Ensemble molecular dynamics yields submillisecond kinetics and intermediates of membrane fusion

Quantifying Unbiased Conformational Ensembles from Biased Simulations Using ShapeGMM

Quantifying the conformational ensembles of biomolecules is fundamental to describing mechanisms of processes such as protein folding, interconversion between folded states, ligand binding, and allosteric regulation. Accurate quantification of these ensembles remains a challenge for conventional molecular simulations of all but the simplest molecules due to insufficient sampling. Enhanced sampling approaches, such as metadynamics, were designed to overcome this challenge; however, the nonuniform frame weights that result from many of these approaches present an additional challenge to ensemble quantification techniques such as Markov State Modeling or structural clustering. Here, we present rigorous inclusion of nonuniform frame weights into a structural clustering method entitled shapeGMM. The result of frame-weighted shapeGMM is a high dimensional probability density and generative model for the unbiased system from which we can compute important thermodynamic properties such as relative free energies and configurational entropy. The accuracy of this approach is demonstrated by the quantitative agreement between GMMs computed by Hamiltonian reweighting and direct simulation of a coarse-grained helix model system. Furthermore, the relative free energy computed from a shapeGMM probability density of alanine dipeptide reweighted from a metadynamics simulation quantitatively reproduces the underlying free energy in the basins. Finally, the method identifies hidden structures along the actin globular to filamentous-like structural transition from a metadynamics simulation on a linear discriminant analysis coordinate trained on GMM states, illustrating how structural clustering of biased data can lead to biophysical insight. Combined, these results demonstrate that frame-weighted shapeGMM is a powerful approach to quantifying biomolecular ensembles from biased simulations.

Molecular mechanism underlying SNARE-mediated membrane fusion enlightened by all-atom molecular dynamics simulations

The SNAP receptor (SNARE) proteins syntaxin-1, SNAP-25, and synaptobrevin mediate neurotransmitter release by forming tight SNARE complexes that fuse synaptic vesicles with the plasma membranes in microseconds. Membrane fusion is generally explained by the action of proteins on macroscopic membrane properties such as curvature, elastic modulus, and tension, and a widespread model envisions that the SNARE motifs, juxtamembrane linkers, and C-terminal transmembrane regions of synaptobrevin and syntaxin-1 form continuous helices that act mechanically as semirigid rods, squeezing the membranes together as they assemble ("zipper") from the N to the C termini. However, the mechanism underlying fast SNARE-induced membrane fusion remains unknown. We have used all-atom molecular dynamics simulations to investigate this mechanism. Our results need to be interpreted with caution because of the limited number and length of the simulations, but they suggest a model of membrane fusion that has a natural physicochemical basis, emphasizes local molecular events over general membrane properties, and explains extensive experimental data. In this model, the central event that initiates fast (microsecond scale) membrane fusion occurs when the SNARE helices zipper into the juxtamembrane linkers which, together with the adjacent transmembrane regions, promote encounters of acyl chains from both bilayers at the polar interface. The resulting hydrophobic nucleus rapidly expands into stalk-like structures that gradually progress to form a fusion pore, aided by the SNARE transmembrane regions and without clearly discernible intermediates. The propensity of polyunsaturated lipids to participate in encounters that initiate fusion suggests that these lipids may be important for the high speed of neurotransmitter release.

Simulated dynamic cholesterol redistribution favors membrane fusion pore constriction

Endo- and exocytosis proceed through a highly strained membrane fusion pore topology regardless of the aiding protein machinery. The membrane's lipid components bias fusion pores toward expansion or closure, modifying the necessary work done by proteins. Cholesterol, a key component of plasma membranes, promotes both inverted lipid phases with concave leaflets (i.e., negative total curvature, which thins the leaflet) and flat bilayer phases with thick, ordered hydrophobic interiors. We demonstrate by theory and simulation that both leaflets of nascent catenoidal fusion pores have negative total curvature. Furthermore, the hydrophobic core of bilayers with strong negative Gaussian curvature is thinned. Therefore, it is an open question whether cholesterol will be enriched in these regions because of the negative total curvature or depleted because of the membrane thinning. Here, we compare all-atom molecular dynamics simulations (built using a procedure to create specific fusion pore geometries) and theory to understand the underlying reasons for lipid redistribution on fusion pores. Our all-atom molecular dynamics simulations resolve this question by showing that cholesterol is strongly excluded from the thinned neck of fusion and fission pores, revealing that thickness (and/or lipid order) influences cholesterol distributions more than curvature. The results imply that cholesterol exclusion can drive fusion pore closure by creating a small, cholesterol-depleted zone in the neck. This model agrees with literature evidence that membrane reshaping is connected to cholesterol-dependent lateral phase separation.

Machine Learning-Driven Multiscale Modeling: Bridging the Scales with a Next-Generation Simulation Infrastructure

Interdependence across time and length scales is common in biology, where atomic interactions can impact larger-scale phenomenon. Such dependence is especially true for a well-known cancer signaling pathway, where the membrane-bound RAS protein binds an effector protein called RAF. To capture the driving forces that bring RAS and RAF (represented as two domains, RBD and CRD) together on the plasma membrane, simulations with the ability to calculate atomic detail while having long time and large length- scales are needed. The Multiscale Machine-Learned Modeling Infrastructure (MuMMI) is able to resolve RAS/RAF protein-membrane interactions that identify specific lipid-protein fingerprints that enhance protein orientations viable for effector binding. MuMMI is a fully automated, ensemble-based multiscale approach connecting three resolution scales: (1) the coarsest scale is a continuum model able to simulate milliseconds of time for a 1 μm2 membrane, (2) the middle scale is a coarse-grained (CG) Martini bead model to explore protein-lipid interactions, and (3) the finest scale is an all-atom (AA) model capturing specific interactions between lipids and proteins. MuMMI dynamically couples adjacent scales in a pairwise manner using machine learning (ML). The dynamic coupling allows for better sampling of the refined scale from the adjacent coarse scale (forward) and on-the-fly feedback to improve the fidelity of the coarser scale from the adjacent refined scale (backward). MuMMI operates efficiently at any scale, from a few compute nodes to the largest supercomputers in the world, and is generalizable to simulate different systems. As computing resources continue to increase and multiscale methods continue to advance, fully automated multiscale simulations (like MuMMI) will be commonly used to address complex science questions.

