Conformational dynamics of adenylate kinase in crystals.

Adenylate kinase is a ubiquitous enzyme in living systems and undergoes dramatic conformational changes during its catalytic cycle. For these reasons, it is widely studied by genetic, biochemical, and biophysical methods, both experimental and theoretical. We have determined the basic crystal structures of three differently liganded states of adenylate kinase from Methanotorrus igneus, a hyperthermophilic organism whose adenylate kinase is a homotrimeric oligomer. The multiple copies of each protomer in the asymmetric unit of the crystal provide a unique opportunity to study the variation in the structure and were further analyzed using advanced crystallographic refinement methods and analysis tools to reveal conformational heterogeneity and, thus, implied dynamic behaviors in the catalytic cycle.

Persistent Protein Motions in a Rugged Energy Landscape Revealed by Normal Mode Ensemble Analysis.

Proteins are allosteric machines that couple motions at distinct, often distant, sites to control biological function. Low-frequency structural vibrations are a mechanism of this long-distance connection and are often used computationally to predict correlations, but experimentally identifying the vibrations associated with specific motions has proved challenging. Spectroscopy is an ideal tool to explore these excitations, but measurements have been largely unable to identify important frequency bands. The result is at odds with some previous calculations and raises the question what methods could successfully characterize protein structural vibrations. Here we show the lack of spectral structure arises in part from the variations in protein structure as the protein samples the energy landscape. However, by averaging over the energy landscape as sampled using an aggregate 18.5 µs of all-atom molecular dynamics simulation of hen egg white lysozyme and normal-mode analyses, we find vibrations with large overlap with functional displacements are surprisingly concentrated in narrow frequency bands. These bands are not apparent in either the ensemble averaged vibrational density of states or isotropic absorption. However, in the case of the ensemble averaged anisotropic absorption, there is persistent spectral structure and overlap between this structure and the functional displacement frequency bands. We systematically lay out heuristics for calculating the spectra robustly, including the need for statistical sampling of the protein and inclusion of adequate water in the spectral calculation. The results show the congested spectrum of these complex molecules obscures important frequency bands associated with function and reveal a method to overcome this congestion by combining structurally sensitive spectroscopy with robust normal mode ensemble analysis.

Lipids Alter Rhodopsin Function via Ligand-like and Solvent-like Interactions.

Rhodopsin, a prototypical G protein-coupled receptor, is a membrane protein that can sense dim light. This highly effective photoreceptor is known to be sensitive to the composition of its lipidic environment, but the molecular mechanisms underlying this fine-tuned modulation of the receptor's function and structural stability are not fully understood. There are two competing hypotheses to explain how this occurs: 1) lipid modulation occurs via solvent-like interactions, where lipid composition controls membrane properties like hydrophobic thickness, which in turn modulate the protein's conformational equilibrium; or 2) protein-lipid interactions are ligand-like, with specific hot spots and long-lived binding events. By analyzing an ensemble of all-atom molecular dynamics simulations of five different states of rhodopsin, we show that a local ordering effect takes place in the membrane upon receptor activation. Likewise, docosahexaenoic acid acyl tails and phosphatidylethanolamine headgroups behave like weak ligands, preferentially binding to the receptor in inactive-like conformations and inducing subtle but significant structural changes.

Selectivity and Mechanism of Fengycin, an Antimicrobial Lipopeptide, from Molecular Dynamics.

Fengycin is a cyclic lipopeptide used as an agricultural fungicide. It is synthesized by Bacillus subtilis as an immune response against fungal infection and functions by damaging the target's cell membrane. Previous molecular dynamics simulations and experiments have led to the hypothesis that the aggregation of fengycins on the membrane surface plays a key role in cell disruption. Here, we used microsecond-scale all-atom molecular dynamics simulations to understand the specificity, selectivity, and structure of fengycin oligomers. Our simulations suggest that fengycin is more likely to form stable oligomers in model fungal membranes (phosphatidylcholine) compared to the model bacterial membranes (phosphatidylethanolamine:phosphatidylglycerol). Furthermore, we characterize the differences in the structure and kinetics of the membrane-bound aggregates and discuss their functional implications.

