Balancing Force Field Protein-Lipid Interactions To Capture Transmembrane Helix-Helix Association

Machine Learning Derived Collective Variables for the Study of Protein Homodimerization in Membrane

The accurate calculation of equilibrium constants for protein-protein association is of fundamental importance to quantitative biology and remains an outstanding challenge for computational biophysics. Traditionally, equilibrium constants have been computed from one-dimensional free energy surfaces derived from sampling along a single collective variable. Importantly, recent advances in enhanced sampling methodology have facilitated the characterization of multidimensional free energy landscapes, often exposing multiple thermodynamically important minima missed by more restrictive sampling methods. A key to the effectiveness of this multidimensional sampling approach is the identification of collective variables that effectively define the configurational space of dissociated and associated states. Here we present the application of two machine learning methods for the unbiased determination of collective variables for enhanced sampling and analysis of protein-protein association. Our results both validate prior work, based on intuition derived collective variables, and demonstrate the effectiveness of the machine learning methods for the identification of collective variables for association reactions in complex biomolecular systems.

Free-energy landscapes of transmembrane homodimers by bias-exchange adaptively biased molecular dynamics

Membrane proteins play essential roles in various biological functions within the cell. One of the most common functional regulations involves the dimerization of two single-pass transmembrane (TM) helices. Glycophorin A (GpA) and amyloid precursor protein (APP) form TM homodimers in the membrane, which have been investigated both experimentally and computationally. The homodimer structures are well characterized using only four collective variables (CVs) when each TM helix is stable. The CVs are the interhelical distance, the crossing angle, and the Crick angles for two TM helices. However, conformational sampling with multi-dimensional replica-exchange umbrella sampling (REUS) requires too many replicas to sample all the CVs for exploring the conformational landscapes. Here, we show that the bias-exchange adaptively biased molecular dynamics (BE-ABMD) with the four CVs effectively explores the free-energy landscapes of the TM helix dimers of GpA, wild-type APP and its mutants in the IMM1 implicit membrane. Compared to the original ABMD, the bias-exchange algorithm in BE-ABMD can provide a more rapidly converged conformational landscape. The BE-ABMD simulations could also reveal TM packing interfaces of the membrane proteins and the dependence of the free-energy landscapes on the membrane thickness. This approach is valuable for numerous other applications, including those involving explicit solvent and a lipid bilayer in all-atom force fields or Martini coarse-grained models, and enhances our understanding of protein-protein interactions in biological membranes.

A Rigorous Framework for Calculating Protein-Protein Binding Affinities in Membranes

Calculating the binding free energy of integral transmembrane (TM) proteins is crucial for understanding the mechanisms by which they recognize one another and reversibly associate. The glycophorin A (GpA) homodimer, composed of two α-helical segments, has long served as a model system for studying TM protein reversible association. The present work establishes a methodological framework for calculating the binding affinity of the GpA homodimer in the heterogeneous environment of a membrane. Our investigation carefully considered a variety of protocols, including the appropriate choice of the force field, rigorous standardization reflecting the experimental conditions, sampling algorithm, anisotropic environment, and collective variables, to accurately describe GpA dimerization via molecular dynamics-based approaches. Specifically, two strategies were explored: (i) an unrestrained potential mean force (PMF) calculation, which merely enhances sampling along the separation of the two binding partners without any restraint, and (ii) a so-called "geometrical route", whereby the α-helices are progressively separated with imposed restraints on their orientational, positional, and conformational degrees of freedom to accelerate convergence. Our simulations reveal that the simplified, unrestrained PMF approach is inadequate for the description of GpA dimerization. Instead, the geometrical route, tailored specifically to GpA in a membrane environment, yields excellent agreement with experimental data within a reasonable computational time. A dimerization free energy of -10.7 kcal/mol is obtained, in fairly good agreement with available experimental data. The geometrical route further helps elucidate how environmental forces drive association before helical interactions stabilize it. Our simulations also brought to light a distinct, long-lived spatial arrangement that potentially serves as an intermediate state during dimer formation. The methodological advances in the generalized geometrical route provide a powerful tool for accurate and efficient binding-affinity calculations of intricate TM protein complexes in inhomogeneous environments.