On the role of membrane embedding, protein rigidity and transmembrane length in lipid membrane fusion

The fusion of biological membranes is ubiquitous in natural processes like exo- and endocytosis, intracellular trafficking and viral entry. Membrane fusion is also utilized in artificial biomimetic fusion systems, e.g. for drug delivery. Both the natural and the biomimetic fusion systems rely on a wide range of (artificial) proteins mediating the fusion process. Although the exact mechanisms of these proteins differ, clear analogies in their general behavior can be observed in bringing the membranes in close proximity and mediating the fusion reaction. In our study, we use molecular dynamics simulations with coarse grained models, mimicking the general behavior of fusion proteins (spikes), to systematically examine the effects of specific characteristics of these proteins on the fusion process. The protein characteristics considered are (i) the type of membrane embedding, i.e., either transmembrane or not, (ii) the rigidity, and (iii) the transmembrane domain (TMD) length. The results show essential differences in fusion pathway between monotopic and transmembrane spikes, in which transmembrane spikes seem to inhibit the formation of hemifusion diaphragms, leading to a faster fusion development. Furthermore, we observed that an increased rigidity and a decreased TMD length both proved to contribute to a faster fusion development. Finally, we show that a single spike may suffice to successfully induce a fusion reaction, provided that the spike is sufficiently rigid and attractive. Not only does this shed light on biological fusion of membranes, it also provides clear design rules for artificial membrane fusion systems.

All-atom molecular dynamics simulations of Synaptotagmin-SNARE-complexin complexes bridging a vesicle and a flat lipid bilayer

Synaptic vesicles are primed into a state that is ready for fast neurotransmitter release upon Ca²⁺-binding to Synaptotagmin-1. This state likely includes trans-SNARE complexes between the vesicle and plasma membranes that are bound to Synaptotagmin-1 and complexins. However, the nature of this state and the steps leading to membrane fusion are unclear, in part because of the difficulty of studying this dynamic process experimentally. To shed light into these questions, we performed all-atom molecular dynamics simulations of systems containing trans-SNARE complexes between two flat bilayers or a vesicle and a flat bilayer with or without fragments of Synaptotagmin-1 and/or complexin-1. Our results need to be interpreted with caution because of the limited simulation times and the absence of key components, but suggest mechanistic features that may control release and help visualize potential states of the primed Synaptotagmin-1-SNARE-complexin-1 complex. The simulations suggest that SNAREs alone induce formation of extended membrane-membrane contact interfaces that may fuse slowly, and that the primed state contains macromolecular assemblies of trans-SNARE complexes bound to the Synaptotagmin-1 C₂B domain and complexin-1 in a spring-loaded configuration that prevents premature membrane merger and formation of extended interfaces, but keeps the system ready for fast fusion upon Ca²⁺ influx.

Computational investigations on target-site searching and recognition mechanisms by thymine DNA glycosylase during DNA repair process

DNA glycosylase, as one member of DNA repair machineries, plays an essential role in correcting mismatched/damaged DNA nucleotides by cleaving the N-glycosidic bond between the sugar and target nucleobase through the base excision repair (BER) pathways. Efficient corrections of these DNA lesions are critical for maintaining genome integrity and preventing premature aging and cancers. The target-site searching/recognition mechanisms and the subsequent conformational dynamics of DNA glycosylase, however, remain challenging to be characterized using experimental techniques. In this review, we summarize our recent studies of sequential structural changes of thymine DNA glycosylase (TDG) during the DNA repair process, achieved mostly by molecular dynamics (MD) simulations. Computational simulations allow us to reveal atomic-level structural dynamics of TDG as it approaches the target-site, and pinpoint the key structural elements responsible for regulating the translocation of TDG along DNA. Subsequently, upon locating the lesions, TDG adopts a base-flipping mechanism to extrude the mispaired nucleobase into the enzyme active-site. The constructed kinetic network model elucidates six metastable states during the base-extrusion process and suggests an active role of TDG in flipping the intrahelical nucleobase. Finally, the molecular mechanism of product release dynamics after catalysis is also summarized. Taken together, we highlight to what extent the computational simulations advance our knowledge and understanding of the molecular mechanism underlying the conformational dynamics of TDG, as well as the limitations of current theoretical work.

Modeling biomolecular kinetics with large-scale simulation

The molecular details of biomolecular kinetics present a challenging estimation problem because the identities of relevant intermediates and the rates of exchange between them must be determined. These can be derived from prior knowledge, but in recent years, great advances have been made in the development and application of methods to systematically determine states and rates using biomolecular simulation. Doing this for biological systems of reasonable complexity requires substantial computational power, and contemporary methods leverage distributed computing or leadership-class computing resources to accomplish this. The result has been substantial insight into pressing contemporary problems, including structural activation of pandemic viruses. Here, we highlight recent developments in both methodology and exciting applications.

Computational methods to study enveloped viral entry

The protein-membrane interactions that mediate viral infection occur via loosely ordered, transient assemblies, creating challenges for high-resolution structure determination. Computational methods and in particular molecular dynamics simulation have thus become important adjuncts for integrating experimental data, developing mechanistic models, and suggesting testable hypotheses regarding viral function. However, the large molecular scales of virus-host interaction also create challenges for detailed molecular simulation. For this reason, continuum membrane models have played a large historical role, although they have become less favored for high-resolution models of protein assemblies and lipid organization. Here, we review recent progress in the field, with an emphasis on the insight that has been gained using a mixture of coarse-grained and atomic-resolution molecular dynamics simulations. Based on successes and challenges to date, we suggest a multiresolution strategy that should yield the best mixture of computational efficiency and physical fidelity. This strategy may facilitate further simulations of viral entry by a broader range of viruses, helping illuminate the diversity of viral entry strategies and the essential common elements that can be targeted for antiviral therapies.