Minimal Nucleation State of α-Synuclein Is Stabilized by Dynamic Threonine-Water Networks.

The first structures of α-synuclein (αSyn) fibrils have recently been solved. Here, we use a unique combination of molecular dynamics simulation strategies to address the minimal nucleation size of the 11-amino acid NAC protofibril solved by X-ray and to interrogate the dynamic behavior of unexpected crystal waters in the steric zipper. We found that protofibrils of >8 chains are thermodynamically stabilized due to protection of the fibril core from solvent influx and ordering of the end strands by the fibril core. In these stable oligomers, water molecules resolved in the crystal structure freely exchange with bulk solvent but are, on average, stably coordinated along the ß-sheet by inward-facing Thr72 and Thr75. We confirm the persistence of this water coordination via simulations of the full-length Greek-key structure solved by NMR and speculate that these Thr-water networks are important in the context of enhanced fibril nucleation in the familial A53T mutation.

Retinal Conformation Changes Rhodopsin's Dynamic Ensemble.

G protein-coupled receptors are vital membrane proteins that allosterically transduce biomolecular signals across the cell membrane. However, the process by which ligand binding induces protein conformation changes is not well understood biophysically. Rhodopsin, the mammalian dim-light receptor, is a unique test case for understanding these processes because of its switch-like activity; the ligand, retinal, is bound throughout the activation cycle, switching from inverse agonist to agonist after absorbing a photon. By contrast, the ligand-free opsin is outside the activation cycle and may behave differently. We find that retinal influences rhodopsin dynamics using an ensemble of all-atom molecular dynamics simulations that in aggregate contain 100 µs of sampling. Active retinal destabilizes the inactive state of the receptor, whereas the active ensemble was more structurally homogenous. By contrast, simulations of an active-like receptor without retinal present were much more heterogeneous than those containing retinal. These results suggest allosteric processes are more complicated than a ligand inducing protein conformational changes or simply capturing a shifted ensemble as outlined in classic models of allostery.

Lightweight object oriented structure analysis: tools for building tools to analyze molecular dynamics simulations.

LOOS (Lightweight Object Oriented Structure-analysis) is a C++ library designed to facilitate making novel tools for analyzing molecular dynamics simulations by abstracting out the repetitive tasks, allowing developers to focus on the scientifically relevant part of the problem. LOOS supports input using the native file formats of most common biomolecular simulation packages, including CHARMM, NAMD, Amber, Tinker, and Gromacs. A dynamic atom selection language based on the C expression syntax is included and is easily accessible to the tool-writer. In addition, LOOS is bundled with over 140 prebuilt tools, including suites of tools for analyzing simulation convergence, three-dimensional histograms, and elastic network models. Through modern C++ design, LOOS is both simple to develop with (requiring knowledge of only four core classes and a few utility functions) and is easily extensible. A python interface to the core classes is also provided, further facilitating tool development.

Structure-based simulations reveal concerted dynamics of GPCR activation.

G protein-coupled receptors (GPCRs) are a vital class of proteins that transduce biological signals across the cell membrane. However, their allosteric activation mechanism is not fully understood; crystal structures of active and inactive receptors have been reported, but the functional pathway between these two states remains elusive. Here, we use structure-based (Go-like) models to simulate activation of two GPCRs, rhodopsin and the ß2 adrenergic receptor (ß2AR). We used data-derived reaction coordinates that capture the activation mechanism for both proteins, showing that activation proceeds through quantitatively different paths in the two systems. Both reaction coordinates are determined from the dominant concerted motions in the simulations so the technique is broadly applicable. There were two surprising results. First, the main structural changes in the simulations were distributed throughout the transmembrane bundle, and not localized to the obvious areas of interest, such as the intracellular portion of Helix 6. Second, the activation (and deactivation) paths were distinctly nonmonotonic, populating states that were not simply interpolations between the inactive and active structures. These transitions also suggest a functional explanation for ß2AR's basal activity: it can proceed through a more broadly defined path during the observed transitions.

