G Protein-Coupled Receptors Self-Assemble in Dynamics Simulations of Model Bilayers

Nanoporous Membranes of Densely Packed Carbon Nanotubes Formed by Lipid-Mediated Self-Assembly

Nanofiltration technology faces the competing challenges of achieving high fluid flux through uniformly narrow pores of a mechanically and chemically stable filter. Supported dense-packed 2D-crystals of single-walled carbon nanotube (CNT) porins with ∼1 nm wide pores could, in principle, meet these challenges. However, such CNT membranes cannot currently be synthesized at high pore density. Here, we use computer simulations to explore lipid-mediated self-assembly as a route toward densely packed CNT membranes, motivated by the analogy to membrane-protein 2D crystallization. In large-scale coarse-grained molecular dynamics (MD) simulations, we find that CNTs in lipid membranes readily self-assemble into large clusters. Lipids trapped between the CNTs lubricate CNT repacking upon collisions of diffusing clusters, thereby facilitating the formation of large ordered structures. Cluster diffusion follows the Saffman-Delbrück law and its generalization by Hughes, Pailthorpe, and White. On longer time scales, we expect the formation of close-packed CNT structures by depletion of the intervening shared annular lipid shell, depending on the relative strength of CNT-CNT and CNT-lipid interactions. Our simulations identify CNT length, diameter, and end functionalization as major factors for the self-assembly of CNT membranes.

Improved Protein Dynamics and Hydration in the Martini3 Coarse-Grain Model

The Martini coarse-grain force-field has emerged as an important framework to probe cellular processes at experimentally relevant time- and length-scales. However, the recently developed version, the Martini3 force-field with the implemented Go̅ model (Martini3Go̅), as well as previous variants of the Martini model have not been benchmarked and rigorously tested for globular proteins. In this study, we consider three globular proteins, ubiquitin, lysozyme, and cofilin, and compare protein dynamics and hydration with observables from experiments and all-atom simulations. We show that the Martini3Go̅ model is able to accurately model the structural and dynamic features of small globular proteins. Overall, the structural integrity of the proteins is maintained, as validated by contact maps, radii of gyration (Rg), and SAXS profiles. The chemical shifts predicted from the ensemble sampled in the simulations are consistent with the experimental data. Further, a good match is observed in the protein-water interaction energetics, and the hydration levels of the residues are similar to atomistic simulations. However, the protein-water interaction dynamics is not accurately represented and appears to depend on the protein structural complexity, residue specificity, and water dynamics. Our work is a step toward testing and assessing the Martini3Go̅ model and provides insights into future efforts to refine Martini models with improved solvation effects and better correspondence to the underlying all-atom systems.

Molecular Dynamics Simulations in Protein-Protein Docking

Concerted interactions between all the cell components form the basis of biological processes. Protein-protein interactions (PPIs) constitute a tremendous part of this interaction network. Deeper insight into PPIs can help us better understand numerous diseases and lead to the development of new diagnostic and therapeutic strategies. PPI interfaces, until recently, were considered undruggable. However, it is now believed that the interfaces contain "hot spots," which could be targeted by small molecules. Such a strategy would require high-quality structural data of PPIs, which are difficult to obtain experimentally. Therefore, in silico modeling can complement or be an alternative to in vitro approaches. There are several computational methods for analyzing the structural data of the binding partners and modeling of the protein-protein dimer/oligomer structure. The major problem with in silico structure prediction of protein assemblies is obtaining sufficient sampling of protein dynamics. One of the methods that can take protein flexibility and the effects of the environment into account is Molecular Dynamics (MD). While sampling of the whole protein-protein association process with plain MD would be computationally expensive, there are several strategies to harness the method to PPI studies while maintaining reasonable use of resources. This chapter reviews known applications of MD in the PPI investigation workflows.

Computational Methods to Target Protein-Protein Interactions

The chapter emphasizes the importance of understanding protein-protein interactions in cellular mechanisms and highlights the role of computational modeling in predicting these interactions. It discusses sequence-based approaches such as evolutionary trace (ET), correlated mutation analysis (CMA), and subtractive correlated mutation (SCM) for identifying crucial amino acid residues, considering interface conservation or evolutionary changes. The chapter also explores methods like differential ET, hidden-site class model, and spatial cluster detection (SCD) for interface specificity and spatial clustering. Furthermore, it examines approaches combining structural and sequential methodologies and evaluates modeled predictions through initiatives like critical assessment of prediction of interactions (CAPRI). Additionally, the chapter provides an overview of various software programs used for molecular docking, detailing their search, sampling, refinement and scoring stages, along with innovative techniques and tools like normal mode analysis (NMA) and adaptive Poisson-Boltzmann solver (APBS) for electrostatic calculations. These computational and experimental approaches are crucial for unraveling protein-protein interactions and aid in developing potential therapeutics for various diseases.

Molecular Biophysics of Class A G Protein Coupled Receptors-Lipids Interactome at a Glance-Highlights from the A2A Adenosine Receptor

G protein-coupled receptors (GPCRs) are embedded in phospholipid membrane bilayers with cholesterol representing 34% of the total lipid content in mammalian plasma membranes. Membrane lipids interact with GPCRs structures and modulate their function and drug-stimulated signaling through conformational selection. It has been shown that anionic phospholipids form strong interactions between positively charged residues in the G protein and the TM5-TM6-TM 7 cytoplasmic interface of class A GPCRs stabilizing the signaling GPCR-G complex. Cholesterol with a high content in plasma membranes can be identified in more specific sites in the transmembrane region of GPCRs, such as the Cholesterol Consensus Motif (CCM) and Cholesterol Recognition Amino Acid Consensus (CRAC) motifs and other receptor dependent and receptor state dependent sites. Experimental biophysical methods, atomistic (AA) MD simulations and coarse-grained (CG) molecular dynamics simulations have been applied to investigate these interactions. We emphasized here the impact of phosphatidyl inositol-4,5-bisphosphate (PtdIns(4,5)P₂ or PIP₂), a minor phospholipid component and of cholesterol on the function-related conformational equilibria of the human A_2A adenosine receptor (A_2AR), a representative receptor in class A GPCR. Several GPCRs of class A interacted with PIP₂ and cholesterol and in many cases the mechanism of the modulation of their function remains unknown. This review provides a helpful comprehensive overview for biophysics that enter the field of GPCRs-lipid systems.

