Amphipathic-Lipid-Packing-Sensor interactions with lipids assessed by atomistic molecular dynamics

The Functionality of Membrane-Inserting Proteins and Peptides: Curvature Sensing, Generation, and Pore Formation

Proteins and peptides with hydrophobic and amphiphilic segments are responsible for many biological functions. The sensing and generation of membrane curvature are the functions of several protein domains or motifs. While some specific membrane proteins play an essential role in controlling the curvature of distinct intracellular membranes, others participate in various cellular processes such as clathrin-mediated endocytosis, where several proteins sort themselves at the neck of the membrane bud. A few membrane-inserting proteins form nanopores that permeate selective ions and water to cross the membrane. In addition, many natural and synthetic small peptides and protein toxins disrupt the membrane by inducing nonspecific pores in the membrane. The pore formation causes cell death through the uncontrolled exchange between interior and exterior cellular contents. In this article, we discuss the insertion depth and orientation of protein/peptide helices, and their role as a sensor and inducer of membrane curvature as well as a pore former in the membrane. We anticipate that this extensive review will assist biophysicists to gain insight into curvature sensing, generation, and pore formation by membrane insertion.

Protein-driven membrane remodeling: Molecular perspectives from Flaviviridae infections

The mammalian cell membrane consists of thousands of different lipid species, and this variety is critical for biological function. Alterations to this balance can be dangerous as they can lead to permanent disruption of lipid metabolism, a hallmark in several viral diseases. The Flaviviridae family is made up of positive single-stranded RNA viruses that assemble at or near the location of lipid droplet formation in the endoplasmic reticulum. These viruses are known to interfere with lipid metabolism during the onset of liver disease, albeit to different extents. Pathogenesis of these infections involves specific protein-lipid interactions that alter lipid sorting and metabolism to sustain propagation of the viral infection. Recent experimental studies identify a correlation between viral proteins and lipid content or location in the cell, but these do not assess membrane-embedded interactions. Molecular modeling, specifically molecular dynamics simulations, can provide molecular-level spatial and temporal resolution for characterization of biomolecular interactions. This review focuses on recent advancements and current knowledge gaps in the molecular mechanisms of lipid-mediated liver disease preceded by viral infection. We discuss three viruses from the Flaviviridae family: dengue, zika, and hepatitis C, with a particular focus on lipid interactions with their respective ion channels, known as viroporins.

Physics-based generative model of curvature sensing peptides; distinguishing sensors from binders

Proteins can specifically bind to curved membranes through curvature-induced hydrophobic lipid packing defects. The chemical diversity among such curvature "sensors" challenges our understanding of how they differ from general membrane "binders" that bind without curvature selectivity. Here, we combine an evolutionary algorithm with coarse-grained molecular dynamics simulations (Evo-MD) to resolve the peptide sequences that optimally recognize the curvature of lipid membranes. We subsequently demonstrate how a synergy between Evo-MD and a neural network (NN) can enhance the identification and discovery of curvature sensing peptides and proteins. To this aim, we benchmark a physics-trained NN model against experimental data and show that we can correctly identify known sensors and binders. We illustrate that sensing and binding are phenomena that lie on the same thermodynamic continuum, with only subtle but explainable differences in membrane binding free energy, consistent with the serendipitous discovery of sensors.

Efficient Quantification of Lipid Packing Defect Sensing by Amphipathic Peptides: Comparing Martini 2 and 3 with CHARMM36

