades have brought Markov state model techniques to the point where practitioners can regularly use them to glimpse the long-time dynamics of slow conformations in complex systems, many systems are still beyond their reach. In this Perspective, we discuss how including memory (i.e., non-Markovian effects) can reduce the computational cost to predict the long-time dynamics in these complex systems by orders of magnitude and with greater accuracy and resolution than state-of-the-art Markov state models. We illustrate how memory lies at the heart of successful and promising techniques, ranging from the Fokker-Planck and generalized Langevin equations to deep-learning recurrent neural networks and generalized master equations. We delineate how these techniques work, identify insights that they can offer in biomolecular systems, and discuss their advantages and disadvantages in practical settings. We show how generalized master equations can enable the investigation of, for example, the gate-opening process in RNA polymerase II and demonstrate how our recent advances tame the deleterious influence of statistical underconvergence of the molecular dynamics simulations used to parameterize these techniques. This represents a significant leap forward that will enable our memory-based techniques to interrogate systems that are currently beyond the reach of even the best Markov state models. We conclude by discussing some current challenges and future prospects for how exploiting memory will open the door to many exciting opportunities.

Predictive Molecular Models for Charged Materials Systems: From Energy Materials to Biomacromolecules

Electrostatic interactions play a dominant role in charged materials systems. Understanding the complex correlation between macroscopic properties with microscopic structures is of critical importance to develop rational design strategies for advanced materials. But the complexity of this challenging task is augmented by interfaces present in the charged materials systems, such as electrode-electrolyte interfaces or biological membranes. Over the last decades, predictive molecular simulations that are founded in fundamental physics and optimized for charged interfacial systems have proven their value in providing molecular understanding of physicochemical properties and functional mechanisms for diverse materials. Novel design strategies utilizing predictive models have been suggested as promising route for the rational design of materials with tailored properties. Here, an overview of recent advances in the understanding of charged interfacial systems aided by predictive molecular simulations is presented. Focusing on three types of charged interfaces found in energy materials and biomacromolecules, how the molecular models characterize ion structure, charge transport, morphology relation to the environment, and the thermodynamics/kinetics of molecular binding at the interfaces is discussed. The critical analysis brings two prominent field of energy materials and biological science under common perspective, to stimulate crossover in both research field that have been largely separated.

Interplay of Hydration and Protonation Dynamics in the K-Channel of Cytochrome c Oxidase

Cytochrome c oxidase is a membrane protein of the respiratory chain that consumes protons and molecular oxygen to produce water and uses the resulting energy to pump protons across the membrane. Our molecular dynamics simulations with an excess proton located at different positions in one of the proton-conducting channels, the K-channel, show a clear dependence of the number of water molecules inside the channel on the proton position. A higher hydration level facilitates the formation of hydrogen-bonded chains along which proton transfer can occur. However, a sufficiently high hydration level for such proton transport is observed only when the excess proton is located above S365, i.e., the lower third of the channel. From the channel entrance up to this point, proton transport is via water molecules as proton carriers. These hydronium ions move with their surrounding water molecules, up to K362, filling and widening the channel. The conformation of K362 depends on its own protonation state and on the hydration level, suggesting its role to be proton transport from a hydronium ion at the height of K362 to the upper part of the channel via a conformational change. The protonation-dependent conformational dynamics of E101 at the bottom of the channel renders proton transfer via E101 unlikely. Instead, its role is rather that of an amplifier of H96’s proton affinity, suggesting H96 as the initial proton acceptor.

Electronic Polarization Is Essential for the Stabilization and Dynamics of Buried Ion Pairs in Staphylococcal Nuclease Mutants