The role of structural heterogeneity in the homodimerization of transmembrane proteins

The equilibrium association of transmembrane proteins plays a fundamental role in membrane protein function and cellular signaling. While the study of the equilibrium binding of single pass transmembrane proteins has received significant attention in experiment and simulation, the accurate assessment of equilibrium association constants remains a challenge to experiment and simulation. In experiment, there remain wide variations in association constants derived from experimental studies of the most widely studied transmembrane proteins. In simulation, state-of-the art methods have failed to adequately sample the thermodynamically relevant structures of the dimer state ensembles using coarse-grained models. In addition, all-atom force fields often fail to accurately assess the relative free energies of the dimer and monomer states. Given the importance of this fundamental biophysical process, it is essential to address these shortcomings. In this work, we establish an effective computational protocol for the calculation of equilibrium association constants for transmembrane homodimer formation. A set of transmembrane protein homodimers, used in the parameterization of the MARTINI v3 force field, are simulated using metadynamics, based on three collective variables. The method is found to be accurate and computationally efficient, providing a standard to be used in the future simulation studies using coarse-grained or all-atom models.

Transmembrane dimers of type 1 receptors sample alternate configurations: MD simulations using coarse grain Martini 3 versus AlphaFold2 Multimer

Structures and dynamics of transmembrane (TM) receptor regions are key to understanding their signaling mechanism across membranes. Here we examine configurations of TM region dimers, assembled using the recent Martini 3 force field for coarse-grain (CG) molecular dynamics simulations. At first glance, our results show only a reasonable agreement with ab initio predictions using PREDDIMER and AlphaFold2 Multimer and with nuclear magnetic resonance (NMR)-derived structures. 5 of 11 CG TM structures are similar to the NMR structures (within <3.5 Å root-mean-square deviation [RMSD]) compared with 10 and 9 using PREDDIMER and AlphaFold2, respectively (with 8 structures of the later within 1.5 Å). Surprisingly, AlphaFold2 predictions are closer to NMR structures when the 2001 instead of 2020 database is used for training. The CG simulations reveal that alternative configurations of TM dimers readily interconvert with a predominant population. The implications for transmembrane signaling are discussed, including for the development of peptide-based pharmaceuticals.

Pseudomonas aeruginosa responds to altered membrane phospholipid composition by adjusting the production of two-component systems, proteases and iron uptake proteins

Membrane protein and phospholipid (PL) composition changes in response to environmental cues and during infections. To achieve these, bacteria use adaptation mechanisms involving covalent modification and remodelling of the acyl chain length of PLs. However, little is known about bacterial pathways regulated by PLs. Here, we investigated proteomic changes in the biofilm of P. aeruginosa phospholipase mutant (∆plaF) with altered membrane PL composition. The results revealed profound alterations in the abundance of many biofilm-related two-component systems (TCSs), including accumulation of PprAB, a key regulator of the transition to biofilm. Furthermore, a unique phosphorylation pattern of transcriptional regulators, transporters and metabolic enzymes, as well as differential production of several proteases, in ∆plaF, indicate that PlaF-mediated virulence adaptation involves complex transcriptional and posttranscriptional response. Moreover, proteomics and biochemical assays revealed the depletion of pyoverdine-mediated iron uptake pathway proteins in ∆plaF, while proteins from alternative iron-uptake systems were accumulated. These suggest that PlaF may function as a switch between different iron-acquisition pathways. The observation that PL-acyl chain modifying and PL synthesis enzymes were overproduced in ∆plaF reveals the interconnection of degradation, synthesis and modification of PLs for proper membrane homeostasis. Although the precise mechanism by which PlaF simultaneously affects multiple pathways remains to be elucidated, we suggest that alteration of PL composition in ∆plaF plays a role for the global adaptive response in P. aeruginosa mediated by TCSs and proteases. Our study revealed the global regulation of virulence and biofilm by PlaF and suggests that targeting this enzyme may have therapeutic potential.