In biological systems, proteins can be attracted to curved or stretched regions of lipid bilayers by sensing hydrophobic defects in the lipid packing on the membrane surface. Here, we present an efficient end-state free energy calculation method to quantify such sensing in molecular dynamics simulations. We illustrate that lipid packing defect sensing can be defined as the difference in mechanical work required to stretch a membrane with and without a peptide bound to the surface. We also demonstrate that a peptide's ability to concurrently induce excess leaflet area (tension) and elastic softening─a property we call the "characteristic area of sensing" (CHAOS)─and lipid packing sensing behavior are in fact two sides of the same coin. In essence, defect sensing displays a peptide's propensity to generate tension. The here-proposed mechanical pathway is equally accurate yet, computationally, about 40 times less costly than the commonly used alchemical pathway (thermodynamic integration), allowing for more feasible free energy calculations in atomistic simulations. This enabled us to directly compare the Martini 2 and 3 coarse-grained and the CHARMM36 atomistic force fields in terms of relative binding free energies for six representative peptides including the curvature sensor ALPS and two antiviral amphipathic helices (AH). We observed that Martini 3 qualitatively reproduces experimental trends while producing substantially lower (relative) binding free energies and shallower membrane insertion depths compared to atomistic simulations. In contrast, Martini 2 tends to overestimate (relative) binding free energies. Finally, we offer a glimpse into how our end-state-based free energy method can enable the inverse design of optimal lipid packing defect sensing peptides when used in conjunction with our recently developed evolutionary molecular dynamics (Evo-MD) method. We argue that these optimized defect sensors─aside from their biomedical and biophysical relevance─can provide valuable targets for the development of lipid force fields.

The endophilin curvature-sensitive motif requires electrostatic guidance to recycle synaptic vesicles in vivo

Curvature-sensing mechanisms assist proteins in executing particular actions on various membrane organelles. Here, we investigate the functional specificity of curvature-sensing amphipathic motifs in Caenorhabditis elegans through the study of endophilin, an endocytic protein for synaptic vesicle recycling. We generate chimeric endophilin proteins by replacing the endophilin amphipathic motif H0 with other curvature-sensing amphipathic motifs. We find that the role of amphipathic motifs cannot simply be extrapolated from the identity of their parental proteins. For example, the amphipathic motif of the nuclear pore complex protein NUP133 functionally replaces the synaptic role of endophilin H0. Interestingly, non-functional endophilin chimeras have similar defects-producing fewer synaptic vesicles but more endosomes-and this indicates that the curvature-sensing motifs in these chimeras have a common deficiency for reforming synaptic vesicles. Finally, we convert non-functional endophilin chimeras into functional proteins by changing the cationic property of amphipathic motifs, successfully reprogramming the functional specificity of curvature-sensing motifs in vivo.

Quantifying Membrane Curvature Sensing of Peripheral Proteins by Simulated Buckling and Umbrella Sampling

Membrane curvature plays an essential role in the organization and trafficking of membrane associated proteins. Comparison or prediction of the experimentally resolved protein concentrations adopted at different membrane curvatures requires direct quantification of the relative partitioning free energy. Here, we present a highly efficient and simple to implement a free-energy calculation method which is able to directly resolve the relative partitioning free energy of proteins as a direct function of membrane curvature, i.e., a curvature sensing profile, within (coarse-grained) molecular dynamics simulations. We demonstrate its utility by resolving these profiles for two known curvature sensing peptides, namely ALPS and α-synuclein, for a membrane curvature ranging from -1/6.5 to +1/6.5 nm^-1. We illustrate that the difference in relative partitioning (binding) free energy between these two extrema is only about 13 k_BT for both peptides, illustrating that the driving force of curvature sensing is subtle. Furthermore, we illustrate that ALPS and α-synuclein sense curvature via a contrasting mechanism, which is differentially affected by membrane composition. In addition, we demonstrate that the intrinsic spontaneous curvature of both of these peptides lies beyond the range of membrane curvature accessible in micropipette aspiration experiments, being about 1/7 nm ^-1. Our approach offers an efficient and simple to implement in silico tool for exploring and screening the membrane curvature sensing mechanisms of proteins.

Recent developments in membrane curvature sensing and induction by proteins

BACKGROUND

Membrane-bound intracellular organelles have characteristic shapes attributed to different local membrane curvatures, and these attributes are conserved across species. Over the past decade, it has been confirmed that specific proteins control the large curvatures of the membrane, whereas many others due to their specific structural features can sense the curvatures and bind to the specific geometrical cues. Elucidating the interplay between sensing and induction is indispensable to understand the mechanisms behind various biological processes such as vesicular trafficking and budding.

