Critical Comparison of Biomembrane Force Fields: Protein-Lipid Interactions at the Membrane Interface

Exploring the Properties of Curved Lipid Membranes: Comparative Analysis of Atomistic and Coarse-Grained Force Fields

Curvature emerges as a fundamental membrane characteristic crucial for diverse biological processes, including vesicle formation, cell signaling, and membrane trafficking. Increasingly valuable insights into atomistic details governing curvature-dependent membrane properties are provided by computer simulations. Nevertheless, the underlying force field models are conventionally calibrated and tested in relation to experimentally derived parameters of planar bilayers, thereby leaving uncertainties concerning their consistency in reproducing curved lipid systems. In this study we compare the depiction of buckled phosphatidylcholine (POPC) and POPC-cholesterol membranes by four popular force field models. Aside from agreement with respect to general trends in curvature dependence of a number of parameters, we observe a few qualitative differences. Among the most prominent ones is the difference between atomistic and coarse grained force fields in their representation of relative compressibility of the polar headgroup region and hydrophobic lipid core. Through a number of downstream effects, this discrepancy can influence the way in which curvature modulates the behavior of membrane bound proteins depending on the adopted simulation model.

Pathways to a Shiny Future: Building the Foundation for Computational Physical Chemistry and Biophysics in 2050

In the last quarter-century, the field of molecular dynamics (MD) has undergone a remarkable transformation, propelled by substantial enhancements in software, hardware, and underlying methodologies. In this Perspective, we contemplate the future trajectory of MD simulations and their possible look at the year 2050. We spotlight the pivotal role of artificial intelligence (AI) in shaping the future of MD and the broader field of computational physical chemistry. We outline critical strategies and initiatives that are essential for the seamless integration of such technologies. Our discussion delves into topics like multiscale modeling, adept management of ever-increasing data deluge, the establishment of centralized simulation databases, and the autonomous refinement, cross-validation, and self-expansion of these repositories. The successful implementation of these advancements requires scientific transparency, a cautiously optimistic approach to interpreting AI-driven simulations and their analysis, and a mindset that prioritizes knowledge-motivated research alongside AI-enhanced big data exploration. While history reminds us that the trajectory of technological progress can be unpredictable, this Perspective offers guidance on preparedness and proactive measures, aiming to steer future advancements in the most beneficial and successful direction.

Interaction of MRI Contrast Agent [Gd(DOTA)]- with Lipid Membranes: A Molecular Dynamics Study

Contrast agents are important imaging probes in clinical MRI, allowing the identification of anatomic changes that otherwise would not be possible. Intensive research on the development of new contrast agents is being made to image specific pathological markers or sense local biochemical changes. The most widely used MRI contrast agents are based on gadolinium(III) complexes. Due to their very high charge density, they have low permeability through tight biological barriers such as the blood-brain barrier, hampering their application in the diagnosis of neurological disorders. In this study, we explore the interaction between the widely used contrast agent [Gd(DOTA)]- (Dotarem) and POPC lipid bilayers by means of molecular dynamics simulations. This metal complex is a standard reference where several chemical modifications have been introduced to improve key properties such as bioavailability and targeting. The simulations unveil detailed insights into the agent's interaction with the lipid bilayer, offering perspectives beyond experimental methods. Various properties, including the impact on global and local bilayer properties, were analyzed. As expected, the results indicate a low partition coefficient (KP) and high permeation barrier for this reference compound. Nevertheless, favorable interactions are established with the membrane leading to moderately long residence times. While coordination of one inner-sphere water molecule is maintained for the membrane-associated chelate, the physical-chemical attributes of [Gd(DOTA)]- as a MRI contrast agent are affected. Namely, increases in the rotational correlation times and in the residence time of the inner-sphere water are observed, with the former expected to significantly increase the water proton relaxivity. This work establishes a reference framework for the use of simulations to guide the rational design of new contrast agents with improved relaxivity and bioavailability and for the development of liposome-based formulations for use as imaging probes or theranostic agents.

Improved Protein Model in SPICA Force Field

The previous version of the SPICA coarse-grained (CG) force field (FF) protein model focused primarily on membrane proteins and successfully reproduced the dimerization free energies of several transmembrane helices and the stable structures of various membrane protein assemblies. However, that model had limited accuracy when applied to other proteins, such as intrinsically disordered proteins (IDPs) and peripheral proteins, because the dimensions of the IDPs in an aqueous solution were too compact, and protein binding on the lipid membrane surface was overstabilized. To improve the accuracy of the SPICA FF model for the simulation of such systems, in this study, we introduce protein secondary structure-dependent nonbonded interaction parameters to the backbone segments and reoptimize almost all nonbonded parameters for amino acids. The improved FF proposed here successfully reproduces the radii of gyration of various IDPs, the binding sensitivity of several peripheral membrane proteins, and the dimerization free energies of several transmembrane helices. The new model also shows improved agreement with experiments on the free energy of peptide association in water. In addition, an extensive library of nonbonded interactions between proteins and lipids, including various glycerophospholipids, sphingolipids, and cholesterol, allows the study of specific interactions between lipids and peripheral and transmembrane proteins. Hence, the new SPICA FF (version 2) proposed herein is applicable with high accuracy for simulating a wide range of protein systems.

Deep Learning Dynamic Allostery of G-Protein-Coupled Receptors

G-protein-coupled receptors (GPCRs) make up the largest superfamily of human membrane proteins and represent primary targets of ∼1/3 of currently marketed drugs. Allosteric modulators have emerged as more selective drug candidates compared with orthosteric agonists and antagonists. However, many X-ray and cryo-EM structures of GPCRs resolved so far exhibit negligible differences upon the binding of positive and negative allosteric modulators (PAMs and NAMs). The mechanism of dynamic allosteric modulation in GPCRs remains unclear. In this work, we have systematically mapped dynamic changes in free energy landscapes of GPCRs upon binding of allosteric modulators using the Gaussian accelerated molecular dynamics (GaMD), deep learning (DL), and free energy prOfiling Workflow (GLOW). GaMD simulations were performed for a total of 66 μs on 44 GPCR systems in the presence and absence of the modulator. DL and free energy calculations revealed significantly reduced dynamic fluctuations and conformational space of GPCRs upon modulator binding. While the modulator-free GPCRs often sampled multiple low-energy conformational states, the NAMs and PAMs confined the inactive and active agonist-G-protein-bound GPCRs, respectively, to mostly only one specific conformation for signaling. Such cooperative effects were significantly reduced for binding of the selective modulators to "non-cognate" receptor subtypes. Therefore, GPCR allostery exhibits a dynamic "conformational selection" mechanism. In the absence of available modulator-bound structures as for most current GPCRs, it is critical to use a structural ensemble of representative GPCR conformations rather than a single structure for compound docking ("ensemble docking"), which will potentially improve structure-based design of novel allosteric drugs of GPCRs.