Physiological changes in bilayer thickness induced by cholesterol control GPCR rhodopsin function

We monitored the effect on function of the G-protein-coupled receptor (GPCR) rhodopsin from small, stepwise changes in bilayer thickness induced by cholesterol. Over a range of phosphatidylcholine bilayers with hydrophobic thickness from ≈21 Å to 38 Å, the metarhodopsin-I (MI)/metarhodopsin-II (MII) equilibrium was monitored with UV-visible spectroscopy while ordering of hydrocarbon chains was probed by 2H-NMR. Addition of cholesterol shifted equilibrium toward MII for bilayers thinner than the average length of hydrophobic transmembrane helices (27 Å) and to MI for thicker bilayers, while small bilayer thickness changes within the range of the protein hydrophobic thickness drastically up- or downregulated MII formation. The cholesterol-induced shifts toward MII for thinner membranes correlated with the cholesterol-induced increase of bilayer hydrophobic thickness measured by NMR, consistent with continuum elastic modeling. The energetic penalty of adding cholesterol to thick bilayers caused rhodopsin oligomerization and a shift toward MI. In membranes of physiological thickness, changes in bilayer mechanical properties induced by cholesterol potentiated the interplay between bilayer and protein thickness resulting in large swings of the MI-MII equilibrium. In membrane containing cholesterol, elastic deformations near the protein are a dominant energetic contribution to the functional equilibrium of the model GPCR rhodopsin.

Rhodopsin, light-sensor of vision

The light sensor of vertebrate scotopic (low-light) vision, rhodopsin, is a G-protein-coupled receptor comprising a polypeptide chain with bound chromophore, 11-cis-retinal, that exhibits remarkable physicochemical properties. This photopigment is extremely stable in the dark, yet its chromophore isomerises upon photon absorption with 70% efficiency, enabling the activation of its G-protein, transducin, with high efficiency. Rhodopsin's photochemical and biochemical activities occur over very different time-scales: the energy of retinaldehyde's excited state is stored in <1 ps in retinal-protein interactions, but it takes milliseconds for the catalytically active state to form, and many tens of minutes for the resting state to be restored. In this review, we describe the properties of rhodopsin and its role in rod phototransduction. We first introduce rhodopsin's gross structural features, its evolution, and the basic mechanisms of its activation. We then discuss light absorption and spectral sensitivity, photoreceptor electrical responses that result from the activity of individual rhodopsin molecules, and recovery of rhodopsin and the visual system from intense bleaching exposures. We then provide a detailed examination of rhodopsin's molecular structure and function, first in its dark state, and then in the active Meta states that govern its interactions with transducin, rhodopsin kinase and arrestin. While it is clear that rhodopsin's molecular properties are exquisitely honed for phototransduction, from starlight to dawn/dusk intensity levels, our understanding of how its molecular interactions determine the properties of scotopic vision remains incomplete. We describe potential future directions of research, and outline several major problems that remain to be solved.

Ion-bridges and lipids drive aggregation of same-charge nanoparticles on lipid membranes

The control of the aggregation of biomedical nanoparticles (NP) in physiological conditions is crucial as clustering may change completely the way they interact with the biological environment. Here we show that Au nanoparticles, functionalized by an anionic, amphiphilic shell, spontaneously aggregate in fluid zwitterionic lipid bilayers. We use molecular dynamics and enhanced sampling techniques to disentangle the short-range and long-range driving forces of aggregation. At short inter-particle distances, ion-mediated, charge-charge interactions (ion bridging) stabilize the formation of large NP aggregates, as confirmed by cryo-electron microscopy. Lipid depletion and membrane curvature are the main membrane deformations driving long-range NP-NP attraction. Ion bridging, lipid depletion, and membrane curvature stem from the configurational flexibility of the nanoparticle shell. Our simulations show, more in general, that the aggregation of same-charge membrane inclusions can be expected as a result of intrinsically nanoscale effects taking place at the NP-NP and NP-bilayer soft interfaces.

Modulation of adenosine A2a receptor oligomerization by receptor activation and PIP2 interactions

GPCRs have been shown to form oligomers, which generate distinctive signaling outcomes. However, the structural nature of the oligomerization process remains uncertain. We have characterized oligomeric configurations of the adenosine A2a receptor (A2aR) by combining large-scale molecular dynamics simulations with Markov state models. These oligomeric structures may also serve as templates for studying oligomerization of other class A GPCRs. Our simulation data revealed that receptor activation results in enhanced oligomerization, more diverse oligomer populations, and a more connected oligomerization network. The active state conformation of the A2aR shifts protein-protein association interfaces to those involving intracellular loop ICL3 and transmembrane helix TM6. Binding of PIP₂ to A2aR stabilizes protein-protein interactions via PIP₂-mediated association interfaces. These results indicate that A2aR oligomerization is responsive to the local membrane lipid environment. This, in turn, suggests a modulatory effect on A2aR whereby a given oligomerization profile favors the dynamic formation of specific supramolecular signaling complexes.

Genetic, cellular, and structural characterization of the membrane potential-dependent cell-penetrating peptide translocation pore

Cell-penetrating peptides (CPPs) allow intracellular delivery of bioactive cargo molecules. The mechanisms allowing CPPs to enter cells are ill-defined. Using a CRISPR/Cas9-based screening, we discovered that KCNQ5, KCNN4, and KCNK5 potassium channels positively modulate cationic CPP direct translocation into cells by decreasing the transmembrane potential (V_m). These findings provide the first unbiased genetic validation of the role of V_m in CPP translocation in cells. In silico modeling and live cell experiments indicate that CPPs, by bringing positive charges on the outer surface of the plasma membrane, decrease the V_m to very low values (–150 mV or less), a situation we have coined megapolarization that then triggers formation of water pores used by CPPs to enter cells. Megapolarization lowers the free energy barrier associated with CPP membrane translocation. Using dyes of varying dimensions in CPP co-entry experiments, the diameter of the water pores in living cells was estimated to be 2 (–5) nm, in accordance with the structural characteristics of the pores predicted by in silico modeling. Pharmacological manipulation to lower transmembrane potential boosted CPP cellular internalization in zebrafish and mouse models. Besides identifying the first proteins that regulate CPP translocation, this work characterized key mechanistic steps used by CPPs to cross cellular membranes. This opens the ground for strategies aimed at improving the ability of cells to capture CPP-linked cargos in vitro and in vivo.