SCOPE OF REVIEW

We provide an overview of major classes of membrane proteins and the mechanisms of curvature sensing and induction. We then discuss the importance of membrane elastic characteristics to induce the membrane shapes similar to intracellular organelles. Finally, we survey recently available assays developed for studying the curvature sensing and induction by many proteins.

MAJOR CONCLUSIONS

Recent theoretical/computational modeling along with experimental studies have uncovered fascinating connections between lipid membrane and protein interactions. However, the phenomena of protein localization and synchronization to generate spatiotemporal dynamics in membrane morphology are yet to be fully understood.

GENERAL SIGNIFICANCE

The understanding of protein-membrane interactions is essential to shed light on various biological processes. This further enables the technological applications of many natural proteins/peptides in therapeutic treatments. The studies of membrane dynamic shapes help to understand the fundamental functions of membranes, while the medicinal roles of various macromolecules (such as proteins, peptides, etc.) are being increasingly investigated.

Arf1 directly recruits the Pik1-Frq1 PI4K complex to regulate the final stages of Golgi maturation

Proper Golgi complex function depends on the activity of Arf1, a GTPase whose effectors assemble and transport outgoing vesicles. Phosphatidylinositol 4-phosphate (PI4P) generated at the Golgi by the conserved PI 4-kinase Pik1 (PI4KIIIβ) is also essential for Golgi function, although its precise roles in vesicle formation are less clear. Arf1 has been reported to regulate PI4P production, but whether Pik1 is a direct Arf1 effector is not established. Using a combination of live-cell time-lapse imaging analyses, acute PI4P depletion experiments, and in vitro protein–protein interaction assays on Golgi-mimetic membranes, we present evidence for a model in which Arf1 initiates the final stages of Golgi maturation by tightly controlling PI4P production through direct recruitment of the Pik1-Frq1 PI4-kinase complex. This PI4P serves as a critical signal for AP-1 and secretory vesicle formation, the final events at maturing Golgi compartments. This work therefore establishes the regulatory and temporal context surrounding Golgi PI4P production and its precise roles in Golgi maturation.

Protein-induced metamorphosis of unilamellar lipid vesicles to multilamellar hybrid vesicles

Protein encapsulation into nanocarriers has been extensively studied to improve the efficacy and stability of therapeutic proteins. However, the chemical modification of proteins or new synthetic carrier materials are essential to achieve a high encapsulation efficiency and structural stability of proteins, which hinders their clinical applications. New strategies to physically incorporate proteins into nanocarriers feasible for clinical uses are required to overcome the current limitation. Here we report the spontaneous protein-induced reorganization of 'pre-formed' unilamellar lipid vesicles to efficiently incorporate proteins within multilamellar protein-lipid hybrid vesicles without chemical modification. Epidermal growth factor (EGF) binds to the surface of cationic unilamellar lipid vesicles and induces layer-by-layer self-assembly of the vesicles. The protein is spontaneously entrapped in the interstitial layers of a multilamellar structure with extremely high loading efficiency, ~99%, through polyionic interactions as predicted by molecular dynamics simulation. The loaded protein exhibits much higher structural, chemical, and biological stability compared to free protein. The method is also successfully applied to several other proteins. This work provides a promising method for the highly efficient encapsulation of therapeutic proteins into multilamellar lipid vesicles without the use of specialized instruments, high energy, coupling agents, or organic solvents.

Estimating the accuracy of the MARTINI model towards the investigation of peripheral protein–membrane interactions

In this article, we investigate the ability of the MARTINI CG force field, specifically the 3 open-beta version, to reproduce known experimental observations regarding the membrane binding behavior of 12 peripheral membrane proteins and peptides.