Humanization and characterization of a murine monoclonal neutralizing antibody against human adenovirus 7

Human adenovirus type 7 (HAdV7) is commonly associated with febrile acute respiratory disease (ARD) outbreaks. We have reported that 10G12, a mouse monoclonal antibody (mAb) specifically recognizing and neutralizing HAdV7, is a promising candidate for humanization. In this study, we engineered the six variants of 10G12 with increased degree of humanization and investigated their biological activity. The humanized monoclonal antibody (mAb) 10G12-M2 was shown to retain the parental antibody's high binding affinity, specificity and potent efficacy of viral suppression. The mAb 10G12-M2 recognized a conformational neutralization epitope of the hexon protein. Complex structure-based molecular docking simulation showed that the hexon protein formed several interactions with 10G12-M2, including hydrogen bonds and salt bridges interaction. Physicochemical properties analysis of 10G12-M2 demonstrated that it is stable and desirable lead candidate. In general, 10G12-M2 had excellent biological activity after humanization combined with the potential for use in prophylactic or therapeutic applications against HAdV7.

Computer Aided Development of Nucleic Acid Applications in Nanotechnologies

Utilization of nucleic acids (NAs) in nanotechnologies and nanotechnology-related applications is a growing field with broad application potential, ranging from biosensing up to targeted cell delivery. Computer simulations are useful techniques that can aid design and speed up development in this field. This review focuses on computer simulations of hybrid nanomaterials composed of NAs and other components. Current state-of-the-art molecular dynamics simulations, empirical force fields (FFs), and coarse-grained approaches for the description of deoxyribonucleic acid and ribonucleic acid are critically discussed. Challenges in combining biomacromolecular and nanomaterial FFs are emphasized. Recent applications of simulations for modeling NAs and their interactions with nano- and biomaterials are overviewed in the fields of sensing applications, targeted delivery, and NA templated materials. Future perspectives of development are also highlighted.

A Single Point Mutation Blocks the Entrance of Ligands to the Cannabinoid CB2 Receptor via the Lipid Bilayer

Molecular dynamic (MD) simulations have become a common tool to study the pathway of ligand entry to the orthosteric binding site of G protein-coupled receptors. Here, we have combined MD simulations and site-directed mutagenesis to study the binding process of the potent JWH-133 agonist to the cannabinoid CB₂ receptor (CB₂R). In CB₂R, the N-terminus and extracellular loop 2 fold over the ligand binding pocket, blocking access to the binding cavity from the extracellular environment. We, thus, hypothesized that the binding pathway is a multistage process consisting of the hydrophobic ligand diffusing in the lipid bilayer to contact a lipid-facing vestibule, from which the ligand enters an allosteric site inside the transmembrane bundle through a tunnel formed between TMs 1 and 7 and finally moving from the allosteric to the orthosteric binding cavity. This pathway was experimentally validated by the Ala282^7.36Phe mutation that blocks the entrance of the ligand, as JWH-133 was not able to decrease the forskolin-induced cAMP levels in cells expressing the mutant receptor. This proposed ligand entry pathway defines transient binding sites that are potential cavities for the design of synthetic modulators.

Charged Small Molecule Binding to Membranes in MD Simulations Evaluated against NMR Experiments

Interactions of charged molecules with biomembranes regulate many of their biological activities, but their binding affinities to lipid bilayers are difficult to measure experimentally and model theoretically. Classical molecular dynamics (MD) simulations have the potential to capture the complex interactions determining how charged biomolecules interact with membranes, but systematic overbinding of sodium and calcium cations in standard MD simulations raises the question of how accurately force fields capture the interactions between lipid membranes and charged biomolecules. Here, we evaluate the binding of positively charged small molecules, etidocaine, and tetraphenylphosphonium to a phosphatidylcholine (POPC) lipid bilayer using the changes in lipid head-group order parameters. We observed that these molecules behave oppositely to calcium and sodium ions when binding to membranes: (i) their binding affinities are not overestimated by standard force field parameters, (ii) implicit inclusion of electronic polarizability increases their binding affinity, and (iii) they penetrate into the hydrophobic membrane core. Our results can be explained by distinct binding mechanisms of charged small molecules with hydrophobic moieties and monoatomic ions. The binding of the former is driven by hydrophobic effects, while the latter has direct electrostatic interactions with lipids. In addition to elucidating how different kinds of charged biomolecules bind to membranes, we deliver tools for further development of MD simulation parameters and methodology.

Not sorcery after all: Roles of multiple charged residues in membrane insertion of gasdermin-A3

Gasdermins execute programmatory cell death, known as pyroptosis, by forming medium-sized membrane pores. Recently, the molecular structure of those pores as well as the diversity in their shape and size have been revealed by cryoTEM and atomic force microscopy, respectively. Even though a growth of smaller to larger oligomers and reshaping from slits to rings could be documented, the initiation of the gasdermin pore formation remains a mystery. In one hypothesis, gasdermin monomers insert into membranes before associating into oligomeric pores. In the other hypothesis, gasdermin oligomers preassemble on the membrane surface prior to membrane insertion. Here, by studying the behavior of monomeric membrane-inserted gasdermin-A3 (GSDMA3), we unveil that a monomeric gasdermin prefers the membrane-adsorbed over the membrane-inserted state. Our results thus support the hypothesis of oligomers preassembling on the membrane surface before membrane penetration. At the same time, our simulations of small membrane-inserted arcs of GSDMA3 suggest that the inserting oligomer can be small and does not have to comprise a full ring of approximately 26-30 subunits. Moreover, our simulations have revealed an astonishingly large impact of salt-bridge formation and protein surroundings on the transmembrane passage of charged residues, reducing the energetic cost by up to 53% as compared to their free forms. The here observed free energy barrier of mere 5.6 kcal/mol for the membrane insertion of monomeric GSDMA3 explains the surprising ability of gasdermins to spontaneously self-insert into cellular membranes.

