Understanding the free-energy landscape of phase separation in lipid bilayers using molecular dynamics.

Liquid-liquid phase separation inside the cell often results in biological condensates that can critically affect cell homeostasis. Such phase separation events occur in multiple parts of cells, including the cell membranes, where the "lipid raft" hypothesis posits the formation of ordered domains floating in a sea of disordered lipids. The resulting lipid domains often have functional roles. However, the thermodynamics of lipid phase separation and their resulting mechanistic effects on cell function and dysfunction are poorly understood. Understanding such complex phenomena in cell membranes, with their diverse lipid compositions, is exceptionally difficult. For these reasons, simple model systems that can recapitulate similar behavior are widely used to study this phenomenon. Despite these simplifications, the timescale and length scales of domain formation pose a challenge for molecular dynamics (MD) simulations. Thus, most MD studies focus on spontaneous lipid phase separation-essentially measuring the sign (but not the amplitude) of the free-energy change upon separation-rather than directly interrogating the thermodynamics. Here, we propose a proof-of-concept pipeline that can directly measure this free energy by combining coarse-grained MD with enhanced sampling protocols using a novel collective variable. This approach will be a useful tool to help connect the thermodynamics of phase separation with the mechanistic insights already available from MD simulations.

Surveying nonvisual arrestins reveals allosteric interactions between functional sites.

Arrestins are important scaffolding proteins that are expressed in all vertebrate animals. They regulate cell-signaling events upon binding to active G-protein coupled receptors (GPCR) and trigger endocytosis of active GPCRs. While many of the functional sites on arrestins have been characterized, the question of how these sites interact is unanswered. We used anisotropic network modeling (ANM) together with our covariance compliment techniques to survey all the available structures of the nonvisual arrestins to map how structural changes and protein-binding affect their structural dynamics. We found that activation and clathrin binding have a marked effect on arrestin dynamics, and that these dynamics changes are localized to a small number of distant functional sites. These sites include α-helix 1, the lariat loop, nuclear localization domain, and the C-domain ß-sheets on the C-loop side. Our techniques suggest that clathrin binding and/or GPCR activation of arrestin perturb the dynamics of these sites independent of structural changes.

Effects of cholesterol on the mechanism of fengycin, a biofungicide.

Fengycins are a class of antifungal lipopeptides synthesized by the bacteria Bacillus subtilis, commercially available as the primary component of the agricultural fungicide Serenade. They are toxic to fungi but far less to mammalian cells. One key difference between mammalian and fungal cell membranes is the presence of cholesterol only in the former; recent experimental work showed that the presence of cholesterol reduces fengycin-induced membrane leakage. Since our previous all-atom and coarse-grained simulations suggested that aggregation of membrane-bound fengycin is central to its ability to disrupt membranes, we hypothesized that cholesterol might reduce fengycin aggregation. Here, we test this hypothesis using coarse-grained molecular dynamics simulations, with sampling enhanced via the weighted ensemble method. The results indicate that cholesterol subtly alters the size distribution for fengycin aggregates, limits the lateral range of their membrane disordering, and reduces the ability of aggregates to bend the membrane. Taken together, these phenomena may account for cholesterol's effects on fengycin activity.

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.

Phosphorylation-mediated structural changes within the SOAR domain of stromal interaction molecule 1 enable specific activation of distinct Orai channels.

Low-conductance, highly calcium-selective channels formed by the Orai proteins exist as store-operated CRAC channels and store-independent, arachidonic acid-activated ARC channels. Both are activated by stromal interaction molecule 1 (STIM1), but CRAC channels are activated by STIM1 located in the endoplasmic reticulum membrane, whereas ARC channels are activated by the minor plasma membrane-associated pool of STIM1. Critically, maximally activated CRAC channel and ARC channel currents are completely additive within the same cell, and their selective activation results in their ability to each induce distinct cellular responses. We have previously shown that specific ARC channel activation requires a PKA-mediated phosphorylation of a single threonine residue (Thr389) within the cytoplasmic region of STIM1. Here, examination of the molecular basis of this phosphorylation-dependent activation revealed that phosphorylation of the Thr389 residue induces a significant structural change in the STIM1-Orai-activating region (SOAR) that interacts with the Orai proteins, and it is this change that determines the selective activation of the store-independent ARC channels versus the store-operated CRAC channels. In conclusion, our findings reveal the structural changes underlying the selective activation of STIM1-induced CRAC or ARC channels that determine the specific stimulation of these two functionally distinct Ca2+ entry pathways.

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.