Membrane Thinning Induces Sorting of Lipids and the Amphipathic Lipid Packing Sensor (ALPS) Protein Motif

Heterogeneities (e.g., membrane proteins and lipid domains) and deformations (e.g., highly curved membrane regions) in biological lipid membranes cause lipid packing defects that may trigger functional sorting of lipids and membrane-associated proteins. To study these phenomena in a controlled and efficient way within molecular simulations, we developed an external field protocol that artificially enhances packing defects in lipid membranes by enforcing local thinning of a flat membrane region. For varying lipid compositions, we observed strong thinning-induced depletion or enrichment, depending on the lipid's intrinsic shape and its effect on a membrane's elastic modulus. In particular, polyunsaturated and lysolipids are strongly attracted to regions high in packing defects, whereas phosphatidylethanolamine (PE) lipids and cholesterol are strongly repelled from it. Our results indicate that externally imposed changes in membrane thickness, area, and curvature are underpinned by shared membrane elastic principles. The observed sorting toward the thinner membrane region is in line with the sorting expected for a positively curved membrane region. Furthermore, we have demonstrated that the amphipathic lipid packing sensor (ALPS) protein motif, a known curvature and packing defect sensor, is effectively attracted to thinner membrane regions. By extracting the force that drives amphipathic molecules toward the thinner region, our thinning protocol can directly quantify and score the lipid packing sensing of different amphipathic molecules. In this way, our protocol paves the way toward high-throughput exploration of potential defect- and curvature-sensing motifs, making it a valuable addition to the molecular simulation toolbox.

Membrane Curvature Sensing by Amphipathic Helices: Insights from Implicit Membrane Modeling

Sensing and generation of lipid membrane curvature, mediated by the binding of specific proteins onto the membrane surface, play crucial roles in cell biology. A number of mechanisms have been proposed, but the molecular understanding of these processes is incomplete. All-atom molecular dynamics simulations have offered valuable insights but are extremely demanding computationally. Implicit membrane simulations could provide a viable alternative, but current models apply only to planar membranes. In this work, the implicit membrane model 1 is extended to spherical and tubular membranes. The geometric change from planar to curved shapes is straightforward but insufficient for capturing the full curvature effect, which includes changes in lipid packing. Here, these packing effects are taken into account via the lateral pressure profile. The extended implicit membrane model 1 is tested on the wild-types and mutants of the antimicrobial peptide magainin, the ALPS motif of arfgap1, α-synuclein, and an ENTH domain. In these systems, the model is in qualitative agreement with experiments. We confirm that favorable electrostatic interactions tend to weaken curvature sensitivity in the presence of strong hydrophobic interactions but may actually have a positive effect when those are weak. We also find that binding to vesicles is more favorable than binding to tubes of the same diameter and that the long helix of α-synuclein tends to orient along the axis of tubes, whereas shorter helices tend to orient perpendicular to it. Adoption of a specific orientation could provide a mechanism for coupling protein oligomerization to tubule formation.

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

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

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.

A filter at the entrance of the Golgi that selects vesicles according to size and bulk lipid composition

When small phosphatidylcholine liposomes are added to perforated cells, they bind preferentially to the Golgi suggesting an exceptional avidity of this organelle for curved membranes without stereospecific interactions. We show that the cis golgin GMAP-210 accounts for this property. First, the liposome tethering properties of the Golgi resembles that of the amphipathic lipid-packing sensor (ALPS) motif of GMAP-210: both preferred small (radius < 40 nm) liposomes made of monounsaturated but not saturated lipids. Second, reducing GMAP-210 levels or redirecting its ALPS motif to mitochondria decreased liposome capture by the Golgi. Extensive mutagenesis analysis suggests that GMAP-210 tethers authentic transport vesicles via the same mechanism whereby the ALPS motif senses lipid-packing defects at the vesicle surface through its regularly spaced hydrophobic residues. We conclude that the Golgi uses GMAP-210 as a filter to select transport vesicles according to their size and bulk lipid composition.