Gasdermin-A3 pore formation propagates along variable pathways

Gasdermins are main effectors of pyroptosis, an inflammatory form of cell death. Released by proteolysis, the N-terminal gasdermin domain assembles large oligomers to punch lytic pores into the cell membrane. While the endpoint of this reaction, the fully formed pore, has been well characterized, the assembly and pore-forming mechanisms remain largely unknown. To resolve these mechanisms, we characterize mouse gasdermin-A3 by high-resolution time-lapse atomic force microscopy. We find that gasdermin-A3 oligomers assemble on the membrane surface where they remain attached and mobile. Once inserted into the membrane gasdermin-A3 grows variable oligomeric stoichiometries and shapes, each able to open transmembrane pores. Molecular dynamics simulations resolve how the membrane-inserted amphiphilic β-hairpins and the structurally adapting hydrophilic head domains stabilize variable oligomeric conformations and open the pore. The results show that without a vertical collapse gasdermin pore formation propagates along a set of multiple parallel but connected reaction pathways to ensure a robust cellular response.

Molecular Dynamics Simulations of Transmembrane Cyclic Peptide Nanotubes Using Classical Force Fields, Hydrogen Mass Repartitioning, and Hydrogen Isotope Exchange Methods: A Critical Comparison

Self-assembled cyclic peptide nanotubes with alternating D- and L-amino acid residues in the sequence of each subunit have attracted a great deal of attention due to their potential for new nanotechnology and biomedical applications, mainly in the field of antimicrobial peptides. Molecular dynamics simulations can be used to characterize these systems with atomic resolution at different time scales, providing information that is difficult to obtain via wet lab experiments. However, the performance of classical force fields typically employed in the simulation of biomolecules has not yet been extensively tested with this kind of highly constrained peptide. Four different classical force fields (AMBER, CHARMM, OPLS, and GROMOS), using a nanotube formed by eight D,L-α-cyclic peptides inserted into a lipid bilayer as a model system, were employed here to fill this gap. Significant differences in the pseudo-cylindrical cavities formed by the nanotubes were observed, the most important being the diameter of the nanopores, the number and location of confined water molecules, and the density distribution of the solvent molecules. Furthermore, several modifications were performed on GROMOS54a7, aiming to explore acceleration strategies of the MD simulations. The hydrogen mass repartitioning (HMR) and hydrogen isotope exchange (HIE) methods were tested to slow down the fastest degrees of freedom. These approaches allowed a significant increase in the time step employed in the equation of the motion integration algorithm, from 2 fs up to 5-7 fs, with no serious changes in the structural and dynamical properties of the nanopores. Subtle differences with respect to the simulations with the unmodified force fields were observed in the concerted movements of the cyclic peptides, as well as in the lifetime of several H-bonds. All together, these results are expected to contribute to better understanding of the behavior of self-assembled cyclic peptide nanotubes, as well as to support the methods tested to speed up general MD simulations; additionally, they do provide a number of quantitative descriptors that are expected to be used as a reference to design new experiments intended to validate and complement computational studies of antimicrobial cyclic peptides.

Spontaneous local membrane curvature induced by transmembrane proteins

The (local) curvature of cellular membranes acts as a driving force for the targeting of membrane-associated proteins to specific membrane domains, as well as a sorting mechanism for transmembrane proteins, e.g., by accumulation in regions of matching spontaneous curvature. The latter measure was previously experimentally employed to study the curvature induced by the potassium channel KvAP and by aquaporin AQP0. However, the direction of the reported spontaneous curvature levels as well as the molecular driving forces governing the membrane curvature induced by these integral transmembrane proteins could not be addressed experimentally. Here, using both coarse-grained and atomistic molecular dynamics (MD) simulations, we report induced spontaneous curvature values for the homologous potassium channel Kv 1.2/2.1 Chimera (KvChim) and AQP0 embedded in unrestrained lipid bicelles that are in very good agreement with experiment. Importantly, the direction of curvature could be directly assessed from our simulations: KvChim induces a strong positive membrane curvature (≈0.036 nm^-1) whereas AQP0 causes a comparably small negative curvature (≈-0.019 nm^-1). Analyses of protein-lipid interactions within the bicelle revealed that the potassium channel shapes the surrounding membrane via structural determinants. Differences in shape of the protein-lipid interface of the voltage-gating domains between the extracellular and cytosolic membrane leaflets induce membrane stress and thereby promote a protein-proximal membrane curvature. In contrast, the water pore AQP0 displayed a high structural stability and an only faint effect on the surrounding membrane environment that is connected to its wedge-like shape.

Variability in the Spatial Structure of the Central Loop in Cobra Cytotoxins Revealed by X-ray Analysis and Molecular Modeling

Cobra cytotoxins (CTs) belong to the three-fingered protein family and possess membrane activity. Here, we studied cytotoxin 13 from Naja naja cobra venom (CT13Nn). For the first time, a spatial model of CT13Nn with both “water” and “membrane” conformations of the central loop (loop-2) were determined by X-ray crystallography. The “water” conformation of the loop was frequently observed. It was similar to the structure of loop-2 of numerous CTs, determined by either NMR spectroscopy in aqueous solution, or the X-ray method. The “membrane” conformation is rare one and, to date has only been observed by NMR for a single cytotoxin 1 from N. oxiana (CT1No) in detergent micelle. Both CT13Nn and CT1No are S-type CTs. Membrane-binding of these CTs probably involves an additional step—the conformational transformation of the loop-2. To confirm this suggestion, we conducted molecular dynamics simulations of both CT1No and CT13Nn in the Highly Mimetic Membrane Model of palmitoiloleoylphosphatidylglycerol, starting with their “water” NMR models. We found that the both toxins transform their “water” conformation of loop-2 into the “membrane” one during the insertion process. This supports the hypothesis that the S-type CTs, unlike their P-type counterparts, require conformational adaptation of loop-2 during interaction with lipid membranes.

How well does molecular simulation reproduce environment-specific conformations of the intrinsically disordered peptides PLP, TP2 and ONEG?

Understanding the conformational ensembles of intrinsically disordered proteins and peptides (IDPs) in their various biological environments is essential for understanding their mechanisms and functional roles in the proteome, leading to a greater knowledge of, and potential treatments for, a broad range of diseases. To determine whether molecular simulation is able to generate accurate conformational ensembles of IDPs, we explore the structural landscape of the PLP peptide (an intrinsically disordered region of the proteolipid membrane protein) in aqueous and membrane-mimicking solvents, using replica exchange with solute scaling (REST2), and examine the ability of four force fields (ff14SB, ff14IDPSFF, CHARMM36 and CHARMM36m) to reproduce literature circular dichroism (CD) data. Results from variable temperature (VT) 1H and Rotating frame Overhauser Effect SpectroscopY (ROESY) nuclear magnetic resonance (NMR) experiments are also presented and are consistent with the structural observations obtained from the simulations and CD. We also apply the optimum simulation protocol to TP2 and ONEG (a cell-penetrating peptide (CPP) and a negative control peptide, respectively) to gain insight into the structural differences that may account for the observed difference in their membrane-penetrating abilities. Of the tested force fields, we find that CHARMM36 and CHARMM36m are best suited to the study of IDPs, and accurately predict a disordered to helical conformational transition of the PLP peptide accompanying the change from aqueous to membrane-mimicking solvents. We also identify an α-helical structure of TP2 in the membrane-mimicking solvents and provide a discussion of the mechanistic implications of this observation with reference to the previous literature on the peptide. From these results, we recommend the use of CHARMM36m with the REST2 protocol for the study of environment-specific IDP conformations. We believe that the simulation protocol will allow the study of a broad range of IDPs that undergo conformational transitions in different biological environments.

