Light harvesting by lamellar chromatophores in Rhodospirillum photometricum

SPANA: Spatial decomposition analysis for cellular-scale molecular dynamics simulations

The rapid increase in computational power with the latest supercomputers has enabled atomistic molecular dynamics (MDs) simulations of biomolecules in biological membrane, cytoplasm, and other cellular environments. These environments often contain a million or more atoms to be simulated simultaneously. Therefore, their trajectory analyses involve heavy computations that can become a bottleneck in the computational studies. Spatial decomposition analysis (SPANA) is a set of analysis tools in the Generalized-Ensemble Simulation System (GENESIS) software package that can carry out MD trajectory analyses of large-scale biological simulations using multiple CPU cores in parallel. SPANA applies the spatial decomposition of a large biological system to distribute structural and dynamical analyses into individual CPU cores, which reduces the computational time and the memory size, significantly. SPANA opens new possibilities for detailed atomistic analyses of biomacromolecules as well as solvent water molecules, ions, and metabolites in MD simulation trajectories of very large biological systems containing more than millions of atoms in cellular environments.

An efficient time-domain implementation of the multichromophoric Förster resonant energy transfer method

The excitation energy transfer (EET) process for photosynthetic antenna complexes consisting of subunits, each comprised of multiple chromophores, remains challenging to describe. The multichromophoric Förster resonance energy transfer theory is a popular method to describe the EET process in such systems. This paper presents a new time-domain method for calculating energy transfer based on the combination of multichromophoric Förster resonance energy transfer theory and the Numerical Integration of the Schrödinger Equation method. After validating the method on simple model systems, we apply it to the Light-Harvesting antenna 2 (LH2) complex, a light harvesting antenna found in purple bacteria. We use a simple model combining the overdamped Brownian oscillators to describe the dynamic disorder originating from the environmental fluctuations and the transition charge from the electrostatic potential coupling model to determine the interactions between chromophores. We demonstrate that with this model, both the calculated spectra and the EET rates between the two rings within the LH2 complex agree well with experimental results. We further find that the transfer between the strongly coupled rings of neighboring LH2 complexes can also be well described with our method. We conclude that our new method accurately describes the EET rate for biologically relevant multichromophoric systems, which are similar to the LH2 complex. Computationally, the new method is very tractable, especially for slow processes. We foresee that the method can be applied to efficiently calculate transfer in artificial systems as well and may pave the way for calculating multidimensional spectra of extensive multichromophoric systems in the future.

Controlling photosynthetic energy conversion by small conformational changes

Control phenomena in biology usually refer to changes in gene expression and protein translation and modification. In this paper, another mode of regulation is highlighted; we propose that photosynthetic organisms can harness the interplay between localization and delocalization of energy transfer by utilizing small conformational changes in the structure of light-harvesting complexes. We examine the mechanism of energy transfer in photosynthetic pigment-protein complexes, first through the scope of theoretical work and then by in vitro studies of these complexes. Next, the biological relevance to evolutionary fitness of this localization-delocalization switch is explored by in vivo experiments on desert crust and marine cyanobacteria, which are both exposed to rapidly changing environmental conditions. These examples demonstrate the flexibility and low energy cost of this mechanism, making it a competitive survival strategy.

Large-Scale Molecular Dynamics Simulations of Cellular Compartments

Molecular dynamics or MD simulation is gradually maturing into a tool for constructing in vivo models of living cells in atomistic details. The feasibility of such models is bolstered by integrating the simulations with data from microscopic, tomographic and spectroscopic experiments on exascale supercomputers, facilitated by the use of deep learning technologies. Over time, MD simulation has evolved from tens of thousands of atoms to over 100 million atoms comprising an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium. In this chapter, we present a step-by-step outline for preparing, executing and analyzing such large-scale MD simulations of biological systems that are essential to life processes. All scripts are provided via GitHub.