Buried charged residues play important roles in the modulation of protein stabilities and conformational dynamics and make crucial contributions to protein functions. Considering the generally nonpolar nature of protein interior, a key question concerns the contribution of electronic polarization to the stabilization and properties of buried charges. We answer this question by conducting free energy simulations using the latest polarizable CHARMM force field based on Drude oscillators for a series of Staphylococcal nuclease mutants that involve a buried Glu-Lys pair in different titration states and orientations. While a nonpolarizable model suggests that the ionized form of the buried Glu-Lys pair is more than 40 kcal/mol less stable than the charge-neutral form, the two titration states are comparable in stability when electronic polarization is included explicitly, a result better reconcilable with available experimental data. Analysis of free energy components suggests that additional stabilization of the ionized Glu-Lys pair has contributions from both the enhanced salt-bridge strength and stronger interaction between the ion-pair and surrounding protein residues and penetrated water. Despite the stronger direct interaction between Glu and Lys, the ion-pair exhibits considerably larger and faster structural fluctuations when polarization is included, due to compensation of interactions in the cavity. Collectively, observations from this work provide compelling evidence that electronic polarization is essential to the stability, hydration, dynamics, and therefore function of buried charges in proteins. Therefore, our study advocates for the explicit consideration of electronic polarization for mechanistic and engineering studies that implicate buried charged residues, such as enzymes and ion transporters.

O to bR transition in bacteriorhodopsin occurs through a proton hole mechanism

Extensive classical and quantum mechanical/molecular mechanical (QM/MM) molecular dynamics simulations are used to establish the structural features of the O state in bacteriorhodopsin (bR) and its conversion back to the bR ground state. The computed free energy surface is consistent with available experimental data for the kinetics and thermodynamics of the O to bR transition. The simulation results highlight the importance of the proton release group (PRG, consisting of Glu194/204) and the conserved arginine 82 in modulating the hydration level of the protein cavity. In particular, in the O state, deprotonation of the PRG and downward rotation of Arg82 lead to elevated hydration level and a continuous water network that connects the PRG to the protonated Asp85. Proton exchange through this water network is shown by ∼0.1-μs semiempirical QM/MM free energy simulations to occur through the generation and propagation of a proton hole, which is relayed by Asp212 and stabilized by Arg82. This mechanism provides an explanation for the observation that the D85S mutant of bacteriorhodopsin pumps chloride ions. The electrostatics-hydration coupling mechanism and the involvement of all titration states of water are likely applicable to many biomolecules involved in bioenergetic transduction.

Markov State Models to Study the Functional Dynamics of Proteins in the Wake of Machine Learning

Markov state models (MSMs) based on molecular dynamics (MD) simulations are routinely employed to study protein folding, however, their application to functional conformational changes of biomolecules is still limited. In the past few years, the field of computational chemistry has experienced a surge of advancements stemming from machine learning algorithms, and MSMs have not been left out. Unlike global processes, such as protein folding, the application of MSMs to functional conformational changes is challenging because they mostly consist of localized structural transitions. Therefore, it is critical to properly select a subset of structural features that can describe the slowest dynamics of these functional conformational changes. To address this challenge, we recommend several automatic feature selection methods such as Spectral-OASIS. To identify states in MSMs, the chosen features can be subject to dimensionality reduction methods such as TICA or deep learning based VAMPNets to project MD conformations onto a few collective variables for subsequent clustering. Another challenge for the application of MSMs to the study of functional conformational changes is the ability to comprehend their biophysical mechanisms, as MSMs built for these processes often require a large number of states. We recommend the recently developed quasi-MSMs (qMSMs) to address this issue. Compared to MSMs, qMSMs encode the non-Markovian dynamics via the generalized master equation and can significantly reduce the number of states. As a result, qMSMs can be built with a handful of states to facilitate the interpretation of functional conformational changes. In the wake of machine learning, we believe that the rapid advancement in the MSM methodology will lead to their wider application in studying functional conformational changes of biomolecules.