Biosafety-inspired structural optimization of triazolium ionic liquids based on structure-toxicity relationships

Ionic liquids (ILs), owing to their low vapor pressure and excellent solvating ability, are being increasingly applied in various industries to replace highly toxic organic solvents. They mainly pollute aquatic environment and soils, directly endangering eco-environment and human health. Therefore, it is critical to understand and optimize structural motifs of ILs with reduced toxicity. Considering human oral exposure is the major route, our investigations employed a human cell panel (modeling oral exposures) including human stomach (GES-1), intestinal (FHC), liver (HepG2) and kidney (HEK293) cells using a series of experimental and computational approaches to explore the cytotoxicity and molecular mechanism of ILs. We discovered that the cytotoxicity of triazolium and imidazolium ILs was human cell line-dependent with cytotoxicity in an order of FHC > GES-1 > HepG2 > HEK293. For this reason, a toxicity assay using a single cell line was highly inappropriate. Compared to anions (Br^-, OTs^-, OTMBS^-) we tested, the cation of ILs played a major role in causing cytotoxicity. Ionic liquids with cations having longer hydrophobic sidechains (IL09 vs. IL01) readily insert into cell membranes with enhanced membrane and lipidomic perturbations, induce cytotoxicity by triggering cell cycle arrest and apoptosis. Reducing sidechain length and incorporating three nitrogen atoms (triazolium) instead of two (imidazolium) in the cation core alleviated cytotoxicity by reducing cell membrane perturbations and cell function interference. These findings provide important guiding principles for the design of the next-generation of "green" and safe ILs.

Lipids and Phosphorylation Conjointly Modulate Complex Formation of β2-Adrenergic Receptor and β-arrestin2

G protein-coupled receptors (GPCRs) are the largest class of human membrane proteins that bind extracellular ligands at their orthosteric binding pocket to transmit signals to the cell interior. Ligand binding evokes conformational changes in GPCRs that trigger the binding of intracellular interaction partners (G proteins, G protein kinases, and arrestins), which initiate diverse cellular responses. It has become increasingly evident that the preference of a GPCR for a certain intracellular interaction partner is modulated by a diverse range of factors, e.g., ligands or lipids embedding the transmembrane receptor. Here, by means of molecular dynamics simulations of the β₂-adrenergic receptor and β-arrestin2, we study how membrane lipids and receptor phosphorylation regulate GPCR-arrestin complex conformation and dynamics. We find that phosphorylation drives the receptor’s intracellular loop 3 (ICL3) away from a native negatively charged membrane surface to interact with arrestin. If the receptor is embedded in a neutral membrane, the phosphorylated ICL3 attaches to the membrane surface, which widely opens the receptor core. This opening, which is similar to the opening in the G protein-bound state, weakens the binding of arrestin. The loss of binding specificity is manifested by shallower arrestin insertion into the receptor core and higher dynamics of the receptor-arrestin complex. Our results show that receptor phosphorylation and the local membrane composition cooperatively fine-tune GPCR-mediated signal transduction. Moreover, the results suggest that deeper understanding of complex GPCR regulation mechanisms is necessary to discover novel pathways of pharmacological intervention.

Monitoring the binding and insertion of a single transmembrane protein by an insertase

Cells employ highly conserved families of insertases and translocases to insert and fold proteins into membranes. How insertases insert and fold membrane proteins is not fully known. To investigate how the bacterial insertase YidC facilitates this process, we here combine single-molecule force spectroscopy and fluorescence spectroscopy approaches, and molecular dynamics simulations. We observe that within 2 ms, the cytoplasmic α-helical hairpin of YidC binds the polypeptide of the membrane protein Pf3 at high conformational variability and kinetic stability. Within 52 ms, YidC strengthens its binding to the substrate and uses the cytoplasmic α-helical hairpin domain and hydrophilic groove to transfer Pf3 to the membrane-inserted, folded state. In this inserted state, Pf3 exposes low conformational variability such as typical for transmembrane α-helical proteins. The presence of YidC homologues in all domains of life gives our mechanistic insight into insertase-mediated membrane protein binding and insertion general relevance for membrane protein biogenesis.

Inside and Out of the Pore: Comparing Interactions and Molecular Dynamics of Influenza A M2 Viroporin Complexes in Standard Lipid Bilayers

Ion channels located at viral envelopes (viroporins) have a critical function for the replication of infectious viruses and are important drug targets. Over the last decade, the number and duration of molecular dynamics (MD) simulations of the influenza A M2 ion channel owing to the increased computational efficiency. Here, we aimed to define the system setup and simulation conditions for the correct description of the protein-pore and the protein-lipid interactions for influenza A M2 in comparison with experimental data. We performed numerous MD simulations of the influenza A M2 protein in complex with adamantane blockers in standard lipid bilayers using OPLS2005 and CHARMM36 (C36) force fields. We explored the effect of varying the M2 construct (M2(22-46) and M2(22-62)), the lipid buffer size and type (stiffer DMPC or softer POPC with or without 20% cholesterol), the simulation time, the H37 protonation site (N_δ or Ν_ε), the conformational state of the W41 channel gate, and M2's cholesterol binding sites (BSs). We report that the 200 ns MD with M2(22-62) (having N_ε Η37) in the 20 Å lipid buffer with the C36 force field accurately describe: (a) the M2 pore structure and interactions inside the pore, that is, adamantane channel blocker location, water clathrate structure, and water or chloride anion blockage/passage from the M2 pore in the presence of a channel blocker and (b) interactions between M2 and the membrane environment as reflected by the calculation of the M2 bundle tilt, folding of amphipathic helices, and cholesterol BSs. Strikingly, we also observed that the C36 1 μs MD simulations using M2(22-62) embedded in a 20 Å POPC:cholesterol (5:1) scrambled membrane produced frequent interactions with cholesterol, which when combined with computational kinetic analysis, revealed the experimentally observed BSs of cholesterol and suggested three similarly long-interacting positions in the top leaflet that have previously not been observed experimentally. These findings promise to be useful for other viroporin systems.