Normal mode analysis of membrane protein dynamics using the vibrational subsystem analysis

The vibrational subsystem analysis is a useful approach that allows for evaluating the spectrum of modes of a given system by integrating out the degrees of freedom accessible to the environment. The approach could be utilized for exploring the collective dynamics of a membrane protein (system) coupled to the lipid bilayer (environment). However, the application to membrane proteins is limited due to high computational costs of modeling a sufficiently large membrane environment unbiased by end effects, which drastically increases the size of the investigated system. We derived a recursive formula for calculating the reduced Hessian of a membrane protein embedded in a lipid bilayer by decomposing the membrane into concentric cylindrical domains with the protein located at the center. The approach allows for the design of a time- and memory-efficient algorithm and a mathematical understanding of the convergence of the reduced Hessian with respect to increasing membrane sizes. The application to the archaeal aspartate transporter Glt_Ph illustrates its utility and efficiency in capturing the transporter's elevator-like movement during its transition between outward-facing and inward-facing states.

Designing and understanding light-harvesting devices with machine learning

Understanding the fundamental processes of light-harvesting is crucial to the development of clean energy materials and devices. Biological organisms have evolved complex metabolic mechanisms to efficiently convert sunlight into chemical energy. Unraveling the secrets of this conversion has inspired the design of clean energy technologies, including solar cells and photocatalytic water splitting. Describing the emergence of macroscopic properties from microscopic processes poses the challenge to bridge length and time scales of several orders of magnitude. Machine learning experiences increased popularity as a tool to bridge the gap between multi-level theoretical models and Edisonian trial-and-error approaches. Machine learning offers opportunities to gain detailed scientific insights into the underlying principles governing light-harvesting phenomena and can accelerate the fabrication of light-harvesting devices.

Membrane Dynamics in Phototrophic Bacteria

Photosynthetic membranes are typically densely packed with proteins, and this is crucial for their function in efficient trapping of light energy. Despite being crowded with protein, the membranes are fluid systems in which proteins and smaller molecules can diffuse. Fluidity is also crucial for photosynthetic function, as it is essential for biogenesis, electron transport, and protein redistribution for functional regulation. All photosynthetic membranes seem to maintain a delicate balance between crowding, order, and fluidity. How does this work in phototrophic bacteria? In this review, we focus on two types of intensively studied bacterial photosynthetic membranes: the chromatophore membranes of purple bacteria and the thylakoid membranes of cyanobacteria. Both systems are distinct from the plasma membrane, and both have a distinctive protein composition that reflects their specialized roles. Chromatophores are formed from plasma membrane invaginations, while thylakoid membranes appear to be an independent intracellular membrane system. We discuss the techniques that can be applied to study the organization and dynamics of these membrane systems, including electron microscopy techniques, atomic force microscopy, and many variants of fluorescence microscopy. We go on to discuss the insights that havebeen acquired from these techniques, and the role of membrane dynamics in the physiology of photosynthetic membranes. Membrane dynamics on multiple timescales are crucial for membrane function, from electron transport on timescales of microseconds to milliseconds to regulation and biogenesis on timescales of minutes to hours. We emphasize the open questions that remain in the field.

Atoms to Phenotypes: Molecular Design Principles of Cellular Energy Metabolism

We report a 100-million atom-scale model of an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium, that reveals the cascade of energy conversion steps culminating in the generation of ATP from sunlight. Molecular dynamics simulations of this vesicle elucidate how the integral membrane complexes influence local curvature to tune photoexcitation of pigments. Brownian dynamics of small molecules within the chromatophore probe the mechanisms of directional charge transport under various pH and salinity conditions. Reproducing phenotypic properties from atomistic details, a kinetic model evinces that low-light adaptations of the bacterium emerge as a spontaneous outcome of optimizing the balance between the chromatophore's structural integrity and robust energy conversion. Parallels are drawn with the more universal mitochondrial bioenergetic machinery, from whence molecular-scale insights into the mechanism of cellular aging are inferred. Together, our integrative method and spectroscopic experiments pave the way to first-principles modeling of whole living cells.