Beating Heart of Cytochrome c Oxidase: The Shared Proton of Heme a3 Propionates

Cytochrome c oxidase (CcO) pumps protons from the N-side to the P-side and consumes electrons from the P-side of the mitochondrial membrane driven by energy gained from reduction of dioxygen to water. ATP synthesis uses the resulting proton gradient and electrostatic potential difference. Since the distance a proton travels through CcO is too large for a one-step transfer process, proton-loading sites (PLS) that can carry protons transiently are necessary. One specific pump-active PLS couples to the redox reaction, thus energizing the proton to move across the membrane against electric potential and proton gradient. The PLS should also prevent proton backflow. Therefore, the propionates of the two redox-active hemes in CcO were suggested as PLS candidates although, according to CcO crystal structures, none of the four propionates can be protonated on account of strong H-bonds. Here, we show that modeling the local structure around heme a₃ propionates enhances significantly their capability of carrying a proton jointly. This was not possible for the propionates of heme a. The modeled structures are stable in molecular dynamics simulations (MDS) and are energetically similar to the crystal structure. Precise electrostatic energy computations of MDS data are used to estimate the pK_A values of all titratable residues in CcO. For the modeled structures, the heme a₃ propionates have pK_A values high enough to host a proton transiently but not too high to fix the proton permanently. The change in pK_A throughout the redox reaction is sufficient to push the proton to the P-side of the membrane and to provide the protons with the necessary amount of energy for ATP synthesis.

Reverse Protonation of Buried Ion-Pairs in Staphylococcal Nuclease Mutants

Although buried titratable residues in protein cavities are often of major functional importance, it is generally challenging to understand their properties such as the ionization state and factors of stabilization based on experimental studies alone. A specific set of examples involve buried Glu-Lys pairs in a series of variants of Staphylococcal nuclease, for which recent structural and thermodynamic studies appeared to suggest that both the stability and the ionization state of the buried Glu-Lys pair are sensitive to its orientation (i.e., Glu23-Lys36 vs Lys23-Glu36). To further clarify the situation, especially ionization states of the buried Glu-Lys pairs, we have conducted extensive molecular dynamics simulations and free energy computations. Microsecond molecular dynamics simulations show that the hydration level of the cavity depends on the orientation of the buried ion-pair therein as well as its ionization state; free energy simulations recapitulate the relative stability of Glu23-Lys36 (EK) vs Lys23-Glu36 (KE) mutants measured experimentally, although the difference is similar in magnitude regardless of the ionization state of the Glu-Lys pair. A complementary set of free energy simulations strongly suggests that, in contrast to the original suggestion in the experimental analysis, the Glu and Lys residues prefer to adopt their charge-neutral rather than the ionized states. This result is consistent with the low dielectric constant computed for water in the cavity, which makes it difficult for the protein cavity to stabilize a pair of charged Glu-Lys residues, even with water penetration. The current study highlights the role of free energy simulations in understanding the ionization state of buried titratable residues and the relevant energetic contributions, forming the basis for the rational design of buried charge networks in proteins.

Protein Motifs for Proton Transfers That Build the Transmembrane Proton Gradient

Biological membranes are barriers to polar molecules, so membrane embedded proteins control the transfers between cellular compartments. Protein controlled transport moves substrates and activates cellular signaling cascades. In addition, the electrochemical gradient across mitochondrial, bacterial and chloroplast membranes, is a key source of stored cellular energy. This is generated by electron, proton and ion transfers through proteins. The gradient is used to fuel ATP synthesis and to drive active transport. Here the mechanisms by which protons move into the buried active sites of Photosystem II (PSII), bacterial RCs (bRCs) and through the proton pumps, Bacteriorhodopsin (bR), Complex I and Cytochrome c oxidase (CcO), are reviewed. These proteins all use water filled proton transfer paths. The proton pumps, that move protons uphill from low to high concentration compartments, also utilize Proton Loading Sites (PLS), that transiently load and unload protons and gates, which block backflow of protons. PLS and gates should be synchronized so PLS proton affinity is high when the gate opens to the side with few protons and low when the path is open to the high concentration side. Proton transfer paths in the proteins we describe have different design features. Linear paths are seen with a unique entry and exit and a relatively straight path between them. Alternatively, paths can be complex with a tangle of possible routes. Likewise, PLS can be a single residue that changes protonation state or a cluster of residues with multiple charge and tautomer states.