Accurate Binding Configuration Prediction of a G-Protein-Coupled Receptor to Its Antagonist Using Multicanonical Molecular Dynamics-Based Dynamic Docking

We have performed dynamic docking between a prototypic G-protein-coupled receptor (GPCR) system, the β₂-adrenergic receptor, and its antagonist, alprenolol, using one of the enhanced conformation sampling methods, multicanonical molecular dynamics (McMD), which does not rely on any prior knowledge for the definition of the reaction coordinate. Although we have previously applied our McMD-based dynamic docking protocol to various globular protein systems, its application to GPCR systems would be difficult because of their complicated design, which include a lipid bilayer, and because of the difficulty in sampling the configurational space of a binding site that exists deep inside the GPCR. Our simulations sampled a wide array of ligand-bound and ligand-unbound structures, and we measured 427 binding events during our 48 μs production run. Analysis of the ensemble revealed several stable and meta-stable structures, where the most stable structure at the global free energy minimum matches the experimental one. Additional canonical MD simulations were used for refinement and validation of the structures, revealing that most of the intermediates are sufficiently stable to trap the ligand in these intermediary states and furthermore validated our prediction results. Given the difficulty in reaching the orthosteric binding site, chemical optimization of the compound for the second ranking configuration, which binds near the pocket's entrance, might lead to a high-affinity allosteric inhibitor. Accordingly, we show that the application of our methodology can be used to provide crucial insights for the rational design of drugs that target GPCRs.

Effect of the Force Field on Molecular Dynamics Simulations of the Multidrug Efflux Protein P-Glycoprotein

Molecular dynamics (MD) simulations have been used extensively to study P-glycoprotein (P-gp), a flexible multidrug transporter that is a key player in the development of multidrug resistance to chemotherapeutics. A substantial body of literature has grown from simulation studies that have employed various simulation conditions and parameters, including AMBER, CHARMM, OPLS, GROMOS, and coarse-grained force fields, drawing conclusions from simulations spanning hundreds of nanoseconds. Each force field is typically parametrized and validated on different data and observables, usually of small molecules and peptides; there have been few comparisons of force field performance on large protein-membrane systems. Here we compare the conformational ensembles of P-gp embedded in a POPC/cholesterol bilayer generated over 500 ns of replicate simulation with five force fields from popular biomolecular families: AMBER 99SB-ILDN, CHARMM 36, OPLS-AA/L, GROMOS 54A7, and MARTINI. We find considerable differences among the ensembles with little conformational overlap, although they correspond to similar extents to structural data obtained from electron paramagnetic resonance and cross-linking studies. Moreover, each trajectory was still sampling new conformations at a high rate after 500 ns of simulation, suggesting the need for more sampling. This work highlights the need to consider known limitations of the force field used (e.g., biases toward certain secondary structures) and the simulation itself (e.g., whether sufficient sampling has been achieved) when interpreting accumulated results of simulation studies of P-gp and other transport proteins.

Effect of Cholesterol Versus Ergosterol on DPPC Bilayer Properties: Insights from Atomistic Simulations

Sterols have been ascribed a major role in the organization of biological membranes, in particular for the formation of liquid ordered domains in complex lipid mixtures. Here, we employed molecular dynamics simulations to compare the effects of cholesterol and ergosterol as the major sterol of mammalian and fungal cells, respectively, on binary mixtures with 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) as a proxy for saturated lipids. In agreement with previous work, we observe that the addition of sterol molecules modifies the order of DPPC both in the gel phase and in the liquid phase. When disentangling the overall tilt angle and the structure of the tail imposed by trans/gauche configurations of torsion angles in the tail, respectively, a more detailed picture of the impact of sterols can be formulated, revealing, for example, an approximate temperature-concentration superposition ranging from the liquid to the gel phase. Furthermore, a new quantitative measure to identify the presence of collective sterol effects is discussed. Moreover, when comparing both types of sterols, addition of cholesterol has a noticeably stronger impact on phospholipid properties than that of ergosterol. The observed differences can be attributed to higher planarity of the cholesterol ring system. This planarity combined with an inherent asymmetry in its molecular interactions leads to better alignment and hence stronger interaction with saturated acyl chains. Our results suggest that the high order demonstrated for ergosterol in fungal plasma membranes must therefore be generated via additional mechanisms.

Cationic Dendrimers for siRNA Delivery: Computational Approaches for Characterization

Nowadays, computer simulations have been established as a fundamental tool in the design and development of new dendrimer-based nanocarriers for drug and gene delivery. Moreover, the level of detail contained in the information that can be gathered by performing atomistic-scale simulations cannot be obtained with any other available experimental technique. In this chapter we describe the main computational toolbox that can be exploited in the different stages of novel dendritic nanocarrier production-from the initial conception to the stage of biological intermolecular interactions.

Prediction of amphipathic helix-membrane interactions with Rosetta

Amphipathic helices have hydrophobic and hydrophilic/charged residues situated on opposite faces of the helix. They can anchor peripheral membrane proteins to the membrane, be attached to integral membrane proteins, or exist as independent peptides. Despite the widespread presence of membrane-interacting amphipathic helices, there is no computational tool within Rosetta to model their interactions with membranes. In order to address this need, we developed the AmphiScan protocol with PyRosetta, which runs a grid search to find the most favorable position of an amphipathic helix with respect to the membrane. The performance of the algorithm was tested in benchmarks with the RosettaMembrane, ref2015_memb, and franklin2019 score functions on six engineered and 44 naturally-occurring amphipathic helices using membrane coordinates from the OPM and PDBTM databases, OREMPRO server, and MD simulations for comparison. The AmphiScan protocol predicted the coordinates of amphipathic helices within less than 3Å of the reference structures and identified membrane-embedded residues with a Matthews Correlation Constant (MCC) of up to 0.57. Overall, AmphiScan stands as fast, accurate, and highly-customizable protocol that can be pipelined with other Rosetta and Python applications.

Amphipathic helices are important targets as antibacterial peptides and as domains of membrane proteins that play a role in sensing the membrane environment. Understanding how amphipathic helices interact with membrane enables us to design better peptides and understand how membrane proteins use them to interact with their environment. However, there is a limited number of tools available for the modeling of amphipathic helices in membranes. Implicit membrane models can be used for this purpose as simplistic representations of the membrane environment. In this work, we developed the AmphiScan protocol that can be used to predict membrane coordinates of amphipathic helices starting with a helix structure in an implicit membrane environment. We benchmarked the performance of AmphiScan on engineered LK peptides, naturally-occurring amphipathic helices, and hydrophobic and hydrophilic peptides. Our approach provides a reliable and customizable tool to model amphipathic helix–membrane interactions, and pose a platform for the screening of amphipathic helix properties in silico.