Single- and multi-component chiral supraparticles as modular enantioselective catalysts

Nanoscale biological assemblies exemplified by exosomes, endosomes and capsids, play crucial roles in all living systems. Supraparticles (SP) from inorganic nanoparticles (NPs) replicate structural characteristics of these bioassemblies, but it is unknown whether they can mimic their biochemical functions. Here, we show that chiral ZnS NPs self-assemble into 70–100 nm SPs that display sub-nanoscale porosity associated with interstitial spaces between constituent NPs. Similarly to photosynthetic bacterial organelles, these SPs can serve as photocatalysts, enantioselectively converting L- or D-tyrosine (Tyr) into dityrosine (diTyr). Experimental data and molecular dynamic simulations indicate that the chiral bias of the photocatalytic reaction is associated with the chiral environment of interstitial spaces and preferential partitioning of enantiomers into SPs, which can be further enhanced by co-assembling ZnS with Au NPs. Besides replicating a specific function of biological nanoassemblies, these findings establish a path to enantioselective oxidative coupling of phenols for biomedical and other needs.

Nanoscale biological assemblies play crucial roles in all living systems and display a variety of chemical functionalities. Here the authors show that it is possible to replicate some of the biochemical functions in similarly-sized assemblies made from inorganic nanoparticles.

Molecular Dynamics Simulations of Membrane Proteins: An Overview

Simulations of membrane proteins have been rising in popularity in the past decade. Advancements in technology and force fields made it possible to simulate behavior of membrane proteins. Membrane protein simulations can now be used as supporting evidence for experimental findings, for elucidating protein mechanisms, and validating protein crystal structures. Unrelated to experimental data, these simulations can also serve to investigate larger scale processes like protein sorting, protein-membrane interactions, and more. In this review, the history as well as the state-of-the-art methodologies in membrane protein simulations will be summarized. An emphasis will be put on how to set up the system and on the current models for the different components of the simulation system. An overview of the available tools for membrane protein simulation will be given, and current limitations and prospects will also be discussed.

PyContact: Rapid, Customizable, and Visual Analysis of Noncovalent Interactions in MD Simulations

Molecular dynamics (MD) simulations have become ubiquitous in all areas of life sciences. The size and model complexity of MD simulations are rapidly growing along with increasing computing power and improved algorithms. This growth has led to the production of a large amount of simulation data that need to be filtered for relevant information to address specific biomedical and biochemical questions. One of the most relevant molecular properties that can be investigated by all-atom MD simulations is the time-dependent evolution of the complex noncovalent interaction networks governing such fundamental aspects as molecular recognition, binding strength, and mechanical and structural stability. Extracting, evaluating, and visualizing noncovalent interactions is a key task in the daily work of structural biologists. We have developed PyContact, an easy-to-use, highly flexible, and intuitive graphical user interface-based application, designed to provide a toolkit to investigate biomolecular interactions in MD trajectories. PyContact is designed to facilitate this task by enabling identification of relevant noncovalent interactions in a comprehensible manner. The implementation of PyContact as a standalone application enables rapid analysis and data visualization without any additional programming requirements, and also preserves full in-program customization and extension capabilities for advanced users. The statistical analysis representation is interactively combined with full mapping of the results on the molecular system through the synergistic connection between PyContact and VMD. We showcase the capabilities and scientific significance of PyContact by analyzing and visualizing in great detail the noncovalent interactions underlying the ion permeation pathway of the human P2X3 receptor. As a second application, we examine the protein-protein interaction network of the mechanically ultrastable cohesin-dockering complex.

Prediction of Thylakoid Lipid Binding Sites on Photosystem II

The thylakoid membrane has a unique lipid composition, consisting mostly of galactolipids. These thylakoid lipids have important roles in photosynthesis. Here, we investigate to what extent these lipids bind specifically to the Photosystem II complex. To this end, we performed coarse-grain MD simulations of the Photosystem II complex embedded in a thylakoid membrane with realistic composition. Based on >85 μs simulation time, we find that monogalactosyldiacylglycerol and sulfoquinovosyldiacylglycerol lipids are enriched in the annular shell around the protein, and form distinct binding sites. From the analysis of residue contacts, we conclude that electrostatic interactions play an important role in stabilizing these binding sites. Furthermore, we find that chlorophyll a has a prevalent role in the coordination of the lipids. In addition, we observe lipids to diffuse in and out of the plastoquinone exchange cavities, allowing exchange of cocrystallized lipids with the bulk membrane and suggesting a more open nature of the plastoquinone exchange cavity. Together, our data provide a wealth of information on protein-lipid interactions for a key protein in photosynthesis.