DOI:http://dx.doi.org/10.7554/eLife.16988.001

Targeting surface voids to counter membrane disorders in lipointoxication-related diseases

Saturated fatty acids (SFA), which are abundant in the so-called western diet, have been shown to efficiently incorporate within membrane phospholipids and therefore impact on organelle integrity and function in many cell types. In the present study, we have developed a yeast-based two-step assay and a virtual screening strategy to identify new drugs able to counter SFA-mediated lipointoxication. The compounds identified here were effective in relieving lipointoxication in mammalian β-cells, one of the main targets of SFA toxicity in humans. In vitro reconstitutions and molecular dynamics simulations on bilayers revealed that these molecules, albeit according to different mechanisms, can generate voids at the membrane surface. The resulting surface defects correlate with the recruitment of loose lipid packing or void-sensing proteins required for vesicular budding, a central cellular process that is precluded under SFA accumulation. Taken together, the results presented here point at modulation of surface voids as a central parameter to consider in order to counter the impacts of SFA on cell function.

Reovirus FAST Proteins Drive Pore Formation and Syncytiogenesis Using a Novel Helix-Loop-Helix Fusion-Inducing Lipid Packing Sensor

Pore formation is the most energy-demanding step during virus-induced membrane fusion, where high curvature of the fusion pore rim increases the spacing between lipid headgroups, exposing the hydrophobic interior of the membrane to water. How protein fusogens breach this thermodynamic barrier to pore formation is unclear. We identified a novel fusion-inducing lipid packing sensor (FLiPS) in the cytosolic endodomain of the baboon reovirus p15 fusion-associated small transmembrane (FAST) protein that is essential for pore formation during cell-cell fusion and syncytiogenesis. NMR spectroscopy and mutational studies indicate the dependence of this FLiPS on a hydrophobic helix-loop-helix structure. Biochemical and biophysical assays reveal the p15 FLiPS preferentially partitions into membranes with high positive curvature, and this partitioning is impeded by bis-ANS, a small molecule that inserts into hydrophobic defects in membranes. Most notably, the p15 FLiPS can be functionally replaced by heterologous amphipathic lipid packing sensors (ALPS) but not by other membrane-interactive amphipathic helices. Furthermore, a previously unrecognized amphipathic helix in the cytosolic domain of the reptilian reovirus p14 FAST protein can functionally replace the p15 FLiPS, and is itself replaceable by a heterologous ALPS motif. Anchored near the cytoplasmic leaflet by the FAST protein transmembrane domain, the FLiPS is perfectly positioned to insert into hydrophobic defects that begin to appear in the highly curved rim of nascent fusion pores, thereby lowering the energy barrier to stable pore formation.

The fusogenic ortho- and aquareoviruses are the only known nonenveloped viruses that induce syncytium formation. Cell-cell fusion is a virulence determinant of fusogenic reoviruses, and is mediated by a singular family of fusion-associated small transmembrane (FAST) proteins, the smallest known viral fusogens. Unlike their enveloped virus counterparts, reovirus FAST proteins have exceptionally small ectodomains and considerable larger cytoplasmic endodomains, suggesting FAST protein interactions with the cytoplasmic leaflet of the plasma membrane likely play a prominent role in the fusion process. We determined that the baboon reovirus p15 FAST protein endodomain contains a novel type of helix-loop-helix lipid packing sensor that partitions into hydrophobic defects present in highly curved membranes. This fusion-inducing lipid packing sensor (FLiPS) is required for pore formation, and can be functionally replaced by heterologous lipid packing sensors. By masking hydrophobic defects appearing in the highly curved rim of nascent fusion pores, the FliPS would make the forward reaction to pore formation a more energetically favored means of resolving an unstable hemifusion intermediate. These results define a new role for curvature sensing motifs, and reveal how viral fusion proteins can drive pore formation without having to rely on membrane stresses induced by complex refolding of large ectodomains.

Molecular modeling of lipid membrane curvature induction by a peptide: more than simply shape

Molecular dynamics simulations of an amphipathic helix embedded in a lipid bilayer indicate that it will induce substantial positive curvature (e.g., a tube of diameter 20 nm at 16% surface coverage). The induction is twice that of a continuum model prediction that only considers the shape of the inclusion. The discrepancy is explained in terms of the additional presence of specific interactions described only by the molecular model. The conclusion that molecular shape alone is insufficient to quantitatively model curvature is supported by contrasting molecular and continuum models of lipids with large and small headgroups (choline and ethanolamine, respectively), and of the removal of a lipid tail (modeling a lyso-lipid). For the molecular model, curvature propensity is analyzed by computing the derivative of the free energy with respect to bending. The continuum model predicts that the inclusion will soften the bilayer near the headgroup region, an effect that may weaken curvature induction. The all-atom predictions are consistent with experimental observations of the degree of tubulation by amphipathic helices and variation of the free energy of binding to liposomes.