Membrane packing defects in synaptic vesicles recruit complexin and synuclein

Complexin-1 (Cpx) and α-synuclein (α-Syn) are involved in neurotransmitter release through an interaction with synaptic vesicles (SVs). Recent studies demonstrated that Cpx and α-Syn preferentially associate with highly curved membranes, like SVs, to correctly position them for fusion. Here, based on recent experimental results, to further propose a possible explanation for this mechanism, we performed in silico simulations probing interactions between Cpx or α-Syn and membranes of varying curvature. We found that the preferential association is attributed to smaller, curved membranes containing more packing defects that expose hydrophobic acyl tails, which may favorably interact with hydrophobic residues of Cpx and α-Syn. The number of membrane defects is proportional to the curvature and the size can be regulated by cholesterol.

Native-like membrane models of E. coli polar lipid extract shed light on the importance of lipid composition complexity

BACKGROUND

Lipid-protein interactions stabilize protein oligomers, shape their structure, and modulate their function. Whereas in vitro experiments already account for the functional importance of lipids by using natural lipid extracts, in silico methods lack behind by embedding proteins in single component lipid bilayers. However, to accurately complement in vitro experiments with molecular details at very high spatio-temporal resolution, molecular dynamics simulations have to be performed in natural(-like) lipid environments.

RESULTS

To enable more accurate MD simulations, we have prepared four membrane models of E. coli polar lipid extract, a typical model organism, each at all-atom (CHARMM36) and coarse-grained (Martini3) representations. These models contain all main lipid headgroup types of the E. coli inner membrane, i.e., phosphatidylethanolamines, phosphatidylglycerols, and cardiolipins, symmetrically distributed between the membrane leaflets. The lipid tail (un)saturation and propanylation stereochemistry represent the bacterial lipid tail composition of E. coli grown at 37∘C until 3/4 of the log growth phase. The comparison of the Simple three lipid component models to the complex 14-lipid component model Avanti over a broad range of physiologically relevant temperatures revealed that the balance of lipid tail unsaturation and propanylation in different positions and inclusion of lipid tails of various length maintain realistic values for lipid mobility, membrane area compressibility, lipid ordering, lipid volume and area, and the bilayer thickness. The only Simple model that was able to satisfactory reproduce most of the structural properties of the complex Avanti model showed worse agreement of the activation energy of basal water permeation with the here performed measurements. The Martini3 models reflect extremely well both experimental and atomistic behavior of the E. coli polar lipid extract membranes. Aquaporin-1 embedded in our native(-like) membranes causes partial lipid ordering and membrane thinning in its vicinity. Moreover, aquaporin-1 attracts and temporarily binds negatively charged lipids, mainly cardiolipins, with a distinct cardiolipin binding site in the crevice at the contact site between two monomers, most probably stabilizing the tetrameric protein assembly.

CONCLUSIONS

The here prepared and validated membrane models of E. coli polar lipids extract revealed that lipid tail complexity, in terms of double bond and cyclopropane location and varying lipid tail length, is key to stabilize membrane properties over a broad temperature range. In addition, they build a solid basis for manifold future simulation studies on more realistic lipid membranes bridging the gap between simulations and experiments.

Guardians of the Cell: State-of-the-Art of Membrane Proteins from a Computational Point-of-View

Membrane proteins (MPs) encompass a large family of proteins with distinct cellular functions, and although representing over 50% of existing pharmaceutical drug targets, their structural and functional information is still very scarce. Over the last years, in silico analysis and algorithm development were essential to characterize MPs and overcome some limitations of experimental approaches. The optimization and improvement of these methods remain an ongoing process, with key advances in MPs' structure, folding, and interface prediction being continuously tackled. Herein, we discuss the latest trends in computational methods toward a deeper understanding of the atomistic and mechanistic details of MPs.

Lipid Dynamics in Membranes Slowed Down by Transmembrane Proteins

Lipids and proteins, as essential components of biological cell membranes, exhibit a significant degree of freedom for different kinds of motions including lateral long-range mobility. Due to their interactions, they not only preserve the cellular membrane but also contribute to many important cellular functions as e.g., signal transport or molecular exchange of the cell with its surrounding. Many of these processes take place on a short time (up to some nanoseconds) and length scale (up to some nanometers) which is perfectly accessible by quasielastic neutron scattering (QENS) experiments and molecular dynamics (MD) simulations. In order to probe the influence of a peptide, a transmembrane sequence of the transferrin receptor (TFRC) protein, on the dynamics of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) large unilamellar vesicles (LUVs) on a nanosecond time scale, high-resolution QENS experiments and complementary MD simulations have been utilized. By using different scattering contrasts in the experiment (chain-deuterated lipids and protonated lipids, respectively), a model could be developed which allows to examine the lipid and peptide dynamics separately. The experimental results revealed a restricted lipid lateral mobility in the presence of the TFRC transmembrane peptides. Also the apparent self-diffusion coefficient of the lateral movement of the peptide molecules could be determined quantitatively for the probed short-time regime. The findings could be confirmed very precisely by MD simulations. Furthermore, the article presents an estimation for the radius of influence of the peptides on the lipid long-range dynamics which could be determined by consistently combining results from experiment and simulation.

Serotonin Alters the Phase Equilibrium of a Ternary Mixture of Phospholipids and Cholesterol

Unsaturated and saturated phospholipids tend to laterally segregate, especially in the presence of cholesterol. Small molecules such as neurotransmitters, toxins, drugs etc. possibly modulate this lateral segregation. The small aromatic neurotransmitter serotonin (5-HT) has been found to bind to membranes. We studied the lipid structure and packing of a ternary membrane mixture consisting of palmitoyl-oleoyl-phosphatidylcholine, palmitoyl-sphingomyelin, and cholesterol at a molar ratio of 4/4/2 in the absence and in the presence of 5-HT, using a combination of solid-state 2H NMR, atomic force microscopy, and atomistic molecular dynamics (MD) simulations. Both NMR and MD report formation of a liquid ordered (L o ) and a liquid disordered (L d ) phase coexistence with small domains. Lipid exchange between the domains was fast such that single component 2H NMR spectra are detected over a wide temperature range. A drastic restructuring of the domains was induced when 5-HT is added to the membranes at a 9 mol% concentration relative to the lipids. 2H NMR spectra of all components of the mixture showed two prominent contributions indicative of molecules of the same kind residing both in the disordered and the ordered phase. Compared to the data in the absence of 5-HT, the lipid chain order in the disordered phase was further decreased in the presence of 5-HT. Likewise, addition of serotonin increased lipid chain order within the ordered phase. These characteristic lipid chain order changes were confirmed by MD simulations. The 5-HT-induced larger difference in lipid chain order results in more pronounced differences in the hydrophobic thickness of the individual membrane domains. The correspondingly enlarged hydrophobic mismatch between ordered and disordered phases is assumed to increase the line tension at the domain boundary, which drives the system into formation of larger size domains. These results not only demonstrate that small membrane binding molecules such as neurotransmitters have a profound impact on essential membrane properties. It also suggests a mechanism by which the interaction of small molecules with membranes can influence the function of membrane proteins and non-cognate receptors. Altered membrane properties may modify lateral sorting of membrane protein, membrane protein conformation, and thus influence their function as suspected for neurotransmitters, local anesthetics, and other small drug molecules.