Before a drug can have its desired effect, it must reach its target tissue or organ, and enter its cells. This is not easy because cells are surrounded by the plasma membrane, a fat-based barrier that separates the cell from its external environment. The plasma membrane contains proteins that act as channels, shuttling specific molecules in and out of the cell, and it also holds charge, with its inside surface being more negatively charged than its outside surface.

Cell-penetrating peptides are short sequences of amino acids (the building blocks that form proteins) that carry positive charges. These positive charges allow them to cross the membrane easily, but it is not well understood how.

To find out how cell-penetrating peptides cross the membrane, Trofimenko et al. attached them to dyes of different sizes. This revealed that the cell-penetrating peptides enter the cell through temporary holes called water pores, which measure about two nanometres across. The water pores form when the membrane becomes ‘megapolarized’, this is, when the difference in charge between the inside and the outside of the membrane becomes greater than normal. This can happen when the negative charge on the inside surface or the positive charge on the outer surface of the membrane increase. Megapolarization depends on potassium channels, which transport positive potassium ions outside the cell, making the outside of the membrane positive. When cell-penetrating peptides arrive at the outer surface of the cell near potassium channels, they make it even more positive. This increases the charge difference between the inside and the outside of the cell, allowing water pores to form. Once the peptides pass through the pores, the charge difference between the inside and the outside of the cell membrane dissipates, and the pores collapse.

Drug developers are experimenting with attaching cell-penetrating peptides to drugs to help them get inside their target cells. Currently there are several experimental medications of this kind in clinical trials. Understanding how these peptides gain entry, and what size of molecule they could carry with them, provides solid ground for further drug development.

Aggregation of Lysozyme in the Presence of a Mixed Bilayer of POPC and POPG

Understanding the molecular mechanisms by which amyloidogenic proteins interact with membranes is a challenging task. Amyloid accumulates from many human diseases have been observed to contain membrane lipids. In this work, coarse-grained molecular dynamics simulations have been used to inspect hen egg white lysozyme (HEWL) aggregation and membrane association in the presence of a pure POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) bilayer and a POPC and POPG (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylglycerol) mixed bilayer. It was observed that, in both cases, two HEWLs formed aggregates. In the presence of a mixed bilayer, after aggregation, the aggregated system started to interact with the membrane. It has been found that one of the lysozymes which came closer to the mixed bilayer unfolded more. The process of the initial insertion of an aggregated system in the mixed bilayer has been analyzed. The structural rearrangements of the protein and lipids were analyzed as well along the course of the simulation. Although with a pure POPC bilayer, aggregation was observed, the aggregated system moved away from the membrane. We believe that our study will provide considerable insights into lysozyme aggregation in the presence of a membrane environment.

Assessing the Role of Lipids in the Molecular Mechanism of Membrane Proteins

Membrane proteins have evolved to work optimally within the complex environment of the biological membrane. Consequently, interactions with surrounding lipids are part of their molecular mechanism. Yet, the identification of lipid-protein interactions and the assessment of their molecular role is an experimental challenge. Recently, biophysical approaches have emerged that are compatible with the study of membrane proteins in an environment closer to the biological membrane. These novel approaches revealed specific mechanisms of regulation of membrane protein function. Lipids have been shown to play a role in oligomerization, conformational transitions or allosteric coupling. In this review, we summarize the recent biophysical approaches, or combination thereof, that allow to decipher the role of lipid-protein interactions in the mechanism of membrane proteins.

Synthesis, Characterization, and Simulation of Four-Armed Megamolecules

This paper describes the synthesis, characterization, and modeling of a series of molecules having four protein domains attached to a central core. The molecules were assembled with the "megamolecule" strategy, wherein enzymes react with their covalent inhibitors that are substituted on a linker. Three linkers were synthesized, where each had four oligo(ethylene glycol)-based arms terminated in a para-nitrophenyl phosphonate group that is a covalent inhibitor for cutinase. This enzyme is a serine hydrolase and reacts efficiently with the phosphonate to give a new ester linkage at the Ser-120 residue in the active site of the enzyme. Negative-stain transmission electron microscopy (TEM) images confirmed the architecture of the four-armed megamolecules. These cutinase tetramers were also characterized by X-ray crystallography, which confirmed the active-site serine-phosphonate linkage by electron-density maps. Molecular dynamics simulations of the tetracutinase megamolecules using three different force field setups were performed and compared with the TEM observations. Using the Amberff99SB-disp + pH7 force field, the two-dimensional projection distances of the megamolecules were found to agree with the measured dimensions from TEM. The study described here, which combines high-resolution characterization with molecular dynamics simulations, will lead to a comprehensive understanding of the molecular structures and dynamics for this new class of molecules.

Addressing the Excessive Aggregation of Membrane Proteins in the MARTINI Model

The MARTINI model is a widely used coarse-grained force field popular for its capacity to represent a diverse array of complex biomolecules. However, efforts to simulate increasingly realistic models of membranes, involving complex lipid mixtures and multiple proteins, suggest that membrane protein aggregates are overstabilized by the MARTINI v2.2 force field. In this study, we address this shortcoming of the MARTINI model. We determined the free energy of dimerization of four transmembrane protein systems using the nonpolarizable MARTINI model. Comparison with experimental FRET-based estimates of the dimerization free energy was used to quantify the significant overstabilization of each protein homodimer studied. To improve the agreement between simulation and experiment, a single uniform scaling factor, α, was used to enhance the protein-lipid Lennard-Jones interaction. A value of α = 1.04-1.045 was found to provide the best fit to the dimerization free energies for the proteins studied while maintaining the specificity of contacts at the dimer interface. To further validate the modified force field, we performed a multiprotein simulation using both MARTINI v2.2 and the reparameterized MARTINI model. While the original MARTINI model predicts oligomerization of protein into a single aggregate, the reparameterized MARTINI model maintains a dynamic equilibrium between monomers and dimers as predicted by experimental studies. The proposed reparameterization is an alternative to the standard MARTINI model for use in simulations of realistic models of a biological membrane containing diverse lipids and proteins.