Retinal ligand mobility explains internal hydration and reconciles active rhodopsin structures.

Rhodopsin, the mammalian dim-light receptor, is one of the best-characterized G-protein-coupled receptors, a pharmaceutically important class of membrane proteins that has garnered a great deal of attention because of the recent availability of structural information. Yet the mechanism of rhodopsin activation is not fully understood. Here, we use microsecond-scale all-atom molecular dynamics simulations, validated by solid-state (2)H nuclear magnetic resonance spectroscopy, to understand the transition between the dark and metarhodopsin I (Meta I) states. Our analysis of these simulations reveals striking differences in ligand flexibility between the two states. Retinal is much more dynamic in Meta I, adopting an elongated conformation similar to that seen in the recent activelike crystal structures. Surprisingly, this elongation corresponds to both a dramatic influx of bulk water into the hydrophobic core of the protein and a concerted transition in the highly conserved Trp265(6.48) residue. In addition, enhanced ligand flexibility upon light activation provides an explanation for the different retinal orientations observed in X-ray crystal structures of active rhodopsin.

Simulating the mechanism of antimicrobial lipopeptides with all-atom molecular dynamics.

The emergence of antibiotic resistant pathogens is one of the major medical concerns of the 21st century, prompting renewed interest in the development of novel antimicrobial compounds. Here we use microsecond-scale all-atom molecular dynamics simulations to characterize the structure, dynamics, and membrane-binding mechanism of a synthetic antimicrobial lipopeptide, C16-KGGK. Our simulations suggest that these lipopeptides prefer to aggregate in solution and alter the intrinsic order of the lipid bilayer upon binding. From these results and previous coarse-grained simulations, we have developed a simple model for the binding and insertion process for these lipopeptides.

Elastic Network Models are Robust to Variations in Formalism.

Understanding the functions of biomolecules requires insight not only from structures, but from dynamics as well. Often, the most interesting processes occur on time scales too slow for exploration by conventional molecular dynamics (MD) simulations. For this reason, alternative computational methods such as elastic network models (ENMs) have become increasingly popular. These simple, coarse-grained models represent molecules as beads connected by harmonic springs; the system's motions are solved analytically by normal mode analysis. In the past few years, many different formalisms for performing ENM calculations have emerged, and several have been optimized using all-atom MD simulations. In contrast to other studies, we have compared the various formalisms in a systematic, quantitative way. In this study, we optimize many ENM functional forms using a uniform dataset containing only long (> 1 µs) all-atom MD simulations. Our results show that all models once optimized produce spring constants for immediate neighboring residues that are orders of magnitude stiffer than more distal contacts. In addition, the statistical significance of ENM performance varied with model resolution. We also show that fitting long trajectories does not improve ENM performance due to a problem inherent in all network models tested: they underestimate the relative importance of the most concerted motions. Finally, we characterize ENMs' resilience by tessellating the parameter space to show that broad ranges of parameters produce similar quality predictions. Taken together our data reveals that choice of spring function and parameters are not vital to performance of a network model and that simple parameters can by derived "by hand" when no data is available for fitting, thus illustrating the robustness of these models.

Characterization of a potent antimicrobial lipopeptide via coarse-grained molecular dynamics.

The prevalence of antibiotic-resistant pathogens is a major medical concern, prompting increased interest in the development of novel antimicrobial compounds. One such set of naturally occurring compounds, known as antimicrobial peptides (AMPs), have broad-spectrum activity, but come with many limitations for clinical use. Recent work has resulted in a set of antimicrobial lipopeptides (AMLPs) with micromolar minimum inhibitory concentrations and excellent selectivity for bacterial membranes. To characterize a potent, synthetic lipopeptide, C16-KGGK, we used multi-microsecond coarse-grained simulations with the MARTINI forcefield, with a total simulation time of nearly 46µs. These simulations show rapid binding of C16-KGGK, which forms micelles in solution, to model bacterial lipid bilayers. Furthermore, upon binding to the surface of the bilayer, these lipopeptides alter the local lipid organization by recruiting negatively charged POPG lipids to the site of binding. It is likely that this drastic reorganization of the bilayer has major effects on bilayer dynamics and cellular processes that depend on specific bilayer compositions. By contrast, the simulations revealed no association between the lipopeptides and model mammalian bilayers. These simulations provide biophysical insights into lipopeptide selectivity and suggest a possible mechanism for antimicrobial action. This article is part of a Special Issue entitled: Membrane protein structure and function.