Exploring the most stable aptamer/target molecule complex by the stochastic tunnelling-basin hopping-discrete molecular dynamics method

The stochastic tunnelling-basin hopping-discrete molecular dynamics (STUN-BH-DMD) method was applied to the search for the most stable biomolecular complexes in water by using the MARTINI coarse-grained (CG) model. The epithelial cell adhesion molecule (EpCAM, PDB code: 4MZV) was used as an EpCAM adaptor for an EpA (Apt_EpA) benchmark target molecule. The effects of two adsorption positions on the EpCAM were analysed, and it is found that the Apt_EpA adsorption configuration located within the EpCAM pocket-like structure is more stable and the energy barrier is lower due to the interaction with water. By the root mean square deviation (RMSD), the configuration of EpCAM in water is more conservative when the Apt_EpA binds to EpCAM by attaching to the pocket space of the EpCAM dimer. For Apt_EpA, the root mean square fluctuation (RMSF) analysis result indicates Nucleobase 1 and Nucleobase 2 display higher flexibility during the CGMD simulation. Finally, from the binding energy contour maps and histogram plots of EpCAM and each Apt_EpA nucleobase, it is clear that the binding energy adsorbed to the pocket-like structure is more continuous than that energy not adsorbed to the pocket-like structure. This study has proposed a new numerical process for applying the STUN-BH-DMD with the CG model, which can reduce computational details and directly find a more stable Apt_EpA/EpCAM complex in water.

Fast bilayer-micelle fusion mediated by hydrophobic dipeptides

To understand the transition from inanimate matter to life, we studied a process that directly couples simple metabolism to evolution via natural selection, demonstrated experimentally by Adamala and Szostak. In this process, dipeptides synthesized inside precursors of cells promote absorption of fatty acid micelles to vesicles, inducing their preferential growth and division at the expense of other vesicles. The process is explained on the basis of coarse-grained molecular dynamics simulations, each extending for tens of microseconds, carried out to model fusion between a micelle and a membrane, both made of fatty acids in the absence and presence of hydrophobic dipeptides. In all systems with dipeptides, but not in their absence, fusion events were observed. They involve the formation of a stalk made by hydrophobic chains from the micelle and the membrane, similar to that postulated for vesicle-vesicle fusion. The emergence of a stalk is facilitated by transient clusters of dipeptides, side chains of which form hydrophobic patches at the membrane surface. Committor probability calculations indicate that the size of a patch is a suitable reaction coordinate and allows for identifying the transition state for fusion. Free-energy barrier to fusion is greatly reduced in the presence of dipeptides to only 4-5 kcal/mol, depending on the hydrophobicity of side chains. The mechanism of mediated fusion, which is expected to apply to other small peptides and hydrophobic molecules, provides a robust means by which a nascent metabolism can confer evolutionary advantage to precursors of cells.

How proteins open fusion pores: insights from molecular simulations

Fusion proteins can play a versatile and involved role during all stages of the fusion reaction. Their roles go far beyond forcing the opposing membranes into close proximity to drive stalk formation and fusion. Molecular simulations have played a central role in providing a molecular understanding of how fusion proteins actively overcome the free energy barriers of the fusion reaction up to the expansion of the fusion pore. Unexpectedly, molecular simulations have revealed a preference of the biological fusion reaction to proceed through asymmetric pathways resulting in the formation of, e.g., a stalk-hole complex, rim-pore, or vertex pore. Force-field based molecular simulations are now able to directly resolve the minimum free-energy path in protein-mediated fusion as well as quantifying the free energies of formed reaction intermediates. Ongoing developments in Graphics Processing Units (GPUs), free energy calculations, and coarse-grained force-fields will soon gain additional insights into the diverse roles of fusion proteins.

Where are those lipid nano rings?

Highly curved toroidal micelles with diameters as small as 100 nm have been successfully constructed by self-assembly of amphiphilic block copolymers. These structures may have potential applications in gene or drug delivery. Experimental observations suggest that toroidal micelles likely originate from spherical or disc-like micelles which are tricked into forming toroidal micelles upon external stimuli ('smart' materials). Since self-assembly of polymeric and lipid surfactants is guided by the same physical principles, we hypothesize that 'smart' lipid surfactants can be equivalently tricked into forming highly curved toroidal micelles that are tenfold smaller (≃10 nm diameter). Paradoxically, these 'nano rings' have never been observed. Using coarse-grained molecular dynamics (MD) simulations in conjunction with a state-of-the-art free energy calculation method (a string method), we illustrate how a thermo-responsive lipid surfactant is able to form toroidal micelles. These micelles originate from disc-like micelles that are spontaneously perforated upon heat shocking, thereby supporting a longstanding hypothesis on the possible origin of polymeric toroidal micelle phases observed in experiments. We illustrate that kinetically stable 'nano rings' are substantially shorter lived than their tenfold larger polymeric analogs. The estimated life-time (milliseconds) is in fact similar to the characteristic breaking time of the corresponding worm-like micelle. Finally, we resolve the characteristic finger print which 'nano rings' leave in time-resolved X-ray spectra and illustrate how the uptake of small DNA fragments may enhance their stability. Despite a shared kinetics of self-assembly, length scale dependent differences in the life-time of surfactant phases can occur when phases are kinetically rather than thermodynamically stable. This results in the apparent absence or presence of toroidal micelle phases on different length scales. Our theoretical work precisely illustrates that the universality of surfactants nevertheless remains conserved even at different length scales.