The Effect of Force-Field Parameters on Cytochrome P450-Membrane Interactions: Structure and Dynamics

The simulation of membrane proteins requires compatible protein and lipid force fields that reproduce the properties of both the protein and the lipid bilayer. Cytochrome P450 enzymes are bitopic membrane proteins with a transmembrane helical anchor and a large cytosolic globular domain that dips into the membrane. As such, they are representative and challenging examples of membrane proteins for simulations, displaying features of both peripheral and integral membrane proteins. We performed molecular dynamics simulations of three cytochrome P450 isoforms (2C9, 2C19 and 1A1) in a 2-oleoyl-1-palmitoyl-sn-glycerol-3-phosphocholine bilayer using two AMBER force field combinations: GAFF-LIPID with ff99SB for the protein, and LIPID14 with ff14SB for the protein. Comparison of the structural and dynamic properties of the proteins, the lipids and the protein-membrane interactions shows differing sensitivity of the cytochrome P450 isoforms to the choice of force field, with generally better agreement with experiment for the LIPID14 + ff14SB combination.

Investigation of the Drug Resistance Mechanism of M2-S31N Channel Blockers through Biomolecular Simulations and Viral Passage Experiments

Recent efforts in drug development against influenza A virus (IAV) M2 proton channel S31N mutant resulted in conjugates of amantadine linked with aryl head heterocycles. To understand the mechanism of drug resistance, we chose a representative M2-S31N inhibitor, compound 3, as a chemical probe to identify resistant mutants. To increase the possibility of identifying novel resistant mutants, serial viral passage experiments were performed with multiple strains of H1N1 and H3N2 viruses in different cell lines. This approach not only identified M2 mutations around the drug-binding site, including the pore-lining residues (V27A, V27F, N31S, and G34E) and an interhelical residue (I32N), but also a new allosteric mutation (R45H), in addition to L46P previously identified, located at the C-terminus of M2 that is more than 10 Å away from the drug-binding site. The effects of each mutation were next investigated using electrophysiology, recombinant viruses, and molecular dynamics (MD) simulations. The reduced sensitivity in channel blockage correlated with increased drug resistance in antiviral assays using recombinant viruses. The MD simulations show that the V27A, V27F, G34E, and R45H mutations increase the diameter and hydration state of the pore in complex with compound 3. The Molecular Mechanics Generalized Born (MM-GBSA) calculations result in more positive binding free energies for the complexes of resistant M2 (V27A, V27F, G34E, R45H) with compound 3 compared to the stable complexes (S31N and I32N). Overall, this is the first systematic study of the drug resistance mechanism of M2-S31N channel blockers using multiple viruses in different cell lines.

Heterogeneous Dielectric Implicit Membrane Model for the Calculation of MMPBSA Binding Free Energies

Membrane-bound protein receptors are a primary biological drug target, but the computational analysis of membrane proteins has been limited. In order to improve molecular mechanics Poisson-Boltzmann surface area (MMPBSA) binding free energy calculations for membrane protein-ligand systems, we have optimized a new heterogeneous dielectric implicit membrane model, with respect to free energy simulations in explicit membrane and explicit water, and implemented it into the Amber software suite. This new model supersedes our previous uniform, single dielectric implicit membrane model by allowing the dielectric constant to vary with depth within the membrane. We calculated MMPBSA binding free energies for the human purinergic platelet receptor (P2Y₁₂R) and two of the muscarinic acetylcholine receptors (M2R and M3R) bound to various antagonist ligands using both membrane models, and we found that the heterogeneous dielectric membrane model has a stronger correlation with experimental binding affinities compared to the older model under otherwise identical conditions. This improved membrane model increases the utility of MMPBSA calculations for the rational design and improvement of future drug candidates.

Computational Modeling of Realistic Cell Membranes

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

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.

Influence of Transmembrane Helix Mutations on Cytochrome P450-Membrane Interactions and Function

Human cytochrome P450 (CYP) enzymes play an important role in the metabolism of drugs, steroids, fatty acids, and xenobiotics. Microsomal CYPs are anchored in the endoplasmic reticulum membrane by an N-terminal transmembrane (TM) helix that is connected to the globular catalytic domain by a flexible linker sequence. However, the structural and functional importance of the TM-helix is unclear because it has been shown that CYPs can still associate with the membrane and have enzymatic activity in reconstituted systems after truncation or modification of the N-terminal sequence. Here, we investigated the effect of mutations in the N-terminal TM-helix residues of two human steroidogenic enzymes, CYP 17A1 and CYP 19A1, that are major drug targets for cancer therapy. These mutations were originally introduced to increase the expression of the proteins in Escherichia coli. To investigate the effect of the mutations on protein-membrane interactions and function, we carried out coarse-grained and all-atom molecular dynamics simulations of the CYPs in a phospholipid bilayer. We confirmed the orientations of the globular domain in the membrane observed in the simulations by linear dichroism measurements in a Nanodisc. Whereas the behavior of CYP 19A1 was rather insensitive to truncation of the TM-helix, mutations in the TM-helix of CYP 17A1, especially W2A and E3L, led to a gradual drifting of the TM-helix out of the hydrophobic core of the membrane. This instability of the TM-helix could affect interactions with the allosteric redox partner, cytochrome b5, required for CYP 17A1's lyase activity. Furthermore, the simulations showed that the mutant TM-helix influenced the membrane interactions of the CYP 17A1 globular domain. In some simulations, the mutated TM-helix obstructed the substrate access tunnel from the membrane to the CYP active site, indicating a possible effect on enzyme function.

Computational insights into lipid assisted peptide misfolding and aggregation in neurodegeneration

An overview of recent advances in computational investigation of peptide–lipid interactions in neurodegeneration – Alzheimer's, Parkinson's and Huntington's disease.