Scaling Protein-Water Interactions in the Martini 3 Coarse-Grained Force Field to Simulate Transmembrane Helix Dimers in Different Lipid Environments

Martini 3, the latest version of the widely used Martini force field for coarse-grained molecular dynamics simulations, is a promising tool to investigate proteins in phospholipid bilayers. However, simulating other lipid environments, such as detergent micelles, presents challenges due to the absence of validated parameters for their constituent molecules. Here, we propose parameters for the micelle-forming surfactant, dodecylphosphocholine (DPC). These result in micelle assembly with aggregation numbers in agreement with the experimental values. However, we identified a lack of hydrophobic interactions between transmembrane helix protein dimers and the tails of DPC molecules, preventing insertion and stabilization of the protein in the micelles. This problem was also observed for protein insertion by self-assembling 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) or dipalmitoylphosphatidylcholine (DPPC) bilayers. We propose the reduction of the nonbonded interactions between protein and water beads by 10% as a simple and effective solution to this problem that enables protein encapsulation in phospholipid micelles and bilayers without altering protein dimerization or the bilayer structure.

Towards de novo design of transmembrane α-helical assemblies using structural modelling and molecular dynamics simulation

Computational de novo protein design involves iterative processes consisting of amino acid sequence design, structural modelling and scoring, and design validation by synthesis and experimental characterisation. Recent advances in protein structure prediction and modelling methods have enabled the highly efficient and accurate design of water-soluble proteins. However, the design of membrane proteins remains a major challenge. To advance membrane protein design, considering the higher complexity of membrane protein folding, stability, and dynamic interactions between water, ions, lipids, and proteins is an important task. For introducing explicit solvents and membranes to these design methods, all-atom molecular dynamics (MD) simulations of designed proteins provide useful information that cannot be obtained experimentally. In this review, we first describe two major approaches to designing transmembrane α-helical assemblies, consensus and de novo design. We further illustrate recent MD studies of membrane protein folding related to protein design, as well as advanced treatments in molecular models and conformational sampling techniques in the simulations. Finally, we discuss the possibility to introduce MD simulations after the existing static modelling and screening of design decoys as an additional step for refinement of the design, which considers membrane protein folding dynamics and interactions with explicit membranes.

The impact of bilayer composition on the dimerization properties of the Slg1 stress sensor TMD from a multiscale analysis

The impact of mutual interactions between the transmembrane domains of membrane proteins and lipids on bilayer properties has gained major attraction. Most simulation studies of membranes rely on the Martini force field, which has proven extremely helpful in providing molecular insights into realistic systems. Accordingly, an evaluation of the accuracy of the Martini force field is crucial to be able to correctly interpret the reported data. In this study, we combine atomistic and coarse-grained Martini simulations to investigate the properties of transmembrane domains (TMDs) in a model yeast membrane. The results show that the TMD binding state (monomeric and dimeric with positive or negative crossing angle) and the membrane composition significantly influence the properties around the TMDs and change TMD-TMD and TMD-lipid affinities. Furthermore, ergosterol (ERG) exhibits a strong affinity to TMD dimers. Importantly, the right-handed TMD dimer configuration is stabilized via TMD-TMD contacts by the addition of asymmetric anionic phosphatidylserine (PS). The coarse-grained simulations corroborate many of these findings, with two notable exceptions: a systematic overestimation of TMD-ERG interaction and lack of stabilization of the right-handed TMD dimers with the addition of PS.