Quantitative Synaptic Biology: A Perspective on Techniques, Numbers and Expectations

Synapses play a central role for the processing of information in the brain and have been analyzed in countless biochemical, electrophysiological, imaging, and computational studies. The functionality and plasticity of synapses are nevertheless still difficult to predict, and conflicting hypotheses have been proposed for many synaptic processes. In this review, we argue that the cause of these problems is a lack of understanding of the spatiotemporal dynamics of key synaptic components. Fortunately, a number of emerging imaging approaches, going beyond super-resolution, should be able to provide required protein positions in space at different points in time. Mathematical models can then integrate the resulting information to allow the prediction of the spatiotemporal dynamics. We argue that these models, to deal with the complexity of synaptic processes, need to be designed in a sufficiently abstract way. Taken together, we suggest that a well-designed combination of imaging and modelling approaches will result in a far more complete understanding of synaptic function than currently possible.

Continuum Models of Membrane Fusion: Evolution of the Theory

Starting from fertilization, through tissue growth, hormone secretion, synaptic transmission, and sometimes morbid events of carcinogenesis and viral infections, membrane fusion regulates the whole life of high organisms. Despite that, a lot of fusion processes still lack well-established models and even a list of main actors. A merger of membranes requires their topological rearrangements controlled by elastic properties of a lipid bilayer. That is why continuum models based on theories of membrane elasticity are actively applied for the construction of physical models of membrane fusion. Started from the view on the membrane as a structureless film with postulated geometry of fusion intermediates, they developed along with experimental and computational techniques to a powerful tool for prediction of the whole process with molecular accuracy. In the present review, focusing on fusion processes occurring in eukaryotic cells, we scrutinize the history of these models, their evolution and complication, as well as open questions and remaining theoretical problems. We show that modern approaches in this field allow continuum models of membrane fusion to stand shoulder to shoulder with molecular dynamics simulations, and provide the deepest understanding of this process in multiple biological systems.

Stochastic modeling of nanoparticle internalization and expulsion through receptor-mediated transcytosis

Receptor-mediated transcytosis (RMT) is a fundamental mechanism for the transcellular transport of nanoparticles. RMT is a complex process, during which the nanoparticles actively interact with the membrane and the membrane profile undergoes extreme deformations for particle internalization and expulsion. In this work, we developed a stochastic model to study the endocytosis and exocytosis of nanoparticles across soft membranes. The model is based on the combination of a stochastic particle binding model with a membrane model, and accounts for both clathrin-mediated endocytosis for internalization and actin-mediated exocytosis for expulsion. Our results showed that nanoparticles must have certain avidity with enough ligand density and ligand-receptor binding affinity to be taken up, while too high avidity limited the particle release from the cell surface. We further explored the functional roles of actin during exocytosis, which has been a topic under active debate. Our simulations indicated that the membrane compression due to the actin induced tension tended to break the ligand-receptor bonds and to shrink the fusion pore. Therefore, an intermediate tension promoted the fusion pore expansion and nanoparticle release, while high tension prohibits particle release. Our model provides new and critical mechanistic insights into RMT, and represents a powerful platform for aiding the rational design of nanocarriers for controlled drug delivery.

Elucidation of the mechanism and energy barrier for anesthetic triggered membrane fusion in model membranes

Membrane fusion is vital for cellular function and is generally mediated via fusogenic proteins and peptides. The mechanistic details and subsequently the transition state dynamics of membrane fusion will be dependent on the type of the fusogenic agent. We have previously established the potential of general anesthetics as a new class of fusion triggering agents in model membranes. We employed two-photon excitation fluorescence cross-correlation spectroscopy (TPE-FCCS) to report on vesicle association kinetics and steady-state fluorescence dequenching assays to monitor lipid mixing kinetics. Using halothane to trigger fusion in 110 nm diameter dioleoylphosphatidylcholine (DOPC) liposomes, we found that lipid rearrangement towards the formation of the fusion stalk was rate limiting. The activation barrier for halothane induced membrane fusion in 110 nm vesicles was found to be ∼40 kJ mol−1. We calculated the enthalpy and entropy of the transition state to be ∼40 kJ mol−1and ∼180 J mol−1K−1, respectively. We have found that the addition of halothane effectively lowers the energy barrier for membrane fusion in less curved vesicles largely due to entropic advantages.

Thermodynamically reversible paths of the first fusion intermediate reveal an important role for membrane anchors of fusion proteins

Biological membrane fusion proceeds via an essential topological transition of the two membranes involved. Known players such as certain lipid species and fusion proteins are generally believed to alter the free energy and thus the rate of the fusion reaction. Quantifying these effects by theory poses a major challenge since the essential reaction intermediates are collective, diffusive and of a molecular length scale. We conducted molecular dynamics simulations in conjunction with a state-of-the-art string method to resolve the minimum free-energy path of the first fusion intermediate state, the so-called stalk. We demonstrate that the isolated transmembrane domains (TMDs) of fusion proteins such as SNARE molecules drastically lower the free energy of both the stalk barrier and metastable stalk, which is not trivially explained by molecular shape arguments. We relate this effect to the local thinning of the membrane (negative hydrophobic mismatch) imposed by the TMDs which favors the nearby presence of the highly bent stalk structure or prestalk dimple. The distance between the membranes is the most crucial determinant of the free energy of the stalk, whereas the free-energy barrier changes only slightly. Surprisingly, fusion enhancing lipids, i.e., lipids with a negative spontaneous curvature, such as PE lipids have little effect on the free energy of the stalk barrier, likely because of its single molecular nature. In contrast, the lipid shape plays a crucial role in overcoming the hydration repulsion between two membranes and thus rather lowers the total work required to form a stalk.