Lateral Segregation of Photosystem I in Cyanobacterial Thylakoids

Photosystem I (PSI) is the dominant photosystem in cyanobacteria and it plays a pivotal role in cyanobacterial metabolism. Despite its biological importance, the native organization of PSI in cyanobacterial thylakoid membranes is poorly understood. Here, we use atomic force microscopy (AFM) to show that ordered, extensive macromolecular arrays of PSI complexes are present in thylakoids from Thermosynechococcus elongatus, Synechococcus sp PCC 7002, and Synechocystis sp PCC 6803. Hyperspectral confocal fluorescence microscopy and three-dimensional structured illumination microscopy of Synechocystis sp PCC 6803 cells visualize PSI domains within the context of the complete thylakoid system. Crystallographic and AFM data were used to build a structural model of a membrane landscape comprising 96 PSI trimers and 27,648 chlorophyll a molecules. Rather than facilitating intertrimer energy transfer, the close associations between PSI primarily maximize packing efficiency; short-range interactions with Complex I and cytochrome b₆f are excluded from these regions of the membrane, so PSI turnover is sustained by long-distance diffusion of the electron donors at the membrane surface. Elsewhere, PSI-photosystem II contact zones provide sites for docking phycobilisomes and the formation of megacomplexes. PSI-enriched domains in cyanobacteria might foreshadow the partitioning of PSI into stromal lamellae in plants, similarly sustained by long-distance diffusion of electron carriers.

Understanding the Phosphorylation Mechanism by Using Quantum Chemical Calculations and Molecular Dynamics Simulations

Phosphorylation is one of the most frequent post-translational modifications on proteins. It regulates many cellular processes by modulation of phosphorylation on protein structure and dynamics. However, the mechanism of phosphorylation-induced conformational changes of proteins is still poorly understood. Here, we report a computational study of three representative groups of tyrosine in ADP-ribosylhydrolase 1, serine in BTG2, and serine in Sp100C by using six molecular dynamics (MD) simulations and quantum chemical calculations. Added phosphorylation was found to disrupt hydrogen bond, and increase new weak interactions (hydrogen bond and hydrophobic interaction) during MD simulations, leading to conformational changes. Quantum chemical calculations further indicate that the phosphorylation on tyrosine, threonine, and serine could decrease the optical band gap energy (Egap), which can trigger electronic transitions to form or disrupt interactions easily. Our results provide an atomic and electronic description of how phosphorylation facilitates conformational and dynamic changes in proteins, which may be useful for studying protein function and protein design.

Challenges of Integrating Stochastic Dynamics and Cryo-Electron Tomograms in Whole-Cell Simulations

Cryo-electron tomography (cryo-ET) has rapidly emerged as a powerful tool to investigate the internal, three-dimensional spatial organization of the cell. In parallel, the GPU-based technology to perform spatially resolved stochastic simulations of whole cells has arisen, allowing the simulation of complex biochemical networks over cell cycle time scales using data taken from -omics, single molecule experiments, and in vitro kinetics. By using real cell geometry derived from cryo-ET data, we have the opportunity to imbue these highly detailed structural data-frozen in time-with realistic biochemical dynamics and investigate how cell structure affects the behavior of the embedded chemical reaction network. Here we present two examples to illustrate the challenges and techniques involved in integrating structural data into stochastic simulations. First, a tomographic reconstruction of Saccharomyces cerevisiae is used to construct the geometry of an entire cell through which a simple stochastic model of an inducible genetic switch is studied. Second, a tomogram of the nuclear periphery in a HeLa cell is converted directly to the simulation geometry through which we study the effects of cellular substructure on the stochastic dynamics of gene repression. These simple chemical models allow us to illustrate how to build whole-cell simulations using cryo-ET derived geometry and the challenges involved in such a process.