On Computing Equilibrium Binding Constants for Protein-Protein Association in Membranes

Protein association in lipid membranes is fundamental to membrane protein function and of great biomedical relevance. All-atom and coarse-grained models have been extensively used to understand the protein-protein interactions in the membrane and to compute equilibrium association constants. However, slow translational and rotational diffusion of protein in membrane presents challenges to the effective sampling of conformations defining the ensembles of free and bound states contributing to the association equilibrium and the free energy of dimerization. We revisit the homodimerization equilibrium of the TM region of glycophorin A. Conformational sampling is performed using umbrella sampling along previously proposed one-dimensional collective variables and compared with sampling over a two-dimensional collective variable space using the MARTINI v2.2 force field. We demonstrate that the one-dimensional collective variables suffer from restricted sampling of the native homodimer conformations leading to a biased free energy landscape. Conversely, simulations along the two-dimensional collective variable effectively characterize the thermodynamically relevant native and non-native interactions contributing to the association equilibrium. These results demonstrate the challenges associated with accurately characterizing binding equilibria when multiple poses contribute to the bound state ensemble.

Lipid-Mediated Association of the Slg1 Transmembrane Domains in Yeast Plasma Membranes

Clustering of transmembrane proteins underlies a multitude of fundamental biological processes at the plasma membrane (PM) such as receptor activation, lateral domain formation, and mechanotransduction. The self-association of the respective transmembrane domains (TMDs) has also been suggested to be responsible for the micron-scaled patterns seen for integral membrane proteins in the budding yeast PM. However, the underlying interplay between the local lipid composition and the TMD identity is still not mechanistically understood. In this work, we combined coarse-grained molecular dynamics simulations of simplified bilayer systems with high-resolution live-cell microscopy to analyze the distribution of a representative helical yeast TMD from the PM sensor Slg1 within different lipid environments. In our simulations, we specifically evaluated the effects of acyl chain saturation and anionic lipid head groups on the association of two TMDs. We found that weak lipid-protein interactions significantly affect the configuration of TMD dimers and the free energy of association. Increased amounts of unsaturated phospholipids (PLs) strongly reduced the helix-helix interaction, while the presence of anionic phosphatidylserine (PS) hardly affected the dimer formation. We could experimentally confirm this surprising lack of effect of PS using the network factor, a mesoscopic measure of PM pattern formation in yeast cells. Simulations also showed that the formation of TMD dimers in turn increased the order parameter of the surrounding lipids and induced long-range perturbations in lipid organization. In summary, our results shed new light on the mechanisms of lipid-mediated dimerization of TMDs in complex lipid mixtures.

Investigating the Conformational Dynamics of a Y-Family DNA Polymerase during Its Folding and Binding to DNA and a Nucleotide

During DNA polymerization, the Y-family DNA polymerases are capable of bypassing various DNA damage, which can stall the replication fork progression. It has been well acknowledged that the structures of the Y-family DNA polymerases have been naturally evolved to undertake this vital task. However, the mechanisms of how these proteins utilize their unique structural and conformational dynamical features to perform the translesion DNA synthesis are less understood. Here, we developed structure-based models to study the precatalytic DNA polymerization process, including DNA and nucleotide binding to DPO4, a paradigmatic Y-family polymerase from Sulfolobus solfataricus. We studied the interplay between the folding and the conformational dynamics of DPO4 and found that DPO4 undergoes first unraveling (unfolding) and then folding for accomplishing the functional "open-to-closed" conformational transition. DNA binding dynamically modulates the conformational equilibrium in DPO4 during the stepwise binding through different types of interactions, leading to different conformational distributions of DPO4 at different DNA binding stages. We observed that nucleotide binding induces modulation of a few contacts surrounding the active site of the DPO4-DNA complex associated with a high free energy barrier. Our simulation results resonate with the experimental evidence that the conformational change at the active site led by nucleotide is the rate-limiting step of nucleotide incorporation. In combination with localized frustration analyses, we underlined the importance of DPO4 conformational dynamics and fluctuations in facilitating DNA and nucleotide binding. Our findings offer mechanistic insights into the processes of DPO4 conformational dynamics associated with the substrate binding and contribute to the understanding of the "structure-dynamics-function" relationship in the Y-family DNA polymerases.

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.