Structural Model of the mIgM B-Cell Receptor Transmembrane Domain From Self-Association Molecular Dynamics Simulations

Antigen binding to B-cell antigen receptors (BCRs) followed by signaling initiates the humoral immune response. The signaling is intimately coupled to nanoclustering of BCRs and their sorting to specific membrane domains, a process that is ruled by interactions between the BCR transmembrane domain and lipids. While the structure of the extracellular domains of BCRs has been resolved, little is known about the configuration of the constituting four immunoglobulin domains spanning the membrane. Here, we modeled the structure of the transmembrane (TM) domain of the IgM B-cell receptor using self-assembly coarse-grained molecular dynamics simulations. The obtained quaternary structure was validated against available experimental data and atomistic simulations. The IgM-BCR-TM domain configuration shows a 1:1 stoichiometry between the homodimeric membrane-bound domain of IgM (mIgM) and a Ig-α/Ig-β heterodimer. The mIgM homodimer is based on an asymmetric association of two mIgM domains. We show that a specific site of the Ig-α/Ig-β heterodimer is responsible for the association of IgM-BCRs with lipid rafts. Our results further suggest that this site is blocked in small-sized IgM-BCR clusters. The BCR TM structure provides a molecular basis for the previously suggested dissociation activation model of B-cell receptors. Self-assembly molecular dynamics simulations at the coarse-grained scale here proved as a versatile tool in the study of receptor complexes.

Molecular Dynamics Simulations of Membrane Proteins: An Overview

Simulations of membrane proteins have been rising in popularity in the past decade. Advancements in technology and force fields made it possible to simulate behavior of membrane proteins. Membrane protein simulations can now be used as supporting evidence for experimental findings, for elucidating protein mechanisms, and validating protein crystal structures. Unrelated to experimental data, these simulations can also serve to investigate larger scale processes like protein sorting, protein-membrane interactions, and more. In this review, the history as well as the state-of-the-art methodologies in membrane protein simulations will be summarized. An emphasis will be put on how to set up the system and on the current models for the different components of the simulation system. An overview of the available tools for membrane protein simulation will be given, and current limitations and prospects will also be discussed.

The importance of the membrane interface as the reference state for membrane protein stability

The insertion of nascent polypeptide chains into lipid bilayer membranes and the stability of membrane proteins crucially depend on the equilibrium partitioning of polypeptides. For this, the transfer of full sequences of amino-acid residues into the bilayer, rather than individual amino acids, must be understood. Earlier studies have revealed that the most likely reference state for partitioning very hydrophobic sequences is the membrane interface. We have used μs-scale simulations to calculate the interface-to-transmembrane partitioning free energies ΔG_S→TM for two hydrophobic carrier sequences in order to estimate the insertion free energy for all 20 amino acid residues when bonded to the center of a partitioning hydrophobic peptide. Our results show that prior single-residue scales likely overestimate the partitioning free energies of polypeptides. The correlation of ΔG_S→TM with experimental full-peptide translocon insertion data is high, suggesting an important role for the membrane interface in translocon-based insertion. The choice of carrier sequence greatly modulates the contribution of each single-residue mutation to the overall partitioning free energy. Our results demonstrate the importance of quantifying the observed full-peptide partitioning equilibrium, which is between membrane interface and transmembrane inserted, rather than combining individual water-to-membrane amino acid transfer free energies.

PackMem: A Versatile Tool to Compute and Visualize Interfacial Packing Defects in Lipid Bilayers

The analysis of the structural organization of lipid bilayers is generally performed across the direction normal to the bilayer/water interface, whereas the surface properties of the bilayer at the interface with water are often neglected. Here, we present PackMem, a bioinformatic tool that performs a topographic analysis of the bilayer surface from various molecular dynamics simulations. PackMem unifies and rationalizes previous analyses based on a Cartesian grid. The grid allows identification of surface regions defined as lipid-packing defects where lipids are loosely packed, leading to cavities in which aliphatic carbons are exposed to the solvent, either deep inside or close to the membrane surface. Examples are provided to show that the abundance of lipid-packing defects varies according to the temperature and to the bilayer composition. Because lipid-packing defects control the adsorption of peripheral proteins with hydrophobic insertions, PackMem is instrumental for us to understand and quantify the adhesive properties of biological membranes as well as their response to mechanical perturbations such as membrane deformation.

Computed Free Energies of Peptide Insertion into Bilayers are Independent of Computational Method

We show that the free energy of inserting hydrophobic peptides into lipid bilayer membranes from surface-aligned to transmembrane inserted states can be reliably calculated using atomistic models. We use two entirely different computational methods: high temperature spontaneous peptide insertion calculations as well as umbrella sampling potential-of-mean-force (PMF) calculations, both yielding the same energetic profiles. The insertion free energies were calculated using two different protein and lipid force fields (OPLS protein/united-atom lipids and CHARMM36 protein/all-atom lipids) and found to be independent of the simulation parameters. In addition, the free energy of insertion is found to be independent of temperature for both force fields. However, we find major difference in the partitioning kinetics between OPLS and CHARMM36, likely due to the difference in roughness of the underlying free energy surfaces. Our results demonstrate not only a reliable method to calculate insertion free energies for peptides, but also represent a rare case where equilibrium simulations and PMF calculations can be directly compared.

Models for randomly distributed nanoscopic domains on spherical vesicles

The existence of lipid domains in the plasma membrane of biological systems has proven controversial, primarily due to their nanoscopic size-a length scale difficult to interrogate with most commonly used experimental techniques. Scattering techniques have recently proven capable of studying nanoscopic lipid domains populating spherical vesicles. However, the development of analytical methods able of predicting and analyzing domain pair correlations from such experiments has not kept pace. Here, we developed models for the random distribution of monodisperse, circular nanoscopic domains averaged on the surface of a spherical vesicle. Specifically, the models take into account (i) intradomain correlations corresponding to form factors and interdomain correlations corresponding to pair distribution functions, and (ii) the analytical computation of interdomain correlations for cases of two and three domains on a spherical vesicle. In the case of more than three domains, these correlations are treated either by Monte Carlo simulations or by spherical analogs of the Ornstein-Zernike and Percus-Yevick (PY) equations. Importantly, the spherical analog of the PY equation works best in the case of nanoscopic size domains, a length scale that is mostly inaccessible by experimental approaches such as, for example, fluorescent techniques and optical microscopies. The analytical form factors and structure factors of nanoscopic domains populating a spherical vesicle provide a new and important framework for the quantitative analysis of experimental data from commonly studied phase-separated vesicles used in a wide range of biophysical studies.