Kinetics of self-assembly of inclusions due to lipid membrane thickness interactions

Self-assembly of proteins on lipid membranes underlies many important processes in cell biology, such as, exo- and endo-cytosis, assembly of viruses, etc. An attractive force that can cause self-assembly is mediated by membrane thickness interactions between proteins. The free energy profile associated with this attractive force is a result of the overlap of thickness deformation fields around the proteins which can be calculated from the solution of a boundary value problem. Yet, the time scales over which two inclusions coalesce has not been explored, even though the evolution of particle concentrations on membranes has been modeled using phase-field approaches. In this paper we compute this time scale as a function of the initial distance between two inclusions by viewing their coalescence as a first passage time problem. The mean first passage time is computed using Langevin dynamics and a partial differential equation, and both methods are found to be in excellent agreement. Inclusions of three different shapes are studied and it is found that for two inclusions separated by about hundred nanometers the time to coalescence is hundreds of milliseconds irrespective of shape. An efficient computation of the interaction energy of inclusions is central to our work. We compute it using a finite difference technique and show that our results are in excellent agreement with those from a previously proposed semi-analytical method based on Fourier-Bessel series. The computational strategies described in this paper could potentially lead to efficient methods to explore the kinetics of self-assembly of proteins on lipid membranes.

Effect of palmitoylation on the dimer formation of the human dopamine transporter

The human dopamine transporter (hDAT) is one in three members of the monoamine transporter family (MAT). hDAT is essential for regulating the dopamine concentration in the synaptic cleft through dopamine reuptake into the presynaptic neuron; thereby controlling hDAT dopamine signaling. Dysfunction of the transporter is linked to several psychiatric disorders. hDAT and the other MATs have been shown to form oligomers in the plasma membrane, but only limited data exists on which dimeric and higher order oligomeric states are accessible and energetically favorable. In this work, we present several probable dimer conformations using computational coarse-grained self-assembly simulations and assess the relative stability of the different dimer conformations using umbrella sampling replica exchange molecular dynamics. Overall, the dimer conformations primarily involve TM9 and/or TM11 and/or TM12 at the interface. Furthermore, we show that a palmitoyl group (palm) attached to hDAT on TM12 modifies the free energy of separation for interfaces involving TM12, suggesting that S-palmitoylation may change the relative abundance of dimers involving TM12 in a biological context. Finally, a comparison of the identified interfaces of hDAT and palmitoylated hDAT to the human serotonin transporter interfaces and the leucine transporter interface, suggests similar dimer conformations across these protein family.

Supramolecular organization of rhodopsin in rod photoreceptor cell membranes

Rhodopsin is the light receptor in rod photoreceptor cells that initiates scotopic vision. Studies on the light receptor span well over a century, yet questions about the organization of rhodopsin within the photoreceptor cell membrane still persist and a consensus view on the topic is still elusive. Rhodopsin has been intensely studied for quite some time, and there is a wealth of information to draw from to formulate an organizational picture of the receptor in native membranes. Early experimental evidence in apparent support for a monomeric arrangement of rhodopsin in rod photoreceptor cell membranes is contrasted and reconciled with more recent visual evidence in support of a supramolecular organization of rhodopsin. What is known so far about the determinants of forming a supramolecular structure and possible functional roles for such an organization are also discussed. Many details are still missing on the structural and functional properties of the supramolecular organization of rhodopsin in rod photoreceptor cell membranes. The emerging picture presented here can serve as a springboard towards a more in-depth understanding of the topic.

Differential FSH Glycosylation Modulates FSHR Oligomerization and Subsequent cAMP Signaling

Follicle-stimulating hormone (FSH) and its target G protein-coupled receptor (FSHR) are essential for reproduction. Recent studies have established that the hypo-glycosylated pituitary FSH glycoform (FSH21/18), is more bioactive in vitro and in vivo than the fully-glycosylated variant (FSH24). FSH21/18 predominates in women of reproductive prime and FSH24 in peri-post-menopausal women, suggesting distinct functional roles of these FSH glycoforms. The aim of this study was to determine if differential FSH glycosylation modulated FSHR oligomerization and resulting impact on cAMP signaling. Using a modified super-resolution imaging technique (PD-PALM) to assess FSHR complexes in HEK293 cells expressing FSHR, we observed time and concentration-dependent modulation of FSHR oligomerization by FSH glycoforms. High eFSH and FSH21/18 concentrations rapidly dissociated FSHR oligomers into monomers, whereas FSH24 displayed slower kinetics. The FSHR β-arrestin biased agonist, truncated eLHβ (Δ121-149) combined with asparagine56-deglycosylated eLHα (dg-eLHt), increased FSHR homomerization. In contrast, low FSH21/18 and FSH24 concentrations promoted FSHR association into oligomers. Dissociation of FSHR oligomers correlated with time points where higher cAMP production was observed. Taken together, these data suggest that FSH glycosylation may modulate the kinetics and amplitude of cAMP production, in part, by forming distinct FSHR complexes, highlighting potential avenues for novel therapeutic targeting of the FSHR to improve IVF outcomes.

Structure and Dynamics of GPCRs in Lipid Membranes: Physical Principles and Experimental Approaches

Over the past decade, the vast amount of information generated through structural and biophysical studies of GPCRs has provided unprecedented mechanistic insight into the complex signalling behaviour of these receptors. With this recent information surge, it has also become increasingly apparent that in order to reproduce the various effects that lipids and membranes exert on the biological function for these allosteric receptors, in vitro studies of GPCRs need to be conducted under conditions that adequately approximate the native lipid bilayer environment. In the first part of this review, we assess some of the more general effects that a membrane environment exerts on lipid bilayer-embedded proteins such as GPCRs. This is then followed by the consideration of more specific effects, including stoichiometric interactions with specific lipid subtypes. In the final section, we survey a range of different membrane mimetics that are currently used for in vitro studies, with a focus on NMR applications.