Structural and Functional Insights into the Transmembrane Domain Association of Eph Receptors

Eph receptors are the largest family of receptor tyrosine kinases and by interactions with ephrin ligands mediate a myriad of processes from embryonic development to adult tissue homeostasis. The interaction of Eph receptors, especially at their transmembrane (TM) domains is key to understanding their mechanism of signal transduction across cellular membranes. We review the structural and functional aspects of EphA1/A2 association and the techniques used to investigate their TM domains: NMR, molecular modelling/dynamics simulations and fluorescence. We also introduce transmembrane peptides, which can be used to alter Eph receptor signaling and we provide a perspective for future studies.

Conformational Clamping by a Membrane Ligand Activates the EphA2 Receptor

The EphA2 receptor is a promising drug target for cancer treatment, since EphA2 activation can inhibit metastasis and tumor progression. It has been recently described that the TYPE7 peptide activates EphA2 using a novel mechanism that involves binding to the single transmembrane domain of the receptor. TYPE7 is a conditional transmembrane (TM) ligand, which only inserts into membranes at neutral pH in the presence of the TM region of EphA2. However, how membrane interactions can activate EphA2 is not known. We systematically altered the sequence of TYPE7 to identify the binding motif used to activate EphA2. With the resulting six peptides, we performed biophysical and cell migration assays that identified a new potent peptide variant. We also performed a mutational screen that determined the helical interface that mediates dimerization of the TM domain of EphA2 in cells. These results, together with molecular dynamic simulations, allowed to elucidate the molecular mechanism that TYPE7 uses to activate EphA2, where the membrane peptide acts as a molecular clamp that wraps around the TM dimer of the receptor. We propose that this binding mode stabilizes the active conformation of EphA2. Our data, additionally, provide clues into the properties that TM ligands need to have in order to achieve activation of membrane receptors.

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.

Martini 3: a general purpose force field for coarse-grained molecular dynamics

The coarse-grained Martini force field is widely used in biomolecular simulations. Here we present the refined model, Martini 3 ( http://cgmartini.nl ), with an improved interaction balance, new bead types and expanded ability to include specific interactions representing, for example, hydrogen bonding and electronic polarizability. The updated model allows more accurate predictions of molecular packing and interactions in general, which is exemplified with a vast and diverse set of applications, ranging from oil/water partitioning and miscibility data to complex molecular systems, involving protein-protein and protein-lipid interactions and material science applications as ionic liquids and aedamers.

Atomistic mechanism of transmembrane helix association

Transmembrane helix association is a fundamental step in the folding of helical membrane proteins. The prototypical example of this association is formation of the glycophorin dimer. While its structure and stability have been well-characterized experimentally, the detailed assembly mechanism is harder to obtain. Here, we use all-atom simulations within phospholipid membrane to study glycophorin association. We find that initial association results in the formation of a non-native intermediate, separated by a significant free energy barrier from the dimer with a native binding interface. We have used transition-path sampling to determine the association mechanism. We find that the mechanism of the initial bimolecular association to form the intermediate state can be mediated by many possible contacts, but seems to be particularly favoured by formation of non-native contacts between the C-termini of the two helices. On the other hand, the contacts which are key to determining progression from the intermediate to the native state are those which define the native binding interface, reminiscent of the role played by native contacts in determining folding of globular proteins. As a check on the simulations, we have computed association and dissociation rates from the transition-path sampling. We obtain results in reasonable accord with available experimental data, after correcting for differences in native state stability. Our results yield an atomistic description of the mechanism for a simple prototype of helical membrane protein folding.

Many important cellular functions are performed by membrane proteins, and in particular by association of proteins via transmembrane helices. However, the mechanism of how the helices associate has been challenging to study, by either experiment or simulation. Here, we use advanced molecular simulation methods to overcome the slow time scales involved in helix association and dissociation and obtain a view of the association mechanism in atomic detail. We show that association occurs via an initially non-native dimer, before proceeding to the native state, and we validate our results by comparison to available experimental kinetic data. Our methods will also aid in the study of the assembly mechanism of larger transmembrane proteins via molecular simulation.