Adaptive ensemble simulations of biomolecules

Recent advances in both theory and computational power have created opportunities to simulate biomolecular processes more efficiently using adaptive ensemble simulations. Ensemble simulations are now widely used to compute a number of individual simulation trajectories and analyze statistics across them. Adaptive ensemble simulations offer a further level of sophistication and flexibility by enabling high-level algorithms to control simulations-based on intermediate results. We review some of the adaptive ensemble algorithms and software infrastructure currently in use and outline where the complexities of implementing adaptive simulation have limited algorithmic innovation to date. We describe an adaptive ensemble API to overcome some of these barriers and more flexibly and simply express adaptive simulation algorithms to help realize the power of this type of simulation.

The fusion pore, 60 years after the first cartoon

Neurotransmitter release occurs in the form of quantal events by fusion of secretory vesicles with the plasma membrane, and begins with the formation of a fusion pore that has a conductance similar to that of a large ion channel or gap junction. In this review, we propose mechanisms of fusion pore formation and discuss their implications for fusion pore structure and function. Accumulating evidence indicates a direct role of soluble N-ethylmaleimide-sensitive-factor attachment receptor proteins in the opening of fusion pores. Fusion pores are likely neither protein channels nor purely lipid, but are of proteolipidic composition. Future perspectives to gain better insight into the molecular structure of fusion pores are discussed.

Hemagglutinin-Mediated Membrane Fusion: A Biophysical Perspective

Influenza hemagglutinin (HA) is a viral membrane protein responsible for the initial steps of the entry of influenza virus into the host cell. It mediates binding of the virus particle to the host-cell membrane and catalyzes fusion of the viral membrane with that of the host. HA is therefore a major target in the development of antiviral strategies. The fusion of two membranes involves high activation barriers and proceeds through several intermediate states. Here, we provide a biophysical description of the membrane fusion process, relating its kinetic and thermodynamic properties to the large conformational changes taking place in HA and placing these in the context of multiple HA proteins working together to mediate fusion. Furthermore, we highlight the role of novel single-particle experiments and computational approaches in understanding the fusion process and their complementarity with other biophysical approaches.

Coarse-grained molecular dynamics study of membrane fusion: Curvature effects on free energy barriers along the stalk mechanism

The effects of membrane curvature on the free energy barrier for membrane fusion have been investigated using coarse-grained molecular dynamics (CG-MD) simulations, assuming that fusion takes place through a stalk intermediate. Free energy barriers were estimated for stalk formation as well as for fusion pore formation using the guiding potential method. Specifically, the three different geometries of two apposed membranes were considered: vesicle-vesicle, vesicle-planar, and planar-planar membranes. The free energy barriers for the resulting fusion were found to depend importantly on the fusing membrane geometries; the lowest barrier was obtained for vesicular membranes. Further, lipid sorting was observed in fusion of the mixed membranes of dimyristoyl phosphatidylcholine and dioleoyl phosphatidylethanolamine (DOPE). Specifically, DOPE molecules were found to assemble around the stalk to support the highly negative curved membrane surface. A consistent result for lipid sorting was observed when a simple continuum model (CM) was used, where the Helfrich energy and mixing entropy of the lipids were taken into account. However, the CM predicts a much higher free energy barrier than found using CG-MD. This discrepancy originates from the conformational changes of lipids, which were not considered in the CM. The results of the CG-MD simulations reveal that a large conformational change in the lipid takes place around the stalk region, which results in a reduction of free energy barriers along the stalk mechanism of membrane fusion.

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.

Probing the structural dynamics of the SNARE recycling machine based on coarse-grained modeling

Membrane fusion in eukaryotes is driven by the formation of a four-helix bundle by three SNARE proteins. To recycle the SNARE proteins, they must be disassembled by the ATPase NSF and four SNAP proteins which together form a 20S supercomplex. Recently, the first high-resolution structures of the NSF (in both ATP and ADP state) and 20S (in four distinct states termed I, II, IIIa, and IIIb) were solved by cryo-electron microscopy (cryo-EM), which have paved the way for structure-driven studies of the SNARE recycling mechanism. To probe the structural dynamics of SNARE disassembly at amino-acid level of details, a systematic coarse-grained modeling based on an elastic network model and related analyses were performed. Our normal mode analysis of NSF, SNARE, and 20S predicted key modes of collective motions that partially account for the observed structural changes, and illuminated how the SNARE complex can be effectively destabilized by untwisting and bending motions of the SNARE complex driven by the amino-terminal domains of NSF in state II. Our flexibility analysis identified regions with high/low flexibility that coincide with key functional sites (such as the NSF-SNAPs-SNARE binding sites). A subset of hotspot residues that control the above collective motions, which will make promising targets for future mutagenesis studies were also identified. Finally, the conformational changes in 20S as induced by the transition of NSF from ATP to ADP state were modeled, and a concerted untwisting motion of SNARE/SNAPs and a sideway flip of two amino-terminal domains were observed. In sum, the findings have offered new structural and dynamic details relevant to the SNARE disassembly mechanism, and will guide future functional studies of the SNARE recycling machinery. Proteins 2016; 84:1055-1066. © 2016 Wiley Periodicals, Inc.

Calculating Transition Energy Barriers and Characterizing Activation States for Steps of Fusion

We use continuum mechanics to calculate an entire least energy pathway of membrane fusion, from stalk formation, to pore creation, and through fusion pore enlargement. The model assumes that each structure in the pathway is axially symmetric. The static continuum stalk structure agrees quantitatively with experimental stalk architecture. Calculations show that in a stalk, the distal monolayer is stretched and the stored stretching energy is significantly less than the tilt energy of an unstretched distal monolayer. The string method is used to determine the energy of the transition barriers that separate intermediate states and the dynamics of two bilayers as they pass through them. Hemifusion requires a small amount of energy independently of lipid composition, while direct transition from a stalk to a fusion pore without a hemifusion intermediate is highly improbable. Hemifusion diaphragm expansion is spontaneous for distal monolayers containing at least two lipid components, given sufficiently negative diaphragm spontaneous curvature. Conversely, diaphragms formed from single-component distal monolayers do not expand without the continual injection of energy. We identify a diaphragm radius, below which central pore expansion is spontaneous. For larger diaphragms, prior studies have shown that pore expansion is not axisymmetric, and here our calculations supply an upper bound for the energy of the barrier against pore formation. The major energy-requiring deformations in the steps of fusion are: widening of a hydrophobic fissure in bilayers for stalk formation, splay within the expanding hemifusion diaphragm, and fissure widening initiating pore formation in a hemifusion diaphragm.