Evidence for the Supramolecular Organization of a Bacterial Outer-Membrane Protein from In Vivo Pulse Electron Paramagnetic Resonance Spectroscopy

In the outer membrane of Gram-negative bacteria, membrane proteins are thought to be organized into domains or islands that play a role in the segregation, movement, and turnover of membrane components. However, there is presently limited information on the structure of these domains or the molecular interactions that mediate domain formation. In the present work, the Escherichia coli outer membrane vitamin B₁₂ transporter, BtuB, was spin-labeled, and double electron-electron resonance was used to measure the distances between proteins in intact cells. These data together with Monte Carlo simulations provide evidence for the presence of specific intermolecular contacts between BtuB monomers that could drive the formation of string-like oligomers. Moreover, the EPR data provide evidence for the location of the interacting interfaces and indicate that lipopolysaccharide mediates the contacts between BtuB monomers.

Cholesterol-mediated oligomerization pathways of serotonin G-coupled receptor 5-HT2C

Serotonin (5-HT) receptors have been shown to homodimerize and heterodimerize with other G protein-coupled receptors (GPCRs), although the details of this process have not yet been elucidated. Here we use coarse-grained molecular dynamics on monomeric 5-HT2C receptors to predict the transmembrane (TM) helices involved in such associations. All these simulations were carried out both in 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipid bilayers and in mixed composition POPC-Cholesterol ones, to show whether the presence of cholesterol could directly influence and drive the dimeric association. The goal is to get insights on the self-assembly pathway leading to GPCRs 5-HT2C oligomerization, which is supposed to be the basis of its constitutional activity. From the analysis of the molecular dynamics trajectories, we observed the formation of 5-HT2C oligomers through self-assembly and we identified the main domains involved in the receptor dimerization. In particular, dimers and oligomers from the two different environments show TM4-TM5 and TM1-TM7-H8 as the preferential dimerization interfaces. Nevertheless, substantial differences arise for oligomers in POPC and in POPC-Chol membranes: in POPC-Chol the variability of dimers interfaces is strictly limited to the TM1-TM7-H8 and TM4-TM5 interfaces and the dimorphism depends on cholesterol that directly participates in its formation. These results are in agreement with both experimental evidences and other computational studies conducted on other GPCRs oligomerization.

Size-dependent aggregation of hydrophobic nanoparticles in lipid membranes

The aggregation of nanoparticles affects their reactivity, transport across biological membranes, uptake into cells, toxicity, and fate in the environment. In the case of membrane-embedded, hydrophobic nanoparticles the relationship between size and aggregation pattern is not well understood. Here, we explore this relationship for the case of spherically symmetrical nanoparticles using the MARTINI coarse-grained force field. We find that the free energy of dimerization depends strongly on nanoparticle size: the smallest molecules (mimicking C60 fullerene) aggregate only weakly, the largest ones form large three-dimensional aggregates causing major deformations in the host membrane, and the intermediate-sized particles show a tendency to form linear aggregates. Suppressing membrane undulations reduces very significantly aggregation, and substantially abolishes linear aggregation, suggesting a relationship between membrane curvature and aggregation geometry. At low concentration, when placed on membranes of variable curvature, the intermediate size nanoparticles move rapidly to high curvature regions - suggesting that they can sense membrane curvature. At high concentration, the same nanoparticles induce massive membrane deformations, without affecting the mechanical stability of the membrane - suggesting that they can generate membrane curvature.

Capturing Choline-Aromatics Cation-π Interactions in the MARTINI Force Field

Cation−π interactions play an important role in biomolecular recognition, including interactions between membrane phosphatidylcholine lipids and aromatic amino acids of peripheral proteins. While molecular mechanics coarse grain (CG) force fields are particularly well suited to simulate membrane proteins in general, they are not parameterized to explicitly reproduce cation−π interactions. We here propose a modification of the polarizable MARTINI coarse grain (CG) model enabling it to model membrane binding events of peripheral proteins whose aromatic amino acid interactions with choline headgroups are crucial for their membrane binding. For this purpose, we first collected and curated a dataset of eight peripheral proteins from different families. We find that the MARTINI CG model expectedly underestimates aromatics–choline interactions and is unable to reproduce membrane binding of the peripheral proteins in our dataset. Adjustments of the relevant interactions in the polarizable MARTINI force field yield significant improvements in the observed binding events. The orientation of each membrane-bound protein is comparable to reference data from all-atom simulations and experimental binding data. We also use negative controls to ensure that choline–aromatics interactions are not overestimated. We finally check that membrane properties, transmembrane proteins, and membrane translocation potential of mean force (PMF) of aromatic amino acid side-chain analogues are not affected by the new parameter set. This new version “MARTINI 2.3P” is a significant improvement over its predecessors and is suitable for modeling membrane proteins including peripheral membrane binding of peptides and proteins.

Membrane lipids are both the substrates and a mechanistically responsive environment of TMEM16 scramblase proteins

Recent discoveries about functional mechanisms of proteins in the TMEM16 family of phospholipid scramblases have illuminated the dual role of the membrane as both the substrate and a mechanistically responsive environment in the wide range of physiological processes and genetic disorders in which they are implicated. This is highlighted in the review of recent findings from our collaborative investigations of molecular mechanisms of TMEM16 scramblases that emerged from iterative functional, structural, and computational experimentation. In the context of this review, we present new MD simulations and trajectory analyses motivated by the fact that new structural information about the TMEM16 scramblases is emerging from cryo-EM determinations in lipid nanodiscs. Because the functional environment of these proteins in in vivo and in in vitro is closer to flat membranes, we studied comparatively the responses of the membrane to the TMEM16 proteins in flat membranes and nanodiscs. We find that bilayer shapes in the nanodiscs are very different from those observed in the flat membrane systems, but the function-related slanting of the membrane observed at the nhTMEM16 boundary with the protein is similar in the nanodiscs and in the flat bilayers. This changes, however, in the bilayer composed of longer-tail lipids, which is thicker near the phospholipid translocation pathway, which may reflect an enhanced tendency of the long tails to penetrate the pathway and create, as shown previously, a nonconductive environment. These findings support the correspondence between the mechanistic involvement of the lipid environment in the flat membranes, and the nanodiscs. © 2019 Wiley Periodicals, Inc.