Inserting Small Molecules across Membrane Mixtures: Insight from the Potential of Mean Force

Small solutes have been shown to alter the lateral organization of cell membranes and reconstituted phospholipid bilayers; however, the mechanisms by which these changes happen are still largely unknown. Traditionally, both experiment and simulation studies have been restricted to testing only a few compounds at a time, failing to identify general molecular descriptors or chemical properties that would allow extrapolating beyond the subset of considered solutes. In this work, we probe the competing energetics of inserting a solute in different membrane environments by means of the potential of mean force. We show that these calculations can be used as a computationally efficient proxy to establish whether a solute will stabilize or destabilize domain phase separation. Combined with umbrella-sampling simulations and coarse-grained molecular dynamics simulations, we are able to screen solutes across a wide range of chemistries and polarities. Our results indicate that for the system under consideration, preferential partitioning and therefore effectiveness in altering membrane phase separation are strictly linked to the location of insertion in the bilayer (i.e., midplane or interface). Our approach represents a fast and simple tool for obtaining structural and thermodynamic insight into the partitioning of small molecules between lipid domains and its relation to phase separation, ultimately providing a platform for identifying the key determinants of this process.

Cutting antiparallel DNA strands in a single active site

A single enzyme active site that catalyzes multiple reactions is a well-established biochemical theme, but how one nuclease site cleaves both DNA strands of a double helix has not been well understood. In analyzing site-specific DNA cleavage by the mammalian RAG1-RAG2 recombinase, which initiates V(D)J recombination, we find that the active site is reconfigured for the two consecutive reactions and the DNA double helix adopts drastically different structures. For initial nicking of the DNA, a locally unwound and unpaired DNA duplex forms a zipper via alternating interstrand base stacking, rather than melting as generally thought. The second strand cleavage and formation of a hairpin-DNA product requires a global scissor-like movement of protein and DNA, delivering the scissile phosphate into the rearranged active site.

Role of the N-Terminal Transmembrane Helix Contacts in the Activation of FGFR3

Fibroblast growth factor receptor 3 (FGFR3) is a member of receptor tyrosine kinases, which is involved in skeletal cell growth, differentiation, and migration. FGFR3 transduces biochemical signals from the extracellular ligand-binding domain to the intracellular kinase domain through the conformational changes of the transmembrane (TM) helix dimer. Here, we apply generalized replica exchange with solute tempering method to wild type (WT) and G380R mutant (G380R) of FGFR3. The dimer interface in G380R is different from WT and the simulation results are in good agreement with the solid-state nuclear magnetic resonance (NMR) spectroscopy. TM helices in G380R are extended more than WT, and thereby, G375 in G380R contacts near the N-termini of the TM helix dimer. Considering that both G380R and G375C show the constitutive activation, the formation of the N-terminal contacts of the TM helices can be generally important for the activation mechanism. © 2019 Wiley Periodicals, Inc.

Accelerating Membrane Simulations with Hydrogen Mass Repartitioning

The time step of atomistic molecular dynamics (MD) simulations is determined by the fastest motions in the system and is typically limited to 2 fs. An increasingly popular approach is to increase the mass of the hydrogen atoms to ∼3 amu and decrease the mass of the parent atom by an equivalent amount. This approach, known as hydrogen-mass repartitioning (HMR), permits time steps up to 4 fs with reasonable simulation stability. While HMR has been applied in many published studies to date, it has not been extensively tested for membrane-containing systems. Here, we compare the results of simulations of a variety of membranes and membrane-protein systems run using a 2 fs time step and a 4 fs time step with HMR. For pure membrane systems, we find almost no difference in structural properties, such as area-per-lipid, electron density profiles, and order parameters, although there are differences in kinetic properties such as the diffusion constant. Conductance through a porin in an applied field, partitioning of a small peptide, hydrogen-bond dynamics, and membrane mixing show very little dependence on HMR and the time step. We also tested a 9 Å cutoff as compared to the standard CHARMM cutoff of 12 Å, finding significant deviations in many properties tested. We conclude that HMR is a valid approach for membrane systems, but a 9 Å cutoff is not.