LHD-Modified Mechanism-Based Liposome Coencapsulation of Mitoxantrone and Prednisolone Using Novel Lipid Bilayer Fusion for Tissue-Specific Colocalization and Synergistic Antitumor Effects

Coencapsulation liposomes are of interest to researchers because they maximize the synergistic effect of loaded drugs. A combination regimen of mitoxantrone (MTO) and prednisolone (PLP) has been ideal for tumor therapy. MTO and PLP offer synergistic antitumor effects confirmed by several experiments in this research. The deduced synergistic mechanism is regulation of Akt signaling pathway including the targets of p-Akt, p-GSK-3β, p-s6 ribosomal protein, and p-AMPK by MTO reactivating PLP-induced apoptosis. The liposome fusion method is adopted to create coencapsulation liposomes (PLP-MTO-YM). Low molecular weight heparin-sodium deoxycholate conjugate (LHD) then is used as a targeting ligand to prove target binding and inhibition of angiogenesis. LHD-modified liposomes (PLP-MTO-HM) have a high entrapment efficiency around 95% for both MTO and PLP. DSC results indicate that both drugs interacted with liposomes to prevent drug leak during liposome fusion. DiD-C6-HM dyes colocalize well to tumor tissue, and coadministration of DiD-HM and C6-CM did not achieve dye colocalization until 24 h after administration. In both CT26 and B16F10 mouse model, PLP-MTO-HM shows a significantly higher tumor inhibition rate relative to the coadministration of MTO-HM and PLP-CM (p < 0.05 or p < 0.01). Thus, the coencapsulation system (PLP-MTO-HM) offers ideal antitumor effects relative to coadministration therapy due to enhanced synergistic effect, and this suggests a promising future for the tumor targeting vectors.

Solvent-exposed lipid tail protrusions depend on lipid membrane composition and curvature

The stochastic protrusion of hydrophobic lipid tails into solution, a subclass of hydrophobic membrane defects, has recently been shown to be a critical step in a number of biological processes like membrane fusion. Understanding the factors that govern the appearance of lipid tail protrusions is critical for identifying membrane features that affect the rate of fusion or other processes that depend on contact with solvent-exposed lipid tails. In this work, we utilize atomistic molecular dynamics simulations to characterize the likelihood of tail protrusions in phosphotidylcholine lipid bilayers of varying composition, curvature, and hydration. We distinguish two protrusion modes corresponding to atoms near the end of the lipid tail or near the glycerol group. Through potential of mean force calculations, we demonstrate that the thermodynamic cost for inducing a protrusion depends on tail saturation but is insensitive to other bilayer structural properties or hydration above a threshold value. Similarly, highly curved vesicles or micelles increase both the overall frequency of lipid tail protrusions as well as the preference for splay protrusions, both of which play an important role in driving membrane fusion. In multi-component bilayers, however, the incidence of protrusion events does not clearly depend on the mismatch between tail length or tail saturation of the constituent lipids. Together, these results provide significant physical insight into how system components might affect the appearance of protrusions in biological membranes, and help explain the roles of composition or curvature-modifying proteins in membrane fusion.

Coarse-Grained Protein Model Coupled with a Coarse-Grained Water Model: Molecular Dynamics Study of Polyalanine-Based Peptides

The coupling of a coarse-grained (CG) protein model with the CG water model developed by Marrink et al. (J. Phys. Chem. B 2004, 108, 750) is presented. The model was used in the molecular dynamics studies of Ac-(Ala)6-Xaa-(Ala)7-NHMe, Xaa = Ala, Leu, Val, and Gly. A Gly mutation in the middle of polyalanine is found to destabilize the helix and stabilize the hairpin by favoring a type-II' turn and probably to speed up hairpin folding. The simulations allow us to derive thermodynamic parameters of, in particular, the helical propensities (s) of amino acids in these polyalanine-based peptides. The calculated s values are 1.18 (Ala), 0.84 (Leu), 0.30 (Val), and <0.02 (Gly) at 291 K, in excellent agreement with experimental values (R(2)=0.970). Analyses using a structural approach method show that the helical propensity difference of these amino acids mainly comes from solvation effect. Leu and Val have lower helical propensities than Ala mainly because the larger side chains shield the solvation of helical structures, while Gly has a much poorer helical propensity mainly due to the much better solvation for the coil structures than for the helical structures. Overall, the model is at least about 10(2) times faster than current all-atom MD methods with explicit solvent.

Toward a Coarse-Grained Protein Model Coupled with a Coarse-Grained Solvent Model: Solvation Free Energies of Amino Acid Side Chains

Recently, we reported that molecular dynamics (MD) simulations using a coarse-grained (CG) peptide model coupled with a CG water model are able to reproduce many of the structural and thermodynamic features of short peptides with nonpolar side chains at 10(3) times the normal speed (JCTC, 2007, 3, 2146-2161). To further develop a CG protein model for MD simulations, we systematically parametrized the side chains of all 20 naturally occurring amino acids. We developed the parameters by fitting the dihedral potentials of 13 small molecules, the densities and self-solvation free energies of liquids of eight organic molecules, and the hydration free energies of 35 small organic molecules. In a set of 11 classes of compounds (105 in total) including alkanes, alcohols, ethers, ketones/aldehydes, amines, amides, aromatics, carboxylic acids, sulfides/thiols, alkyl ammoniums, and carboxylate ions, the average error in the calculated hydration free energies compared with experimental results is about 1.4 kJ/mol. The average error in the calculated transfer free energies of the 19 side-chain analogues of amino acids from cyclohexane to water is about 2.2 kJ/mol. These results are comparable to the results of all-atom models.