Membrane binding of an acyl-lactoferricin B antimicrobial peptide from solid-state NMR experiments and molecular dynamics simulations.

One approach to the growing health problem of antibiotic resistant bacteria is the development of antimicrobial peptides (AMPs) as alternative treatments. The mechanism by which these AMPs selectively attack the bacterial membrane is not well understood, but is believed to depend on differences in membrane lipid composition. N-acylation of the small amidated hexapeptide, RRWQWR-NH(2) (LfB6), derived from the 25 amino acid bovine lactoferricin (LfB25) can be an effective means to improve its antimicrobial properties. Here, we investigate the interactions of C6-LfB6, N-acylated with a 6 carbon fatty acid, with model lipid bilayers with two distinct compositions: 3:1 POPE:POPG (negatively charged) and POPC (zwitterionic). Results from solid-state (2)H and (31)P NMR experiments are compared with those from an ensemble of all-atom molecular dynamic simulations running in aggregate more than 8.6ms. (2)H NMR spectra reveal no change in the lipid acyl chain order when C6-LfB6 is bound to the negatively charged membrane and only a slight decrease in order when it is bound to the zwitterionic membrane. (31)P NMR spectra show no significant perturbation of the phosphate head groups of either lipid system in the presence of C6-LfB6. Molecular dynamic simulations show that for the negatively charged membrane, the peptide's arginines drive the initial association with the membrane, followed by attachment of the tryptophans at the membrane-water interface, and finally by the insertion of the C6 tails deep into the bilayer. In contrast, the C6 tail leads the association with the zwitterionic membrane, with the tryptophans and arginines associating with the membrane-water interface in roughly the same amount of time. We find similar patterns in the order parameters from our simulations. Moreover, we find in the simulations that the C6 tail can insert 1-2Å more deeply into the zwitterionic membrane and can exist in a wider range of angles than in the negatively charged membrane. We propose this is due to the larger area per lipid in the zwitterionic membrane, which provides more space for the C6 to insert and assume different orientations.

Validating and improving elastic network models with molecular dynamics simulations.

Elastic network models (ENMs) are a class of simple models intended to represent the collective motions of proteins. In contrast to all-atom molecular dynamics simulations, the low computational investment required to use an ENM makes them ideal for speculative hypothesis-testing situations. Historically, ENMs have been validated via comparison to crystallographic B-factors, but this comparison is relatively low-resolution and only tests the predictions of relative flexibility. In this work, we systematically validate and optimize a number of ENM-type models by quantitatively comparing their predictions to microsecond-scale all-atom simulations of three different G protein coupled receptors. We show that, despite their apparent simplicity, well-optimized ENMs perform remarkably well, reproducing the protein fluctuations with an accuracy comparable to what one would expect from all-atom simulations run for several hundred nanoseconds.

Block Covariance Overlap Method and Convergence in Molecular Dynamics Simulation.

Molecular dynamics (MD) is a powerful tool for understanding the fluctuations of biomolecular systems. It is, however, subject to statistical errors in its sampling of the underlying distribution of states. One must understand these errors in order to draw meaningful conclusions from the simulation. This is becoming ever more critical as MD simulations of even larger systems are attempted. We present here a new method for determining the extent of convergence that relies on measures of the fluctuation space sampled by the simulation without any a priori knowledge of states or partitioning of the configuration space. This method reveals long correlation times, even for simple systems, and suggests caution when interpreting macromolecular simulations. We also compare this method with previous efforts to characterize the sampling of MD simulation.

A lipid pathway for ligand binding is necessary for a cannabinoid G protein-coupled receptor.