Direct Imaging of Protein Organization in an Intact Bacterial Organelle Using High-Resolution Atomic Force Microscopy

The function of bioenergetic membranes is strongly influenced by the spatial arrangement of their constituent membrane proteins. Atomic force microscopy (AFM) can be used to probe protein organization at high resolution, allowing individual proteins to be identified. However, previous AFM studies of biological membranes have typically required that curved membranes are ruptured and flattened during sample preparation, with the possibility of disruption of the native protein arrangement or loss of proteins. Imaging native, curved membranes requires minimal tip-sample interaction in both lateral and vertical directions. Here, long-range tip-sample interactions are reduced by optimizing the imaging buffer. Tapping mode AFM with high-resonance-frequency small and soft cantilevers, in combination with a high-speed AFM, reduces the forces due to feedback error and enables application of an average imaging force of tens of piconewtons. Using this approach, we have imaged the membrane organization of intact vesicular bacterial photosynthetic "organelles", chromatophores. Despite the highly curved nature of the chromatophore membrane and lack of direct support, the resolution was sufficient to identify the photosystem complexes and quantify their arrangement in the native state. Successive imaging showed the proteins remain surprisingly static, with minimal rotation or translation over several-minute time scales. High-order assemblies of RC-LH1-PufX complexes are observed, and intact ATPases are successfully imaged. The methods developed here are likely to be applicable to a broad range of protein-rich vesicles or curved membrane systems, which are an almost ubiquitous feature of native organelles.

Molecular Dynamics of Photosystem II Embedded in the Thylakoid Membrane

Photosystem II (PSII) is one of the key protein complexes in photosynthesis. We introduce a coarse grained model of PSII and present the analysis of 60 μs molecular dynamics simulations of PSII in both monomeric and dimeric form, embedded in a thylakoid membrane model that reflects its native lipid composition. We describe in detail the setup of the protein complex and the many natural cofactors and characterize their mobility. Overall we find that the protein subunits and cofactors are more flexible toward the periphery of the complex as well as near the PLQ exchange cavity and at the dimer interface. Of all cofactors, β-carotenes show the highest mobility. Some of the β-carotenes diffuse in and out of the protein complex via the thylakoid membrane. In contrast with the PSII dimer, the monomeric form adopts a tilted conformation in the membrane, with strong interactions between the soluble PsbO subunit and the glycolipid headgroups. Interestingly, the tilted conformation causes buckling of the membrane. Together, our results provide an unprecedented view of PSII dynamics on a microsecond time scale. Our data may be used as basis for the interpretation of experimental data as well as for theoretical models describing exciton energy transfer.

Overall energy conversion efficiency of a photosynthetic vesicle

The chromatophore of purple bacteria is an intracellular spherical vesicle that exists in numerous copies in the cell and that efficiently converts sunlight into ATP synthesis, operating typically under low light conditions. Building on an atomic-level structural model of a low-light-adapted chromatophore vesicle from Rhodobacter sphaeroides, we investigate the cooperation between more than a hundred protein complexes in the vesicle. The steady-state ATP production rate as a function of incident light intensity is determined after identifying quinol turnover at the cytochrome bc1 complex (cytb⁢c1) as rate limiting and assuming that the quinone/quinol pool of about 900 molecules acts in a quasi-stationary state. For an illumination condition equivalent to 1% of full sunlight, the vesicle exhibits an ATP production rate of 82 ATP molecules/s. The energy conversion efficiency of ATP synthesis at illuminations corresponding to 1%–5% of full sunlight is calculated to be 0.12–0.04, respectively. The vesicle stoichiometry, evolutionarily adapted to the low light intensities in the habitat of purple bacteria, is suboptimal for steady-state ATP turnover for the benefit of protection against over-illumination.

DOI:http://dx.doi.org/10.7554/eLife.09541.001

Photosynthesis, or the conversion of light energy into chemical energy, is a process that powers almost all life on Earth. Plants and certain bacteria share similar processes to perform photosynthesis, though the purple bacterium Rhodobacter sphaeroides uses a photosynthetic system that is much less complex than that in plants. Light harvesting inside the bacterium takes place in up to hundreds of compartments called chromatophores. Each chromatophore in turn contains hundreds of cooperating proteins that together absorb the energy of sunlight and convert and store it in molecules of ATP, the universal energy currency of all cells.