PACE Force Field for Protein Simulations. 2. Folding Simulations of Peptides

We present the application of our recently developed PACE force field to the folding of peptides. These peptides include α-helical (AK17 and Fs), β-sheet (GB1m2 and Trpzip2), and mixed helical/coil (Trp-cage) peptides. With replica exchange molecular dynamics (REMD), our force field can fold the five peptides into their native structures while maintaining their stabilities reasonably well. Our force field is also able to capture important thermodynamic features of the five peptides that have been observed in previous experimental and computational studies, such as different preferences for a helix-turn-helix topology for AK17 and Fs, the relative contribution of four hydrophobic side chains of GB1p to the stability of β-hairpin, and the distinct role of a hydrogen bond involving Trp-Hε and a D9/R16 salt bridge in stabilizing the Trp-cage native structure. Furthermore, multiple folding and unfolding events are observed in our microsecond-long normal MD simulations of AK17, Trpzip2, and Trp-cage. These simulations provide mechanistic information such as a "zip-out" pathway of the folding mechanism of Trpzip2 and the folding times of AK17 and Trp-cage, which are estimated to be about 51 ± 43 ns and 270 ± 110 ns, respectively. A 600 ns simulation of the peptides can be completed within one day. These features of our force field are potentially applicable to the study of thermodynamics and kinetics of real protein systems.

Expansion of the fusion stalk and its implication for biological membrane fusion

Over the past 20 years, it has been widely accepted that membrane fusion proceeds via a hemifusion step before opening of the productive fusion pore. An initial hourglass-shaped lipid structure, the fusion stalk, is formed between the adjacent membrane leaflets (cis leaflets). It remains controversial if and how fusion proteins drive the subsequent transition (expansion) of the stalk into a fusion pore. Here, we propose a comprehensive and consistent thermodynamic understanding in terms of the underlying free-energy landscape of stalk expansion. We illustrate how the underlying free energy landscape of stalk expansion and the concomitant pathway is altered by subtle differences in membrane environment, such as leaflet composition, asymmetry, and flexibility. Nonleaky stalk expansion (stalk widening) requires the formation of a critical trans-leaflet contact. The fusion machinery can mechanically enforce trans-leaflet contact formation either by directly enforcing the trans-leaflets in close proximity, or by (electrostatically) condensing the area of the cis leaflets. The rate of these fast fusion reactions may not be primarily limited by the energetics but by the forces that the fusion proteins are able to exert.

Free energy analysis along the stalk mechanism of membrane fusion

The free energy profile of the stalk model of membrane fusion has been calculated using coarse-grained molecular dynamics simulations. The proposed method guides the lipid configuration using a guiding wall potential to make the transition from two apposed membranes to a stalk and a fusion pore. The free energy profile is obtained with a thermodynamic integration scheme using the mean force working on the guiding wall as a response of the system. We applied the method to two apposed flat bilayers composed of dioleoyl phosphatidylethanolamine/dioleoyl phosphatidylcholine expanding over the simulation box under the periodic boundary conditions. The two transition states are identified as pre-stalk and pre-pore states. The free energy barrier for the latter is confirmed to be in good agreement with that estimated by the pulling method. The present method provides a practical way to calculate the free energy profile along the stalk mechanism.

Multi-step formation of a hemifusion diaphragm for vesicle fusion revealed by all-atom molecular dynamics simulations

Membrane fusion is essential for intracellular trafficking and virus infection, but the molecular mechanisms underlying the fusion process remain poorly understood. In this study, we employed all-atom molecular dynamics simulations to investigate the membrane fusion mechanism using vesicle models which were pre-bound by inter-vesicle Ca(2+)-lipid clusters to approximate Ca(2+)-catalyzed fusion. Our results show that the formation of the hemifusion diaphragm for vesicle fusion is a multi-step event. This result contrasts with the assumptions made in most continuum models. The neighboring hemifused states are separated by an energy barrier on the energy landscape. The hemifusion diaphragm is much thinner than the planar lipid bilayers. The thinning of the hemifusion diaphragm during its formation results in the opening of a fusion pore for vesicle fusion. This work provides new insights into the formation of the hemifusion diaphragm and thus increases understanding of the molecular mechanism of membrane fusion. This article is part of a Special Issue entitled: Membrane Structure and Function: Relevance in the Cell's Physiology, Pathology and Therapy.

Constant pH simulations with the coarse-grained MARTINI model — Application to oleic acid aggregates

Long chain fatty acids are biologically important molecules with complex and pH sensitive aggregation behavior. The carboxylic head group of oleic acid is ionizable, with the pKa shifting to larger values, even above a value of 7, in certain aggregate states. While experiments have determined the macroscopic phase behavior, we have yet to understand the molecular level details for this complex behavior. This level of detail is likely required to fully appreciate the role of fatty acids in biology and for nanoscale biotechnological and industrial applications. Here, we introduce the use of constant pH molecular dynamics (MD) simulations with the coarse-grained MARTINI model and apply the method to oleic acid aggregates and a model lipid bilayer. By running simulations at different constant pH values, we determined titration curves and the resulting pKa for oleic acid in different environments. The coarse-grained model predicts positive pKa shifts, with a shift from 4.8 in water to 6.5 in a small micelle, and 6.6 in a dioleoylphosphatidylcholine (DOPC) bilayer, similar to experimental estimates. The size of the micelles increased as the pH increased, and correlated with the fraction of deprotonated oleic acid. We show this combination of constant pH MD and the coarse-grained MARTINI model can be used to model pH-dependent surfactant phase behavior. This suggests a large number of potential new applications of large-scale MARTINI simulations in other biological systems with ionizable molecules.