Quantification of Local Electric Field Changes at the Active Site of Cytochrome c Oxidase by Fourier Transform Infrared Spectroelectrochemical Titrations

Cytochrome c oxidase (CcO) is a transmembrane protein complex that reduces molecular oxygen to water while translocating protons across the mitochondrial membrane. Changes in the redox states of its cofactors trigger both O₂ reduction and vectorial proton transfer, which includes a proton-loading site, yet unidentified. In this work, we exploited carbon monoxide (CO) as a vibrational Stark effect (VSE) probe at the binuclear center of CcO from Rhodobacter sphaeroides. The CO stretching frequency was monitored as a function of the electrical potential, using Fourier transform infrared (FTIR) absorption spectroelectrochemistry. We observed three different redox states (R₄CO, R₂CO, and O), determined their midpoint potential, and compared the resulting electric field to electrostatic calculations. A change in the local electric field strength of +2.9 MV/cm was derived, which was induced by the redox transition from R₄CO to R₂CO. We performed potential jump experiments to accumulate the R₂CO and R₄CO species and studied the FTIR difference spectra in the protein fingerprint region. The comparison of the experimental and computational results reveals that the key glutamic acid residue E286 is protonated in the observed states, and that its hydrogen-bonding environment is disturbed upon the redox transition of heme a₃. Our experiments also suggest propionate A of heme a₃ changing its protonation state in concert with the redox state of a second cofactor, heme a. This supports the role of propionic acid side chains as part of the proton-loading site.

Biomolecular QM/MM Simulations: What Are Some of the "Burning Issues"?

QM/MM simulations have become an indispensable tool in many chemical and biochemical investigations. Considering the tremendous degree of success, including recognition by a 2013 Nobel Prize in Chemistry, are there still "burning challenges" in QM/MM methods, especially for biomolecular systems? In this short Perspective, we discuss several issues that we believe greatly impact the robustness and quantitative applicability of QM/MM simulations to many, if not all, biomolecules. We highlight these issues with observations and relevant advances from recent studies in our group and others in the field. Despite such limited scope, we hope the discussions are of general interest and will stimulate additional developments that help push the field forward in meaningful directions.

Identifying the proton loading site cluster in the ba3 cytochrome c oxidase that loads and traps protons

Cytochrome c Oxidase (CcO) is the terminal electron acceptor in aerobic respiratory chain, reducing O₂ to water. The released free energy is stored by pumping protons through the protein, maintaining the transmembrane electrochemical gradient. Protons are held transiently in a proton loading site (PLS) that binds and releases protons driven by the electron transfer reaction cycle. Multi-Conformation Continuum Electrostatics (MCCE) was applied to crystal structures and Molecular Dynamics snapshots of the B-type Thermus thermophilus CcO. Six residues are identified as the PLS, binding and releasing protons as the charges on heme b and the binuclear center are changed: the heme a₃ propionic acids, Asp287, Asp372, His376 and Glu126B. The unloaded state has one proton and the loaded state two protons on these six residues. Different input structures, modifying the PLS conformation, show different proton distributions and result in different proton pumping behaviors. One loaded and one unloaded protonation states have the loaded/unloaded states close in energy so the PLS binds and releases a proton through the reaction cycle. The alternative proton distributions have state energies too far apart to be shifted by the electron transfers so are locked in loaded or unloaded states. Here the protein can use active states to load and unload protons, but has nearby trapped states, which stabilize PLS protonation state, providing new ideas about the CcO proton pumping mechanism. The distance between the PLS residues Asp287 and His376 correlates with the energy difference between loaded and unloaded states.

The redox-coupled proton-channel opening in cytochrome c oxidase

The interplay of cytochrome c oxidase's cofactor electrostatics, long-range conformational changes, H-bond rearrangement, and water dynamics enables transient proton-channel activation.

Electronation-dependent structural change at the proton exit side of cytochrome c oxidase as revealed by site-directed fluorescence labeling

Cytochrome c oxidase (CcO), the terminal enzyme of the respiratory chain of mitochondria and many aerobic prokaryotes that function as a redox-coupled proton pump, catalyzes the reduction of molecular oxygen to water. As part of the respiratory chain, CcO contributes to the proton motive force driving ATP synthesis. While many aspects of the enzyme's catalytic mechanisms have been established, a clear picture of the proton exit pathway(s) remains elusive. Here, we aim to gain insight into the molecular mechanisms of CcO through the development of a new homologous mutagenesis/expression system in Paracoccus denitrificans, which allows mutagenesis of CcO subunits 1, 2, and 3. Our system provides true single thiol-reactive CcO variants in a three-subunit base variant with unique labeling sites for the covalent attachment of reporter groups sensitive to nanoenvironmental factors like protonation, polarity, and hydration. To this end, we exchanged six residues on both membrane sides of CcO for cysteines. We show redox-dependent wetting changes at the proton uptake channel and increased polarity at the proton exit side of CcO upon electronation. We suggest an electronation-dependent conformational change to play a role in proton exit from CcO.