The chromatophore of primitive purple bacteria provides a model for more complex photosynthetic systems in plants. Though researchers had characterized its individual components over the years, less was known about the overall architecture of the chromatophore and how its many components work together to harvest light energy efficiently and robustly. This knowledge would provide insight into the evolutionary pressures that shaped the chromatophore and its ability to work efficiently at different light intensities.

Sener et al. now present a highly detailed structural model of the chromatophore of purple bacteria based on the findings of earlier studies. The model features the position of every atom of the constituent proteins and is used to examine how energy is transferred and converted. Sener et al. describe the sequence of energy conversion steps and calculate the overall energy conversion efficiency, namely how much of the light energy arriving at the microorganism is stored as ATP.

These calculations show that the chromatophore is optimized to produce chemical energy at low light levels typical of purple bacterial habitats, and dissipate excess energy to avoid being damaged under brighter light. The chromatophore’s architecture also displays robustness against perturbations of its components. In the future, the approach used by Sener et al. to describe light harvesting in this bacterial compartment can be applied to more complex systems, such as those in plants.

DOI:http://dx.doi.org/10.7554/eLife.09541.002

Atomic Detail Visualization of Photosynthetic Membranes with GPU-Accelerated Ray Tracing

The cellular process responsible for providing energy for most life on Earth, namely photosynthetic light-harvesting, requires the cooperation of hundreds of proteins across an organelle, involving length and time scales spanning several orders of magnitude over quantum and classical regimes. Simulation and visualization of this fundamental energy conversion process pose many unique methodological and computational challenges. We present, in two accompanying movies, light-harvesting in the photosynthetic apparatus found in purple bacteria, the so-called chromatophore. The movies are the culmination of three decades of modeling efforts, featuring the collaboration of theoretical, experimental, and computational scientists. We describe the techniques that were used to build, simulate, analyze, and visualize the structures shown in the movies, and we highlight cases where scientific needs spurred the development of new parallel algorithms that efficiently harness GPU accelerators and petascale computers.

Influence of model resolution on geometric simulations of antibody aggregation

It is estimated that allergies afflict up to 40% of the world's population. A primary mediator for allergies is the aggregation of antigens and IgE antibodies bound to cell-surface receptors, FcεRI. Antibody/antigen aggregate formation causes stimulation of mast cells and basophils, initiating cellular degranulation and releasing immune mediators which produce an allergic or anaphylactic response. Understanding the shape and structure of these aggregates can provide critical insights into the allergic response. We have previously developed methods to geometrically model, simulate and analyze antibody aggregation inspired by rigid body robotic motion simulations. Our technique handles the large size and number of molecules involved in aggregation, providing an advantage over traditional simulations such as molecular dynamics (MD) and coarse-grained energetic models. In this paper, we study the impact of model resolution on simulations of geometric structures using both our previously developed Monte Carlo simulation and a novel application of rule-based modeling. These methods complement each other, the former providing explicit geometric detail and the latter providing a generic representation where multiple resolutions can be captured. Our exploration is focused on two antigens, a man-made antigen with three binding sites, DF3, and a common shrimp allergen (antigen), Pen a 1. We find that impact of resolution is minimal for DF3, a small globular antigen, but has a larger impact on Pen a 1, a rod-shaped molecule. The volume reduction caused by the loss in resolution allows more binding site accessibility, which can be quantified using a rule-based model with implicit geometric input. Clustering analysis of our simulation shows good correlation when compared with available experimental results. Moreover, collisions in all-atom reconstructions are negligible, at around 0.2% at 90% reduction.

