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Liquid-liquid phase separation (LLPS) inside the cell often results in biological condensates that can critically impact cell homeostasis. Such phase separation events occur in multiple parts of cells, including the cell membranes, where the so-called “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 phenomenon in cell membranes, with their diverse lipid compositions, is exceptionally difficult. For this reasons, simple model systems that can recapitulate similar behavior are widely used to study this phenomenon. Despite these simplifications, the timescale and 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 molecular dynamics simulations.SIGNIFICANCEStandard molecular dynamics simulations can determine the sign the free energy change upon phase separation, but not the amplitude. We present a new method to determine the phase separation free energy for lipid membranes, based on a enhanced sampling using the weighted ensemble method combined with a novel collective variable, validated using coarse-grained simulations applied to several simple systems. The new method will be valuable as a way to develop models that connect molecular-level structural features to the thermodynamics of phase separation.

S-nitrosothiols exert multiple effects on neural processes in the central and peripheral nervous system. This study shows that intravenous infusion of S-nitroso-L-cysteine (SNO-L-CYS, 1 μmol/kg/min) in anesthetized male Sprague Dawley rats elicits (a) sustained increases in minute ventilation, via increases in frequency of breathing and tidal volume, (b) a decrease in Alveolar-arterial (A-a) gradient, thus improving alveolar gas-exchange, (c) concomitant changes in arterial blood-gas chemistry, such as an increase in pO

1.AbstractArrestins 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 modelling (ANM) together with our covariance compliment techniques to survey all of the available structures of the non-visual 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 β-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.

Software is ubiquitous in modern science - almost any project, in almost any discipline, requires some code to work. However, many (or even most) scientists are not programmers, and must rely on programs written and maintained by others. A crucial but often neglected part of a scientist's training is learning how to use new tools, and how to exist as part of a community of users. This article will discuss key behaviors that can make the experience quicker, more efficient, and more pleasant for the user and developer alike.

We determined whether intravenous injections of the membrane-permeable ventilatory stimulants, D-cysteine ethyl ester (ethyl (2 S)- 2-amino-3-sulfanylpropanoate) (D-CYSee) and D-cystine dimethyl ester (methyl (2 S)- 2-amino-3-[[(2 S)- 2-amino-3-methoxy-3-oxopropyl]disulfanyl] propanoate) (D-CYSdime), could overcome the deleterious actions of intravenous morphine on arterial blood pH, pCO

Software is ubiquitous in modern science — almost any project, in almost any discipline, requires some code to work. However, many (or even most) scientists are not program- mers, and must rely on programs written and maintained by others. A crucial but often neglected part of a scientist’s training is learning how to use new tools, and how to exist as part of a community of users. This article will discuss key behaviors that can make the experience quicker, more efficient, and more pleasant for the user and developer alike.

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. (1) Since our previous all-atom and coarse-grained simulations (2, 3) 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 affects on fengycin activity.

C. elegans react to metabolic distress caused by mismatches in oxygen and energy status via distinct behavioral responses. At the molecular level, these responses are coordinated by under-characterized, redox-sensitive processes, thought to initiate in mitochondria. Complex I of the electron transport chain is a major site of reactive oxygen species (ROS) production and is canonically associated with oxidative damage following hypoxic exposure. Here, we use a combination of optogenetics and CRISPR/Cas9-mediated genome editing to exert spatiotemporal control over ROS production. We demonstrate a photo-locomotory remodeling of avoidance behavior by local ROS production due to the reversible oxidation of a single thiol on the complex I subunit NDUF-2.1. Reversible thiol oxidation at this site is necessary and sufficient for the behavioral response to hypoxia, does not respond to ROS produced at more distal sites, and protects against lethal hypoxic exposure. Molecular modeling suggests that oxidation at this thiol residue alters the ability for NDUF-2.1 to coordinate electron transfer to coenzyme Q by destabilizing the Q-binding pocket, causing decreased complex I activity. Overall, site-specific ROS production regulates behavioral responses and these findings provide a mechanistic target to suppress the detrimental effects of hypoxia.

We have identified thiolesters that reverse the negative effects of opioids on breathing without compromising analgesia. Here we report the effects of D-cystine diethyl ester (D-cystine diEE) or D-cystine dimethyl ester (D-cystine diME) on morphine-induced changes in ventilation, arterial-blood gas chemistry, A-a gradient (index of gas-exchange in the lungs) and analgesia in freely moving rats. Injection of morphine (10 mg/kg, IV) elicited negative effects on breathing (e.g., depression of tidal volume, minute ventilation, peak inspiratory flow, and inspiratory drive). Subsequent injection of D-cystine diEE (500 mmol/kg, IV) elicited an immediate and sustained reversal of these effects of morphine. Injection of morphine (10 mg/kg, IV) also elicited pronounced decreases in arterial blood pH, pO2 and sO2 accompanied by pronounced increases in pCO2 (all indicative of a decrease in ventilatory drive) and A-a gradient (mismatch in ventilation-perfusion in the lungs). These effects of morphine were reversed in an immediate and sustained fashion by D-cystine diME (500 mmol/kg, IV). Finally, the duration of morphine (5 and 10 mg/kg, IV) analgesia was augmented by D-cystine diEE. D-cystine diEE and D-cystine diME may be clinically useful agents that can effectively reverse the negative effects of morphine on breathing and gas-exchange in the lungs while promoting analgesia.

We use massive averaging over the thermally populated energy landscape to calculate a realistic terahertz vibrational density of states (VDOS), isotropic absorption and anisotropic absorption for the protein chicken egg white lysozyme (CEWL). We find that the VDOS shows little variation with starting structure, however both the isotropic and anisotropic absorption vary considerably with starting structure. Averaging over the population leads to a smooth featureless average isotropic spectrum, in agreement with THz absorption measurements however resonant bands emerge for the anisotropic averaging. Further we find the vibrational ensemble in fact has frequency dependent features associated with large overlap with functional displacements.