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.

Integrated Functions of Membrane Property Sensors and a Hidden Side of the Unfolded Protein Response

Eukaryotic cells face the challenge of maintaining the complex composition of several coexisting organelles. The molecular mechanisms underlying the homeostasis of subcellular membranes and their adaptation during stress are only now starting to emerge. Here, we discuss three membrane property sensors of the endoplasmic reticulum (ER), namely OPI1, MGA2, and IRE1, each controlling a large cellular program impacting the lipid metabolic network. OPI1 coordinates the production of membrane and storage lipids, MGA2 regulates the production of unsaturated fatty acids required for membrane biogenesis, and IRE1 controls the unfolded protein response (UPR) to adjust ER size, protein folding, and the secretory capacity of the cell. Although these proteins use remarkably distinct sensing mechanisms, they are functionally connected via the ER membrane and cooperate to maintain membrane homeostasis. As a rationalization of the recently described mechanism of UPR activation by lipid bilayer stress, we propose that IRE1 can sense the protein-to-lipid ratio in the ER membrane to ensure a balanced production of membrane proteins and lipids.

Cholesterol Interaction Sites on the Transmembrane Domain of the Hedgehog Signal Transducer and Class F G Protein-Coupled Receptor Smoothened

Transduction of Hedgehog signals across the plasma membrane is facilitated by the class F G-protein-coupled-receptor (GPCR) Smoothened (SMO). Recent studies suggest that SMO is modulated via interactions of its transmembrane (TM) domain with cholesterol. We apply molecular dynamics simulations of SMO embedded in cholesterol containing lipid bilayers, revealing a direct interaction of cholesterol with the TM domain at regions distinct from those observed in class A GPCRs. In particular the extracellular tips of helices TM2 and TM3 form a well-defined cholesterol interaction site. Potential of mean force calculations yield a free energy landscape for cholesterol binding. Alongside analysis of equilibrium cholesterol occupancy, this reveals the existence of a dynamic "greasy patch" interaction with the TM domain of SMO, which may be compared with previously identified lipid interaction sites on other membrane proteins. These predictions provide molecular-level insights into cholesterol interactions with a class F GPCR, suggesting potential druggable sites.

Atomistic Force Fields for Proteins

All-atom, classical force fields for protein molecular dynamics (MD) simulations currently occupy a sweet spot in the universe of computational models, sufficiently detailed to be of predictive value in many cases, yet also simple enough that some biologically relevant time scales (microseconds or more) can now be sampled via specialized hardware or enhanced sampling methods. However, due to their long evolutionary history, there is now a myriad of force field branches in current use, which can make it hard for those entering the simulation field to know which would be the best set of parameters for a given application. In this chapter, I try to give an overview of the historical motivation for the different force fields available, suggestions for how to determine the most appropriate model and what to do if the results are in conflict with experimental evidence.

From Dynamics to Membrane Organization: Experimental Breakthroughs Occasion a "Modeling Manifesto"

New experimental techniques, especially in the context of observing molecular dynamics, reveal the plasma membrane to be heterogeneous and "scale rich," from nanometers to microns and from microseconds to seconds. This is critical information, which shows that scale-dependent transport governs the molecular encounters that underlie cellular signaling. The data are rich and reaffirm the importance of the cortical cytoskeleton, protein aggregates, and lipidomic complexity on the statistics of molecular encounters. Moreover, the data demand simulation approaches with a particular set of features, hence the "manifesto." Together with the experimental data, simulations that satisfy these requirements hold the promise of a deeper understanding of membrane spatiotemporal organization. Several experimental breakthroughs in measuring molecular membrane dynamics are reviewed, the constraints that they place on simulations are discussed, and the status of simulation approaches that aim to meet them are detailed.