Computational Methodologies for Real-Space Structural Refinement of Large Macromolecular Complexes

The rise of the computer as a powerful tool for model building and refinement has revolutionized the field of structure determination for large biomolecular systems. Despite the wide availability of robust experimental methods capable of resolving structural details across a range of spatiotemporal resolutions, computational hybrid methods have the unique ability to integrate the diverse data from multimodal techniques such as X-ray crystallography and electron microscopy into consistent, fully atomistic structures. Here, commonly employed strategies for computational real-space structural refinement are reviewed, and their specific applications are illustrated for several large macromolecular complexes: ribosome, virus capsids, chemosensory array, and photosynthetic chromatophore. The increasingly important role of computational methods in large-scale structural refinement, along with current and future challenges, is discussed.

Quantum Chemical Studies of Light Harvesting

The design of optimal light-harvesting (supra)molecular systems and materials is one of the most challenging frontiers of science. Theoretical methods and computational models play a fundamental role in this difficult task, as they allow the establishment of structural blueprints inspired by natural photosynthetic organisms that can be applied to the design of novel artificial light-harvesting devices. Among theoretical strategies, the application of quantum chemical tools represents an important reality that has already reached an evident degree of maturity, although it still has to show its real potentials. This Review presents an overview of the state of the art of this strategy, showing the actual fields of applicability but also indicating its current limitations, which need to be solved in future developments.

From light-harvesting to photoprotection: structural basis of the dynamic switch of the major antenna complex of plants (LHCII)

Light-Harvesting Complex II (LHCII) is largely responsible for light absorption and excitation energy transfer in plants in light-limiting conditions, while in high-light it participates in photoprotection. It is generally believed that LHCII can change its function by switching between different conformations. However, the underlying molecular picture has not been elucidated yet. The available crystal structures represent the quenched form of the complex, while solubilized LHCII has the properties of the unquenched state. To determine the structural changes involved in the switch and to identify potential quenching sites, we have explored the structural dynamics of LHCII, by performing a series of microsecond Molecular Dynamics simulations. We show that LHCII in the membrane differs substantially from the crystal and has the signatures that were experimentally associated with the light-harvesting state. Local conformational changes at the N-terminus and at the xanthophyll neoxanthin are found to strongly correlate with changes in the interactions energies of two putative quenching sites. In particular conformational disorder is observed at the terminal emitter resulting in large variations of the excitonic coupling strength of this chlorophyll pair. Our results strongly support the hypothesis that light-harvesting regulation in LHCII is coupled with structural changes.

Biomembranes in atomistic and coarse-grained simulations

The architecture of biological membranes is tightly coupled to the localization, organization, and function of membrane proteins. The organelle-specific distribution of lipids allows for the formation of functional microdomains (also called rafts) that facilitate the segregation and aggregation of membrane proteins and thus shape their function. Molecular dynamics simulations enable to directly access the formation, structure, and dynamics of membrane microdomains at the molecular scale and the specific interactions among lipids and proteins on timescales from picoseconds to microseconds. This review focuses on the latest developments of biomembrane force fields for both atomistic and coarse-grained molecular dynamics (MD) simulations, and the different levels of coarsening of biomolecular structures. It also briefly introduces scale-bridging methods applicable to biomembrane studies, and highlights selected recent applications.

Structure-Encoded Global Motions and Their Role in Mediating Protein-Substrate Interactions

Recent structure-based computational studies suggest that, in contrast to the classical description of equilibrium fluctuations as wigglings and jigglings, proteins have access to well-defined spectra of collective motions, called intrinsic dynamics, encoded by their structure under native state conditions. In particular, the global modes of motions (at the low frequency end of the spectrum) are shown by multiple studies to be highly robust to minor differences in the structure or to detailed interactions at the atomic level. These modes, encoded by the overall fold, usually define the mechanisms of interactions with substrates. They can be estimated by low-resolution models such as the elastic network models (ENMs) exclusively based on interresidue contact topology. The ability of ENMs to efficiently assess the global motions intrinsically favored by the overall fold as well as the relevance of these predictions to the dominant changes in structure experimentally observed for a given protein in the presence of different substrates suggest that the intrinsic dynamics plays a role in mediating protein-substrate interactions. These observations underscore the functional significance of structure-encoded dynamics, or the importance of the predisposition to favor functional global modes in the evolutionary selection of structures.