Tracing the Pathways of Waters and Protons in Photosystem II and Cytochrome c Oxidase

Photosystem II (PSII) uses water as the terminal electron donor, producing oxygen in the Mn4CaO5 oxygen evolving complex (OEC), while cytochrome c oxidase (CcO) reduces O2 to water in its heme–Cu binuclear center (BNC). Each protein is oriented in the membrane to add to the proton gradient. The OEC, which releases protons, is located near the P-side (positive, at low-pH) of the membrane. In contrast, the BNC is in the middle of CcO, so the protons needed for O2 reduction must be transferred from the N-side (negative, at high pH). In addition, CcO pumps protons from N- to P-side, coupled to the O2 reduction chemistry, to store additional energy. Thus, proton transfers are directly coupled to the OEC and BNC redox chemistry, as well as needed for CcO proton pumping. The simulations that study the changes in proton affinity of the redox active sites and the surrounding protein at different states of the reaction cycle, as well as the changes in hydration that modulate proton transfer paths, are described.

Atomistic insights into cardiolipin binding sites of cytochrome c oxidase

Mitochondrial cytochrome c oxidase couples the reduction of oxygen to proton pumping. Despite an overall good understanding of its molecular mechanism, the role of cardiolipin in protein function is not understood. Here, we have studied the cardiolipin-protein interactions in a dynamic context by means of atomistic molecular dynamics simulations performed on the entire structure of monomeric and dimeric forms of the enzyme. Several microseconds of simulation data reveal that the crystallographic cardiolipin molecules that glue two monomers together bind weakly in hybrid and single-component lipid bilayers and dissociate rapidly. Atomistic simulations performed in the absence of tightly bound cardiolipin molecules strongly perturb the structural integrity of subunits III and VIIa, thereby highlighting an indispensable nature of lipid-protein interactions in enzyme function such as proton uptake and oxygen channeling. Our results demonstrate the strength of molecular simulations in providing direct atomic description of lipid-protein processes that are difficult to achieve experimentally.

Investigating the Many Roles of Internal Water in Cytochrome c Oxidase

Cytochrome c oxidase (C cO) is the terminal enzyme in the respiratory electron transport chain. As part of its catalytic cycle, C cO transfers protons to its Fe-Cu binuclear center (BNC) to reduce oxygen, and in addition, it pumps protons across the mitochondrial inner, or bacterial, membrane where it is located. It is believed that this proton transport is facilitated by a network of water chains inside the enzyme. Here we present an analysis of the hydration of C cO, including the BNC region, using a semi-empirical hydration program, Dowser++, recently developed in our group. Using high-resolution X-ray data, we show that Dowser++ predictions match very accurately the water molecules seen in the D- and K-channels of C cO, as well as in the vicinity of its BNC. Moreover, Dowser++ predicts many more internal water molecules than is typically seen in the experiment. However, no significant hydration of the catalytic cavity in C cO described recently in the literature is observed. As Dowser++ itself does not account for structural changes of the protein, this result supports the earlier assessment that the proposed wetting transition in the catalytic cavity can only either be due to structural rearrangements of BNC, possibly induced by the charges during the catalytic cycle, or occur transiently, in concert with the proton transfer. Molecular dynamics simulations were performed to investigate the global dynamic nature of Dowser++ waters in C cO, and the results suggest a consistent explanation as to why some predicted water molecules would be missing in the experimental structures. Furthermore, in light of the significant protein hydration predicted by Dowser++, the dielectric constant of the hydrated cavities in C cO was also investigated using the Fröhlich-Kirkwood model; the results indicate that in the cavities where water is packed sufficiently densely the dielectric constant can approach values comparable even to that of bulk water.