Thermodynamics of Micelle Formation and Membrane Fusion Modulate Antimicrobial Lipopeptide Activity.

Antimicrobial lipopeptides (AMLPs) are antimicrobial drug candidates that preferentially target microbial membranes. One class of AMLPs, composed of cationic tetrapeptides attached to an acyl chain, have minimal inhibitory concentrations in the micromolar range against a range of bacteria and fungi. Previously, we used coarse-grained molecular dynamics simulations and free energy methods to study the thermodynamics of their interaction with membranes in their monomeric state. Here, we extended the study to the biologically relevant micellar state, using, to our knowledge, a novel reaction coordinate based on hydrophobic contacts. Using umbrella sampling along this reaction coordinate, we identified the critical transition states when micelles insert into membranes. The results indicate that the binding of these AMLP micelles to membranes is thermodynamically favorable, but in contrast to the monomeric case, there are significant free energy barriers. The height of these free energy barriers depends on the membrane composition, suggesting that the AMLPs' ability to selectively target bacterial membranes may be as much kinetic as thermodynamic. This mechanism highlights the importance of considering oligomeric state in solution as criterion when optimizing peptides or lipopeptides as antibiotic leads.

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.

Structural basis of G protein-coupled receptor-Gi protein interaction: formation of the cannabinoid CB2 receptor-Gi protein complex.

In this study, we applied a comprehensive G protein-coupled receptor-Gαi protein chemical cross-linking strategy to map the cannabinoid receptor subtype 2 (CB2)-Gαi interface and then used molecular dynamics simulations to explore the dynamics of complex formation. Three cross-link sites were identified using LC-MS/MS and electrospray ionization-MS/MS as follows: 1) a sulfhydryl cross-link between C3.53(134) in TMH3 and the Gαi C-terminal i-3 residue Cys-351; 2) a lysine cross-link between K6.35(245) in TMH6 and the Gαi C-terminal i-5 residue, Lys-349; and 3) a lysine cross-link between K5.64(215) in TMH5 and the Gαi α4ß6 loop residue, Lys-317. To investigate the dynamics and nature of the conformational changes involved in CB2·Gi complex formation, we carried out microsecond-time scale molecular dynamics simulations of the CB2 R*·Gαi1ß1γ2 complex embedded in a 1-palmitoyl-2-oleoyl-phosphatidylcholine bilayer, using cross-linking information as validation. Our results show that although molecular dynamics simulations started with the G protein orientation in the ß2-AR*·Gαsß1γ2 complex crystal structure, the Gαi1ß1γ2 protein reoriented itself within 300 ns. Two major changes occurred as follows. 1) The Gαi1 α5 helix tilt changed due to the outward movement of TMH5 in CB2 R*. 2) A 25° clockwise rotation of Gαi1ß1γ2 underneath CB2 R* occurred, with rotation ceasing when Pro-139 (IC-2 loop) anchors in a hydrophobic pocket on Gαi1 (Val-34, Leu-194, Phe-196, Phe-336, Thr-340, Ile-343, and Ile-344). In this complex, all three experimentally identified cross-links can occur. These findings should be relevant for other class A G protein-coupled receptors that couple to Gi proteins.

Thermodynamics of antimicrobial lipopeptide binding to membranes: origins of affinity and selectivity.

The development of novel antibiotic drugs is one of the most pressing biomedical problems due to the increasing number of antibiotic-resistant pathogens. Antimicrobial peptides and lipopeptides are a promising category of candidates, but the molecular origins of their antimembrane activity is unclear. Here we explore a series of recently developed antimicrobial lipopeptides, using coarse-grained molecular-dynamics simulations and free energy methods to uncover the thermodynamics governing their binding to membranes. Specifically, we quantify C16-KGGK's binding affinity to the two types of membrane by umbrella sampling. We also examined the origin of C16-KGGK's selectivity for bacterial versus mammalian membranes by systematically varying the peptide sequence and salt concentration. Our data showed that the C16 hydrophobic tail is the main contributor to its affinity to lipid membrane, whereas the peptide portion is mainly responsible for its selectivity. Furthermore, the electrostatic interaction between the cationic peptide and anionic bacterial membrane plays a significant role in the selectivity.

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.

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.

Global fold of human cannabinoid type 2 receptor probed by solid-state 13C-, 15N-MAS NMR and molecular dynamics simulations.