Proteins are large complex biomolecules which have structural vibrations in the terahertz range. The vibrational spectrum is dependent on the protein structure, which fluctuates at biological temperatures. Recently it was shown that these fluctuations can be accounted for by massive sampling of the energy landscape to calculate the terahertz isotropic and anisotropic absorbance. The large number of vibrations contributing to the spectra however makes interpretation of resonant bands challenging. Here we examine how we can apply elastic network models to define fundamental vibrational displacements to analyze these massive data sets.

There is an urgent need to understand the intracellular mechanisms by which synthetic opioids, such as fentanyl, depress breathing. We used L-NAME (N(G)-nitro-L-arginine methyl ester), a nitric oxide synthase (NOS) inhibitor, to provide evidence for a role of nitric oxide (NO) and nitrosyl factors, including S-nitrosothiols, in fentanyl-induced suppression of breathing in rats. We measured breathing parameters using unrestrained plethysmography to record the changes produced by bolus administration of fentanyl (25 μg/kg, IV) in male Sprague Dawley rats that were pretreated with vehicle (saline), L-NAME (50 μmol/kg, IV) or the inactive D-isomer, D-NAME (50 μmol/kg, IV), 15 min previously. L-NAME produced a series of ventilatory changes that included (i) sustained elevations in breathing frequency, due to the reductions in the durations of inspiration and expiration, (ii) sustained elevations in minute ventilation, accompanied by minimal changes in tidal volume, and (iii) increases in inspiratory drive and expiratory drive, and peak inspiratory flow and peak expiratory flow. Subsequent administration of fentanyl in rats pretreated with vehicle produced negative effects on breathing, including decreases in frequency, tidal volume and therefore minute ventilation. Fentanyl elicited markedly different responses in rats that were pretreated with L-NAME, and conclusively, the negative effects of fentanyl were augmented by the NOS inhibitor. D-NAME did not alter ventilatory parameters or modulate the effects of fentanyl on breathing. Our study fully characterized the effects of L-NAME on ventilation in rats and is the first to suggest a potential role of nitrosyl factors in the ventilatory responses to fentanyl. Our data shows that nitrosyl factors reduce the expression of fentanyl-induced changes in ventilation.

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.

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 β-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.

The quantitative assessment of uncertainty and sampling quality is essential in molecular simulation. Many systems of interest are highly complex, often at the edge of current computational capabilities. Modelers must therefore analyze and communicate statistical uncertainties so that “consumers” of simulated data understand its significance and limitations. This article covers key analyses appropriate for trajectory data generated by conventional simulation methods such as molecular dynamics and (single Markov chain) Monte Carlo. It also provides guidance for analyzing some ‘enhanced’ sampling approaches. We do not discuss systematic errors arising, e.g., from inaccuracy in the chosen model or force field.

This study describes a comparison between melts and simulated stabilities of the same RNAs that could be used to benchmark RNA force fields, and potentially to determine future melt-ing experiments. Using umbrella sampling molecular simulations of three 12-nucleotide RNA hairpin stem loops, for which there are experimentally determined free energies of unfold-ing, we projected unfolding onto the reaction coordinate of end to end (5′ to 3′ hydroxyl oxygen) distance. We estimate the free energy change of the transition from the native con-formation to a fully extended conformation—the stretched state—with no hydrogen bonds between non-neighboring bases. Each simulation was performed four times using the AM-BER FF99+bsc0+χOL3 force field and each window, spaced at 1 Å intervals, was sampled for 1 μs, for a total of 552 μs of simulation. We compared differences in the simulated free energy changes to analogous differences in free energies from optical melting experiments using ther-modynamic cycles where the free energy change between stretched and random coil sequences is assumed to be sequence independent. The differences between experimental and simulated ΔΔG° are on average 1.00 ± 0.66 kcal/mol, which is chemically accurate and suggests analo-gous simulations could be used predictively. We also report a novel method to identify where replica free energies diverge along the reaction coordinate, thus indicating where additional sampling would most improve convergence. We conclude by discussing methods to more economically perform such simulations.

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.

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.

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 α4β6 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*·Gαi1β1γ2 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 β2-AR*·Gαsβ1γ2 complex crystal structure, the Gαi1β1γ2 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 Gαi1β1γ2 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.

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 (Gō-like) models to simulate activation of two GPCRs, rhodopsin and the β₂ adrenergic receptor (β₂AR). 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 β₂AR's basal activity: it can proceed through a more broadly defined path during the observed transitions.

The pre-mRNA splicing factor SF3b1 exhibits recurrent mutations among hematologic malignancies and cancers, and consequently is a major therapeutic target of clinically-advanced spliceosome inhibitors. In this review, we highlight and rigorously analyze emerging views of SF3b1 conformational transitions, including the human SF3b particle either in isolation or bound to spliceosome inhibitors, and human or yeast spliceosome assemblies. Among spliceosome states characterized to date, an SF3b1 α-helical superhelix significantly closes to surround a U2 small nuclear RNA duplex with the pre-mRNA branch point sequence. The SF3b1 torus is locally unwound at an active site adenosine, whereas protein cofactors appear to stabilize overall closure in the spliceosome. Network analyses demonstrates that the natural SF3b1 dynamics mimic its conformational change in the spliceosome, raising the possibility of conformational selection underpinning spliceosome assembly. These dynamic SF3b1 conformations have consequences for gatekeeping of spliceosome assembly and therapeutic targeting of its cancer-associated dysfunction.

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.

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.