A comparison of coarse-grained and continuum models for membrane bending in lipid bilayer fusion pores

To establish the validity of continuum mechanics models quantitatively for the analysis of membrane remodeling processes, we compare the shape and energies of the membrane fusion pore predicted by coarse-grained (MARTINI) and continuum mechanics models. The results at these distinct levels of resolution give surprisingly consistent descriptions for the shape of the fusion pore, and the deviation between the continuum and coarse-grained models becomes notable only when the radius of curvature approaches the thickness of a monolayer. Although slow relaxation beyond microseconds is observed in different perturbative simulations, the key structural features (e.g., dimension and shape of the fusion pore near the pore center) are consistent among independent simulations. These observations provide solid support for the use of coarse-grained and continuum models in the analysis of membrane remodeling. The combined coarse-grained and continuum analysis confirms the recent prediction of continuum models that the fusion pore is a metastable structure and that its optimal shape is neither toroidal nor catenoidal. Moreover, our results help reveal a new, to our knowledge, bowing feature in which the bilayers close to the pore axis separate more from one another than those at greater distances from the pore axis; bowing helps reduce the curvature and therefore stabilizes the fusion pore structure. The spread of the bilayer deformations over distances of hundreds of nanometers and the substantial reduction in energy of fusion pore formation provided by this spread indicate that membrane fusion can be enhanced by allowing a larger area of membrane to participate and be deformed.

Coarse-Grained Models for Protein-Cell Membrane Interactions

The physiological properties of biological soft matter are the product of collective interactions, which span many time and length scales. Recent computational modeling efforts have helped illuminate experiments that characterize the ways in which proteins modulate membrane physics. Linking these models across time and length scales in a multiscale model explains how atomistic information propagates to larger scales. This paper reviews continuum modeling and coarse-grained molecular dynamics methods, which connect atomistic simulations and single-molecule experiments with the observed microscopic or mesoscale properties of soft-matter systems essential to our understanding of cells, particularly those involved in sculpting and remodeling cell membranes.

Lipid nanotechnology

Nanotechnology is a multidisciplinary field that covers a vast and diverse array of devices and machines derived from engineering, physics, materials science, chemistry and biology. These devices have found applications in biomedical sciences, such as targeted drug delivery, bio-imaging, sensing and diagnosis of pathologies at early stages. In these applications, nano-devices typically interface with the plasma membrane of cells. On the other hand, naturally occurring nanostructures in biology have been a source of inspiration for new nanotechnological designs and hybrid nanostructures made of biological and non-biological, organic and inorganic building blocks. Lipids, with their amphiphilicity, diversity of head and tail chemistry, and antifouling properties that block nonspecific binding to lipid-coated surfaces, provide a powerful toolbox for nanotechnology. This review discusses the progress in the emerging field of lipid nanotechnology.

The Martini coarse-grained force field

The Martini force field is a coarse-grained force field suited for molecular dynamics simulations of biomolecular systems. The force field has been parameterized in a systematic way, based on the reproduction of partitioning free energies between polar and apolar phases of a large number of chemical compounds. In this chapter the methodology underlying the force field is presented together with details of its parameterization and limitations. Then currently available topologies are described with a short overview of the key elements of their parameterization. These include the new polarizable Martini water model. A set of three selected ongoing studies using the Martini force field is presented. Finally the latest lines of development are discussed.

Further optimization of a hybrid united-atom and coarse-grained force field for folding simulations: Improved backbone hydration and interactions between charged side chains

PACE, a hybrid force field which couples united-atom protein models with coarse-grained (CG) solvent, has been further optimized, aiming to improve itse ciency for folding simulations. Backbone hydration parameters have been re-optimized based on hydration free energies of polyalanyl peptides through atomistic simulations. Also, atomistic partial charges from all-atom force fields were combined with PACE in order to provide a more realistic description of interactions between charged groups. Using replica exchange molecular dynamics (REMD), ab initio folding using the new PACE has been achieved for seven small proteins (16 - 23 residues) with different structural motifs. Experimental data about folded states, such as their stability at room temperature, melting point and NMR NOE constraints, were also well reproduced. Moreover, a systematic comparison of folding kinetics at room temperature has been made with experiments, through standard MD simulations, showing that the new PACE may speed up the actual folding kinetics 5-10 times. Together with the computational speedup benefited from coarse-graining, the force field provides opportunities to study folding mechanisms. In particular, we used the new PACE to fold a 73-residue protein, 3D, in multiple 10 - 30 μs simulations, to its native states (C(α) RMSD ~ 0.34 nm). Our results suggest the potential applicability of the new PACE for the study of folding and dynamics of proteins.

Cell entry of enveloped viruses

Infection of cells by enveloped viruses requires merger of the viral envelope membrane with target cell membranes, resulting in the formation of fusion pores through which the viral genome is released. Since lipid membranes do not mix spontaneously, the fusion process is energy-dependent and mediated by viral envelope glycoprotein complexes. Based on their structural and mechanistic properties, three distinct classes of viral fusion proteins have been identified to date. Despite their diversity, basic principles of viral membrane fusion, simultaneous engagement of both donor and target membrane and refolding into hairpin-like structures, have emerged as universally conserved. This article provides an overview of the basic principles of viral membrane fusion common to all enveloped viruses and discusses the specific structural and functional features of the different fusion protein classes by example of the paramyxovirus, flavivirus and rhabdovirus families.

The hemifused state on the pathway to membrane fusion

Fusion of compartments enclosed by membrane bilayers enables secretion and other vital cellular processes and is widely studied in model synthetic membrane systems. Experiments suggest the fusion pathway passes through a hemifused intermediate where only outer monolayers are fused. Here we show membrane tension and divalent cations drive vesicles to hemifused equilibrium with expanded hemifusion diaphragms (HDs) where inner monolayers engage. Predicted HD sizes agree with recent measurements of Nikolaus et al. [Biophys. J. 98, 1192 (2010).]. The fusion pathway is completed by HD lysis provided HD tension is sufficiently high.