The global fold of human cannabinoid type 2 (CB2 ) receptor in the agonist-bound active state in lipid bilayers was investigated by solid-state (13)C- and (15)N magic-angle spinning (MAS) NMR, in combination with chemical-shift prediction from a structural model of the receptor obtained by microsecond-long molecular dynamics (MD) simulations. Uniformly (13)C- and (15)N-labeled CB2 receptor was expressed in milligram quantities by bacterial fermentation, purified, and functionally reconstituted into liposomes. (13)C MAS NMR spectra were recorded without sensitivity enhancement for direct comparison of Cα, Cß, and C=O bands of superimposed resonances with predictions from protein structures generated by MD. The experimental NMR spectra matched the calculated spectra reasonably well indicating agreement of the global fold of the protein between experiment and simulations. In particular, the (13) C chemical shift distribution of Cα resonances was shown to be very sensitive to both the primary amino acid sequence and the secondary structure of CB2. Thus the shape of the Cα band can be used as an indicator of CB2 global fold. The prediction from MD simulations indicated that upon receptor activation a rather limited number of amino acid residues, mainly located in the extracellular Loop 2 and the second half of intracellular Loop 3, change their chemical shifts significantly (≥ 1.5 ppm for carbons and ≥ 5.0 ppm for nitrogens). Simulated two-dimensional (13) Cα(i)-(13)C=O(i) and (13)C=O(i)-(15)NH(i + 1) dipolar-interaction correlation spectra provide guidance for selective amino acid labeling and signal assignment schemes to study the molecular mechanism of activation of CB2 by solid-state MAS NMR.

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.

Coarse-grained molecular dynamics provides insight into the interactions of lipids and cholesterol with rhodopsin.

Protein function is a complicated interplay between structure and dynamics, which can be heavily influenced by environmental factors and conditions. This is particularly true in the case of membrane proteins, such as the visual receptor rhodopsin. It has been well documented that lipid headgroups, polyunsaturated tails, and the concentration of cholesterol in membranes all play a role in the function of rhodopsin. Recently, we used all-atom simulations to demonstrate that different lipid species have preferential interactions and possible binding sites on rhodopsin's surface, consistent with experiment. However, the limited timescales of the simulations meant that the statistical uncertainty of these results was substantial. Accordingly, we present here 32 independent 1.6 µs coarse-grained simulations exploring lipids and cholesterols surrounding rhodopsin and opsin, in lipid bilayers mimicking those found naturally. Our results agree with those found experimentally and in previous simulations, but with far better statistical certainty. The results demonstrate the value of combining all-atom and coarse-grained models with experiment to provide a well-rounded view of lipid-protein interactions.

Interactions between fengycin and model bilayers quantified by coarse-grained molecular dynamics.

Bacteria, particularly of the genus Bacillus, produce a wide variety of antifungal compounds. They act by affecting the lipid bilayers of fungal membranes, causing curvature-induced strain and eventual permeabilization. One class of these, known as fengycins, has been commercialized for treating agricultural infections and shows some promise as a possible antifungal pharmaceutical. Understanding the mechanism by which fengycins damage lipid bilayers could prove useful to the future development of related antifungal treatments. In this work, we present multi-microsecond-long simulations of fengycin interacting with different lipid bilayer systems. We see fengycin aggregation and uncover a clear aggregation pattern that is partially influenced by bilayer composition. We also quantify some local bilayer perturbations caused by fengycin binding, including curvature of the lipid bilayer and local electrostatic-driven reorganization.

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.

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.

The interplay of structure and dynamics: insights from a survey of HIV-1 reverse transcriptase crystal structures.

HIV-1 reverse transcriptase (RT) is a critical drug target for HIV treatment, and understanding the exact mechanisms of its function and inhibition would significantly accelerate the development of new anti-HIV drugs. It is well known that structure plays a critical role in protein function, but for RT, structural information has proven to be insufficient-despite enormous effort-to explain the mechanism of inhibition and drug resistance of non-nucleoside RT inhibitors. We hypothesize that the missing link is dynamics, information about the motions of the system. However, many of the techniques that give the best information about dynamics, such as solution nuclear magnetic resonance and molecular dynamics simulations, cannot be easily applied to a protein as large as RT. As an alternative, we combine elastic network modeling with simultaneous hierarchical clustering of structural and dynamic data. We present an extensive survey of the dynamics of RT bound to a variety of ligands and with a number of mutations, revealing a novel mechanism for drug resistance to non-nucleoside RT inhibitors. Hydrophobic core mutations restore active-state motion to multiple functionally significant regions of HIV-1 RT. This model arises out of a combination of structural and dynamic information, rather than exclusively from one or the other.