Prediction and targeting of GPCR oligomer interfaces

GPCR oligomerization has emerged as a hot topic in the GPCR field in the last years. Receptors that are part of these oligomers can influence each other's function, although it is not yet entirely understood how these interactions work. The existence of such a highly complex network of interactions between GPCRs generates the possibility of alternative targets for new therapeutic approaches. However, challenges still exist in the characterization of these complexes, especially at the interface level. Different experimental approaches, such as FRET or BRET, are usually combined to study GPCR oligomer interactions. Computational methods have been applied as a useful tool for retrieving information from GPCR sequences and the few X-ray-resolved oligomeric structures that are accessible, as well as for predicting new and trustworthy GPCR oligomeric interfaces. Machine-learning (ML) approaches have recently helped with some hindrances of other methods. By joining and evaluating multiple structure-, sequence- and co-evolution-based features on the same algorithm, it is possible to dilute the issues of particular structures and residues that arise from the experimental methodology into all-encompassing algorithms capable of accurately predict GPCR-GPCR interfaces. All these methods used as a single or a combined approach provide useful information about GPCR oligomerization and its role in GPCR function and dynamics. Altogether, we present experimental, computational and machine-learning methods used to study oligomers interfaces, as well as strategies that have been used to target these dynamic complexes.

Allosteric pathway selection in templated assembly

Assembling large numbers of molecular building blocks into functional nanostructures is no trivial task. It relies on guiding building blocks through complex energy landscapes shaped by synergistic and antagonistic supramolecular interactions. In nature, the use of molecular templates is a potent strategy to navigate the process to the desired structure with high fidelity. Yet, nature's templating strategy remains to be fully exploited in man-made nanomaterials. Designing effective template-guided self-assembling systems can only be realized through precise insight into how the chemical design of building blocks and the resulting balance of repulsive and attractive forces give rise to pathway selection and suppression of trapped states. We develop a minimal model to unravel the kinetic pathways and pathway selection of the templated assembly of molecular building blocks on a template. We show how allosteric activation of the associative interactions can suppress undesired solution-aggregation pathways and gives rise to a true template-assembly path.

Quantum Mechanical and Molecular Mechanics Modeling of Membrane-Embedded Rhodopsins

Computational chemistry provides versatile methods for studying the properties and functioning of biological systems at different levels of precision and at different time scales. The aim of this article is to review the computational methodologies that are applicable to rhodopsins as archetypes for photoactive membrane proteins that are of great importance both in nature and in modern technologies. For each class of computational techniques, from methods that use quantum mechanics for simulating rhodopsin photophysics to less-accurate coarse-grained methodologies used for long-scale protein dynamics, we consider possible applications and the main directions for improvement.

Rhodopsin Oligomerization and Aggregation

Rhodopsin is the light receptor in photoreceptor cells of the retina and a prototypical G protein-coupled receptor. Two types of quaternary structures can be adopted by rhodopsin. If rhodopsin folds and attains a proper tertiary structure, it can then form oligomers and nanodomains within the photoreceptor cell membrane. In contrast, if rhodopsin misfolds, it cannot progress through the biosynthetic pathway and instead will form aggregates that can cause retinal degenerative disease. In this review, emerging views are highlighted on the supramolecular organization of rhodopsin within the membrane of photoreceptor cells and the aggregation of rhodopsin that can lead to retinal degeneration.

Supramolecular organization of membrane proteins with anisotropic hydrophobic thickness

Experiments have revealed that membrane proteins often self-assemble into locally ordered clusters. Such membrane protein lattices can play key roles in the functional organization of cell membranes. Membrane protein organization can be driven, at least in part, by bilayer-mediated elastic interactions between membrane proteins. For membrane proteins with anisotropic hydrophobic thickness, bilayer-mediated protein interactions are inherently directional. Here we establish general relations between anisotropy in membrane protein hydrophobic thickness and supramolecular membrane protein organization. We show that protein symmetry is distinctively reflected in the energy landscape of bilayer-mediated protein interactions, favoring characteristic lattice architectures of membrane protein clusters. We find that, in the presence of thermal fluctuations, anisotropy in protein hydrophobic thickness can induce membrane proteins to form mesh-like structures dividing the membrane into compartments. Our results help to elucidate the physical principles and mechanisms underlying the functional organization of cell membranes.

Computational Modeling of Realistic Cell Membranes

Cell membranes contain a large variety of lipid types and are crowded with proteins, endowing them with the plasticity needed to fulfill their key roles in cell functioning. The compositional complexity of cellular membranes gives rise to a heterogeneous lateral organization, which is still poorly understood. Computational models, in particular molecular dynamics simulations and related techniques, have provided important insight into the organizational principles of cell membranes over the past decades. Now, we are witnessing a transition from simulations of simpler membrane models to multicomponent systems, culminating in realistic models of an increasing variety of cell types and organelles. Here, we review the state of the art in the field of realistic membrane simulations and discuss the current limitations and challenges ahead.

Characterization of Lipid-Protein Interactions and Lipid-Mediated Modulation of Membrane Protein Function through Molecular Simulation

The cellular membrane constitutes one of the most fundamental compartments of a living cell, where key processes such as selective transport of material and exchange of information between the cell and its environment are mediated by proteins that are closely associated with the membrane. The heterogeneity of lipid composition of biological membranes and the effect of lipid molecules on the structure, dynamics, and function of membrane proteins are now widely recognized. Characterization of these functionally important lipid-protein interactions with experimental techniques is however still prohibitively challenging. Molecular dynamics (MD) simulations offer a powerful complementary approach with sufficient temporal and spatial resolutions to gain atomic-level structural information and energetics on lipid-protein interactions. In this review, we aim to provide a broad survey of MD simulations focusing on exploring lipid-protein interactions and characterizing lipid-modulated protein structure and dynamics that have been successful in providing novel insight into the mechanism of membrane protein function.