Monte Carlo Modeling of Spectral Diffusion Employing Multiwell Protein Energy Landscapes: Application to Pigment-Protein Complexes Involved in Photosynthesis

We are reporting development and initial applications of the light-induced and thermally induced spectral diffusion modeling software, covering nonphotochemical spectral hole burning (NPHB), hole recovery, and single-molecule spectroscopy and involving random generation of the multiwell protein energy landscapes. The model includes tunneling and activated barrier-hopping in both ground and excited states of a protein-chromophore system. Evolution of such a system is predicted by solving the system of rate equations. Using the barrier parameters from the range typical for the energy landscapes of the pigment-protein complexes involved in photosynthesis, we (a) show that realistic cooling of the sample must result in proteins quite far from thermodynamic equilibrium, (b) demonstrate hole evolution in the cases of burning, fixed-temperature recovery and thermocycling that mostly agrees with the experiment and modeling based on the NPHB master equation, and (c) explore the effects of different protein energy landscapes on the antihole shape. Introducing the multiwell energy landscapes and starting the hole burning experiments in realistic nonequilibrium conditions are not sufficient to explain all experimental observations even qualitatively. Therefore, for instance, one is required to invoke the modified NPHB mechanism where a complex interplay of several small conformational changes is poising the energy landscape of the pigment-protein system for downhill tunneling.

Molecular dynamics simulations of large macromolecular complexes

Connecting dynamics to structural data from diverse experimental sources, molecular dynamics simulations permit the exploration of biological phenomena in unparalleled detail. Advances in simulations are moving the atomic resolution descriptions of biological systems into the million-to-billion atom regime, in which numerous cell functions reside. In this opinion, we review the progress, driven by large-scale molecular dynamics simulations, in the study of viruses, ribosomes, bioenergetic systems, and other diverse applications. These examples highlight the utility of molecular dynamics simulations in the critical task of relating atomic detail to the function of supramolecular complexes, a task that cannot be achieved by smaller-scale simulations or existing experimental approaches alone.

Mapping to Irregular Torus Topologies and Other Techniques for Petascale Biomolecular Simulation

Currently deployed petascale supercomputers typically use toroidal network topologies in three or more dimensions. While these networks perform well for topology-agnostic codes on a few thousand nodes, leadership machines with 20,000 nodes require topology awareness to avoid network contention for communication-intensive codes. Topology adaptation is complicated by irregular node allocation shapes and holes due to dedicated input/output nodes or hardware failure. In the context of the popular molecular dynamics program NAMD, we present methods for mapping a periodic 3-D grid of fixed-size spatial decomposition domains to 3-D Cray Gemini and 5-D IBM Blue Gene/Q toroidal networks to enable hundred-million atom full machine simulations, and to similarly partition node allocations into compact domains for smaller simulations using multiple-copy algorithms. Additional enabling techniques are discussed and performance is reported for NCSA Blue Waters, ORNL Titan, ANL Mira, TACC Stampede, and NERSC Edison.

All-atom molecular dynamics simulation of a photosystem i/detergent complex

All-atom molecular dynamics (MD) simulation was used to investigate the solution structure and dynamics of the photosynthetic pigment-protein complex photosystem I (PSI) from Thermosynechococcus elongatus embedded in a toroidal belt of n-dodecyl-β-d-maltoside (DDM) detergent. Evaluation of root-mean-square deviations (RMSDs) relative to the known crystal structure show that the protein complex surrounded by DDM molecules is stable during the 200 ns simulation time, and root-mean-square fluctuation (RMSF) analysis indicates that regions of high local mobility correspond to solvent-exposed regions such as turns in the transmembrane α-helices and flexible loops on the stromal and lumenal faces. Comparing the protein-detergent complex to a pure detergent micelle, the detergent surrounding the PSI trimer is found to be less densely packed but with more ordered detergent tails, contrary to what is seen in most lipid bilayer models. We also investigated any functional implications for the observed conformational dynamics and protein-detergent interactions, discovering interesting structural changes in the psaL subunits associated with maintaining the trimeric structure of the protein. Importantly, we find that the docking of soluble electron mediators such as cytochrome c6 and ferredoxin to PSI is not significantly impacted by the solubilization of PSI in detergent.