Recent isothiocyanate covalent labeling studies have suggested that a classical cannabinoid, (-)-7'-isothiocyanato-11-hydroxy-1',1'dimethylheptyl-hexahydrocannabinol (AM841), enters the cannabinoid CB2 receptor via the lipid bilayer (Pei, Y., Mercier, R. W., Anday, J. K., Thakur, G. A., Zvonok, A. M., Hurst, D., Reggio, P. H., Janero, D. R., and Makriyannis, A. (2008) Chem. Biol. 15, 1207-1219). However, the sequence of steps involved in such a lipid pathway entry has not yet been elucidated. Here, we test the hypothesis that the endogenous cannabinoid sn-2-arachidonoylglycerol (2-AG) attains access to the CB2 receptor via the lipid bilayer. To this end, we have employed microsecond time scale all-atom molecular dynamics (MD) simulations of the interaction of 2-AG with CB2 via a palmitoyl-oleoyl-phosphatidylcholine lipid bilayer. Results suggest the following: 1) 2-AG first partitions out of bulk lipid at the transmembrane alpha-helix (TMH) 6/7 interface; 2) 2-AG then enters the CB2 receptor binding pocket by passing between TMH6 and TMH7; 3) the entrance of the 2-AG headgroup into the CB2 binding pocket is sufficient to trigger breaking of the intracellular TMH3/6 ionic lock and the movement of the TMH6 intracellular end away from TMH3; and 4) subsequent to protonation at D3.49/D6.30, further 2-AG entry into the ligand binding pocket results in both a W6.48 toggle switch change and a large influx of water. To our knowledge, this is the first demonstration via unbiased molecular dynamics that a ligand can access the binding pocket of a class A G protein-coupled receptor via the lipid bilayer and the first demonstration via molecular dynamics of G protein-coupled receptor activation triggered by a ligand binding event.

Concerted interconversion between ionic lock substates of the beta(2) adrenergic receptor revealed by microsecond timescale molecular dynamics.

The recently solved crystallographic structures for the A(2A) adenosine receptor and the beta(1) and beta(2) adrenergic receptors have shown important differences between members of the class-A G-protein-coupled receptors and their archetypal model, rhodopsin, such as the apparent breaking of the ionic lock that stabilizes the inactive structure. Here, we characterize a 1.02 mus all-atom simulation of an apo-beta(2) adrenergic receptor that is missing the third intracellular loop to better understand the inactive structure. Although we find that the structure is remarkably rigid, there is a rapid influx of water into the core of the protein, as well as a slight expansion of the molecule relative to the crystal structure. In contrast to the x-ray crystal structures, the ionic lock rapidly reforms, although we see an activation-precursor-like event wherein the ionic lock opens for approximately 200 ns, accompanied by movements in the transmembrane helices associated with activation. When the lock reforms, we see the structure return to its inactive conformation. We also find that the ionic lock exists in three states: closed (or locked), semi-open with a bridging water molecule, and open. The interconversion of these states involves the concerted motion of the entire protein. We characterize these states and the concerted motion underlying their interconversion. These findings may help elucidate the connection between key local events and the associated global structural changes during activation.

LOOS: an extensible platform for the structural analysis of simulations.

We have developed LOOS (Lightweight Object-Oriented Structure-analysis library) as an object-oriented library designed to facilitate the rapid development of tools for the structural analysis of simulations. LOOS supports the native file formats of most common simulation packages including AMBER, CHARMM, CNS, Gromacs, NAMD, Tinker, and X-PLOR. Encapsulation and polymorphism are used to simultaneously provide a stable interface to the programmer and make LOOS easily extensible. A rich atom selection language based on the C expression syntax is included as part of the library. LOOS enables students and casual programmer-scientists to rapidly write their own analytical tools in a compact and expressive manner resembling scripting. LOOS is written in C++ and makes extensive use of the Standard Template Library and Boost, and is freely available under the GNU General Public License (version 3) LOOS has been tested on Linux and MacOS X, but is written to be portable and should work on most Unix-based platforms.