Does the Lipid Bilayer Orchestrate Access and Binding of Ligands to Transmembrane Orthosteric/Allosteric Sites of G Protein-Coupled Receptors?

The ligand-binding sites of many G protein-coupled receptors (GPCRs) are situated around and deeply embedded within the central pocket formed by their seven transmembrane-spanning α-helical domains. Generally, these binding sites are assumed accessible to endogenous ligands from the aqueous phase. Recent advances in the structural biology of GPCRs, along with biophysical and computational studies, suggest that amphiphilic and lipophilic molecules may gain access to these receptors by first partitioning into the membrane and then reaching the binding site via lateral diffusion through the lipid bilayer. In addition, several crystal structures of class A and class B GPCRs bound to their ligands offer unprecedented details on the existence of lipid-facing allosteric binding sites outside the transmembrane helices that can only be reached via lipid pathways. The highly organized structure of the lipid bilayer may direct lipophilic or amphiphilic drugs to a specific depth within the bilayer, changing local concentration of the drug near the binding site and affecting its binding kinetics. Additionally, the constraints of the lipid bilayer, including its composition and biophysical properties, may play a critical role in "pre-organizing" ligand molecules in an optimal orientation and conformation to facilitate receptor binding. Despite its clear involvement in molecular recognition processes, the critical role of the membrane in binding ligands to lipid-exposed transmembrane binding sites remains poorly understood and warrants comprehensive investigation. Understanding the mechanistic basis of the structure-membrane interaction relationship of drugs will not only provide useful insights about receptor binding kinetics but will also enhance our ability to take advantage of the apparent membrane contributions when designing drugs that target transmembrane proteins with improved efficacy and safety. In this minireview, we summarize recent structural and computational studies on membrane contributions to binding processes, elucidating both lipid pathways of ligand access and binding mechanisms for several orthosteric and allosteric ligands of class A and class B GPCRs.

Emerging Diversity in Lipid-Protein Interactions

Membrane lipids interact with proteins in a variety of ways, ranging from providing a stable membrane environment for proteins to being embedded in to detailed roles in complicated and well-regulated protein functions. Experimental and computational advances are converging in a rapidly expanding research area of lipid–protein interactions. Experimentally, the database of high-resolution membrane protein structures is growing, as are capabilities to identify the complex lipid composition of different membranes, to probe the challenging time and length scales of lipid–protein interactions, and to link lipid–protein interactions to protein function in a variety of proteins. Computationally, more accurate membrane models and more powerful computers now enable a detailed look at lipid–protein interactions and increasing overlap with experimental observations for validation and joint interpretation of simulation and experiment. Here we review papers that use computational approaches to study detailed lipid–protein interactions, together with brief experimental and physiological contexts, aiming at comprehensive coverage of simulation papers in the last five years. Overall, a complex picture of lipid–protein interactions emerges, through a range of mechanisms including modulation of the physical properties of the lipid environment, detailed chemical interactions between lipids and proteins, and key functional roles of very specific lipids binding to well-defined binding sites on proteins. Computationally, despite important limitations, molecular dynamics simulations with current computer power and theoretical models are now in an excellent position to answer detailed questions about lipid–protein interactions.

State-dependent Lipid Interactions with the A2a Receptor Revealed by MD Simulations Using In Vivo-Mimetic Membranes

Membranes are known to have modulatory effects on G protein-coupled receptors (GPCRs) via specific lipid interactions. However, the mechanisms of such modulations in physiological conditions and how they influence GPCR functions remain unclear. Here we report coarse-grained molecular dynamics simulations on the Adenosine A2a receptor in different conformational states embedded in an in vivo-mimetic membrane model. Nine lipid interaction sites were revealed. The strength of lipid interactions with these sites showed a degree of dependence on the conformational states of the receptor, suggesting that these lipids may regulate the conformational dynamics of the receptor. In particular, we revealed a dual role of PIP₂ on A2aR activation that involves both stabilization of the characteristic outward tilt of TM6 and enhancement of A2aR-mini-Gs association. Our results demonstrated that the bound lipids allosterically regulate the functional properties of GPCRs. These protein-lipid interactions provide a springboard for design of allosteric modulators of GPCRs.

An Isoprene Lipid-Binding Protein Promotes Eukaryotic Coenzyme Q Biosynthesis

The biosynthesis of coenzyme Q presents a paradigm for how cells surmount hydrophobic barriers in lipid biology. In eukaryotes, CoQ precursors-among nature's most hydrophobic molecules-must somehow be presented to a series of enzymes peripherally associated with the mitochondrial inner membrane. Here, we reveal that this process relies on custom lipid-binding properties of COQ9. We show that COQ9 repurposes the bacterial TetR fold to bind aromatic isoprenes with high specificity, including CoQ intermediates that likely reside entirely within the bilayer. We reveal a process by which COQ9 associates with cardiolipin-rich membranes and warps the membrane surface to access this cargo. Finally, we identify a molecular interface between COQ9 and the hydroxylase COQ7, motivating a model whereby COQ9 presents intermediates directly to CoQ enzymes. Overall, our results provide a mechanism for how a lipid-binding protein might access, select, and deliver specific cargo from a membrane to promote biosynthesis.

A Practical View of the Martini Force Field

Martini is a coarse-grained (CG) force field suitable for molecular dynamics (MD) simulations of (bio)molecular systems. It is based on mapping of two to four heavy atoms to one CG particle. The effective interactions between the CG particles are parametrized to reproduce partitioning free energies of small chemical compounds between polar and apolar phases. In this chapter, a summary of the key elements of this CG force field is presented, followed by an example of practical application: a lipoplex-membrane fusion experiment. Formulated as hands-on practice, this chapter contains guidelines to build CG models of important biological systems, such as asymmetric bilayers and double-stranded DNA. Finally, a series of notes containing useful information, limitations, and tips are described in the last section.