Dewetting transitions coupled to K-channel activation in cytochrome c oxidase

Cytochrome c oxidase (CcO) drives aerobic respiratory chains in all organisms by transducing the free energy from oxygen reduction into an electrochemical proton gradient across a biological membrane.

Cytochrome c oxidase (CcO) drives aerobic respiratory chains in all organisms by transducing the free energy from oxygen reduction into an electrochemical proton gradient across a biological membrane. CcO employs the so-called D- and K-channels for proton uptake, but the molecular mechanism for activation of the K-channel has remained elusive for decades. We show here by combining large-scale atomistic molecular simulations with graph-theoretical water network analysis, and hybrid quantum/classical (QM/MM) free energy calculations, that the K-channel is activated by formation of a reactive oxidized intermediate in the binuclear heme a₃/Cu_B active site. This state induces electrostatic, hydration, and conformational changes that lower the barrier for proton transfer along the K-channel by dewetting pathways that connect the D-channel with the active site. Our combined results reconcile previous experimental findings and indicate that water dynamics plays a decisive role in the proton pumping machinery in CcO.

Dielectric Properties of a Protein Probed by Reversal of a Buried Ion Pair

Thirty years ago, Hwang and Warshel suggested that a microenvironment preorganized to stabilize an ion pair would be incapable of reorganizing to stabilize the reverse ion pair. The implications were that (1) proteins have a limited capacity to reorganize, even under the influence of strong interactions, such as those present when ionizable groups are buried in the hydrophobic interior of a protein, and (2) the inability of proteins to tolerate the reversal of buried ion pairs demonstrates the limitations inherent to continuum electrostatic models of proteins. Previously we showed that when buried individually in the interior of staphylococcal nuclease, Glu23 and Lys36 have p K_a values near pH 7, but when buried simultaneously, they establish a strong interaction of ∼5 kcal/mol and have p K_a values shifted toward more normal values. Here, using equilibrium thermodynamic measurements, crystal structures, and NMR spectroscopy experiments, we show that although the reversed, individual substitutions-Lys23 and Glu36-also have p K_a values near 7, when buried together, they neither establish a strong interaction nor promote reorganization of their microenvironment. These experiments both confirm Warshel's original hypothesis and expand it by showing that it applies to reorganization, as demonstrated by our artificial ion pairs, as well as to preorganization as is commonly argued for motifs that stabilize naturally occurring ion pairs in polar microenvironments. These data constitute a challenging benchmark useful to test the ability of structure-based algorithms to reproduce the compensation between self-energy, Coulomb and polar interactions in hydrophobic environments of proteins.

Hydrogen-Bonded Network and Water Dynamics in the D-channel of Cytochrome c Oxidase

Proton transfer in cytochrome c oxidase (CcO) from the cellular inside to the binuclear redox centre as well as proton pumping through the membrane takes place through proton entrance via two distinct pathways, the D- and K-channel. Both channels show a dependence of their hydration level on the protonation states of their key residues, K362 for the K-channel, and E286 or D132 for the D-channel. In the oxidative half of CcO's catalytic cycle the D-channel is the proton-conducting path. For this channel, an interplay of protonation state of the D-channel residues with the water and hydrogen-bond dynamics has been observed in molecular dynamics simulations of the CcO protein, embedded in a lipid bi-layer, modelled in different protonation states. Protonation of residue E286 at the end of the D-channel results in a hydrogen-bonded network pointing from E286 to N139, that is against proton transport, and favouring N139 conformations which correspond to a closed asparagine gate (formed by residues N121 and N139). Consequently, the hydration level is lower than with unprotonated E286. In those models, the Asn gate is predominantly open, allowing water molecules to pass and thus increase the hydration level. The hydrogen-bonded network in these states exhibits longer life times of the Asn residues with water than other models and shows the D-channel to be traversable from the entrance, D132, to exit, E286. The D-channel can thus be regarded as auto-regulated with respect to proton transport, allowing proton passage only when required, that is the proton is located at the lower part of the D-channel (D132 to Asn gate) and not at the exit (E286).