Graph-Based Approach to Systematic Molecular Coarse-Graining

A novel methodology is introduced here to generate coarse-grained (CG) representations of molecular models for simulations. The proposed strategy relies on basic graph-theoretic principles and is referred to as graph-based coarse-graining (GBCG). It treats a given system as a molecular graph and derives a corresponding CG representation by using edge contractions to combine nodes in the graph, which correspond to atoms in the molecule, into CG sites. A key element of this methodology is that the nodes are combined according to well-defined protocols that rank-order nodes based on the underlying chemical connectivity. By iteratively performing these operations, successively coarser representations of the original atomic system can be produced to yield a systematic set of CG mappings with hierarchical resolution in an automated fashion. These capabilities are demonstrated in the context of several test systems, including toluene, pentadecane, a polysaccharide dimer, and a rhodopsin protein. In these examples, GBCG yields multiple, intuitive structures that naturally preserve the chemical topology of the system. Importantly, these representations are rendered from algorithmic implementation rather than an arbitrary ansatz, which, until now, has been the conventional approach for defining CG mapping schemes. Overall, the results presented here indicate that GBCG is efficient, robust, and unambiguous in its application, making it a valuable tool for future CG modeling.

Lipid-Protein Interactions Are Unique Fingerprints for Membrane Proteins

Cell membranes contain hundreds of different proteins and lipids in an asymmetric arrangement. Our current understanding of the detailed organization of cell membranes remains rather elusive, because of the challenge to study fluctuating nanoscale assemblies of lipids and proteins with the required spatiotemporal resolution. Here, we use molecular dynamics simulations to characterize the lipid environment of 10 different membrane proteins. To provide a realistic lipid environment, the proteins are embedded in a model plasma membrane, where more than 60 lipid species are represented, asymmetrically distributed between the leaflets. The simulations detail how each protein modulates its local lipid environment in a unique way, through enrichment or depletion of specific lipid components, resulting in thickness and curvature gradients. Our results provide a molecular glimpse of the complexity of lipid-protein interactions, with potentially far-reaching implications for our understanding of the overall organization of real cell membranes.

Effect of dietary docosahexaenoic acid on rhodopsin content and packing in photoreceptor cell membranes

Docosahexaenoic acid (DHA) is enriched in photoreceptor cell membranes. DHA deficiency impairs vision due to photoreceptor cell dysfunction, which is caused, at least in part, by reduced activity of rhodopsin, the light receptor that initiates phototransduction. It is unclear how the depletion of membrane DHA impacts the structural properties of rhodopsin and, in turn, its activity. Atomic force microscopy (AFM) was used to assess the impact of DHA deficiency on membrane structure and rhodopsin organization. AFM revealed that signaling impairment in photoreceptor cells is independent of the oligomeric status of rhodopsin and causes adaptations in photoreceptor cells where the content and density of rhodopsin in the membrane is increased. Functional and structural changes caused by DHA deficiency were reversible.

Dimer Interface of the Human Serotonin Transporter and Effect of the Membrane Composition

The oligomeric state of membrane proteins has recently emerged in many cases as having an effect on their function. However, the intrinsic dynamics of their spatial organization in cells and model systems makes it challenging to characterize. Here we use molecular dynamics (MD) simulations at multiple resolutions to determine the dimer conformation of the human serotonin transporter (hSERT). From self-assembly simulations we predict dimer candidates and subsequently quantify their relative strength. We use umbrella sampling (US) replica exchange MD simulations for which we present extensive analysis of their efficiency and improved sampling compared to regular US MD simulations. The data shows that the most stable hSERT dimer interface is symmetrical and involves transmembrane helix 12 (TM12), similar to the crystal structure of the bacterial homologue LeuT, but with a slightly different orientation. We also describe the supramolecular organization of hSERT from a 250 μs self-assembly simulation. Finally, the effects of the presence of phosphatidylinositol bisphosphate or cholesterol in the membrane model has been quantified for the TM12-TM12 predicted interface. Collectively, the presented data bring new insight to the area of protein and lipid interplay in biological membranes.

Closely related, yet unique: Distinct homo- and heterodimerization patterns of G protein coupled chemokine receptors and their fine-tuning by cholesterol

Chemokine receptors, a subclass of G protein coupled receptors (GPCRs), play essential roles in the human immune system, they are involved in cancer metastasis as well as in HIV-infection. A plethora of studies show that homo- and heterodimers or even higher order oligomers of the chemokine receptors CXCR4, CCR5, and CCR2 modulate receptor function. In addition, membrane cholesterol affects chemokine receptor activity. However, structural information about homo- and heterodimers formed by chemokine receptors and their interplay with cholesterol is limited. Here, we report homo- and heterodimer configurations of the chemokine receptors CXCR4, CCR5, and CCR2 at atomistic detail, as obtained from thousands of molecular dynamics simulations. The observed homodimerization patterns were similar for the closely related CC chemokine receptors, yet they differed significantly between the CC receptors and CXCR4. Despite their high sequence identity, cholesterol modulated the CC homodimer interfaces in a subtype-specific manner. Chemokine receptor heterodimers display distinct dimerization patterns for CXCR4/CCR5 and CXCR4/CCR2. Furthermore, associations between CXCR4 and CCR5 reveal an increased cholesterol-sensitivity as compared to CXCR4/CCR2 heterodimerization patterns. This work provides a first comprehensive structural overview over the complex interaction network between chemokine receptors and indicates how heterodimerization and the interaction with the membrane environment diversifies the function of closely related GPCRs.

Membrane-Mediated Cooperativity of Proteins

Besides direct protein-protein interactions, indirect interactions mediated by membranes play an important role for the assembly and cooperative function of proteins in membrane shaping and adhesion. The intricate shapes of biological membranes are generated by proteins that locally induce membrane curvature. Indirect curvature-mediated interactions between these proteins arise because the proteins jointly affect the bending energy of the membranes. These curvature-mediated interactions are attractive for crescent-shaped proteins and are a driving force in the assembly of the proteins during membrane tubulation. Membrane adhesion results from the binding of receptor and ligand proteins that are anchored in the apposing membranes. The binding of these proteins strongly depends on nanoscale shape fluctuations of the membranes, leading to a fluctuation-mediated binding cooperativity. A length mismatch between receptor-ligand complexes in membrane adhesion zones causes repulsive curvature-mediated interactions that are a driving force for the length-based segregation of proteins during membrane adhesion.