Phospholipase D2 is involved in the formation of Golgi tubules and ArfGAP1 recruitment

Lipids and lipid-modifying enzymes play a key role in the biogenesis, maintenance and fission of transport carriers in the secretory and endocytic pathways. In the present study we demonstrate that phosphatidic acid generated by phospholipase D2 (PLD2) is involved in the formation of Golgi tubules. The main evidence to support this is: 1) inhibitors of phosphatidic acid formation and PLD2 depletion inhibit the formation of tubules containing resident enzymes and regulators of intra-Golgi transport in a low temperature (15°C) model of Golgi tubulation but do not affect brefeldin A-induced tubules, 2) inhibition of PLD2 enzymatic activity and PLD2 depletion in cells cultured under physiological conditions (37°C) induce the formation of tubules specifically containing Golgi matrix proteins, and, 3) over-expression of PLD2 induces the formation of a tubular network. In addition, it was found that the generation of this lipid by the isoenzyme is necessary for ArfGAP1 recruitment to Golgi membranes. These results suggest that both proteins are involved in the molecular mechanisms which drive the formation of different types of Golgi tubules.

A sub-nanometre view of how membrane curvature and composition modulate lipid packing and protein recruitment

Two parameters of biological membranes, curvature and lipid composition, direct the recruitment of many peripheral proteins to cellular organelles. Although these traits are often studied independently, it is their combination that generates the unique interfacial properties of cellular membranes. Here, we use a combination of in vivo, in vitro and in silico approaches to provide a comprehensive map of how these parameters modulate membrane adhesive properties. The correlation between the membrane partitioning of model amphipathic helices and the distribution of lipid-packing defects in membranes of different shape and composition explains how macroscopic membrane properties modulate protein recruitment by changing the molecular topography of the membrane interfacial region. Furthermore, our results suggest that the range of conditions that can be obtained in a cellular context is remarkably large because lipid composition and curvature have, under most circumstances, cumulative effects.

Conical lipids in flat bilayers induce packing defects similar to that induced by positive curvature

In biological membranes, changes in lipid composition or mechanical deformations produce defects in the geometrical arrangement of lipids, thus allowing the adsorption of certain peripheral proteins. Here, we perform molecular dynamics simulations on bilayers containing a cylindrical lipid (PC) and a conical lipid (DOG). Profiles of atomic density and lateral pressure across the bilayer show differences in the acyl chain region due to deeper partitioning of DOG compared to PC. However, such analyses are less informative for the interfacial region where peripheral proteins adsorb. To circumvent this limitation, we develop, to our knowledge, a new method of membrane surface analysis. This method allows the identification of chemical defects, where hydrocarbon chains are accessible to the solvent, and geometrical defects, i.e., voids deeper than the glycerol backbone. The size and number of both types of defects increase with the number of monounsaturated acyl chains in PC and with the introduction of DOG, although the defects do not colocalize with the conical lipid. Interestingly, the size and probability of the defects promoted by DOG resemble those induced by positive curvature, thus explaining why conical lipids and positive curvature can both drive the adsorption of peripheral proteins that use hydrophobic residues as membrane anchors.

Amphipathic lipid packing sensor motifs: probing bilayer defects with hydrophobic residues

Sensing membrane curvature allows fine-tuning of complex reactions that occur at the surface of membrane-bound organelles. One of the most sensitive membrane curvature sensors, the Amphipathic Lipid Packing Sensor (ALPS) motif, does not seem to recognize the curved surface geometry of membranes per se; rather, it recognizes defects in lipid packing that arise from membrane bending. In a companion paper, we show that these defects can be mimicked by introducing conical lipids in a flat lipid bilayer, in agreement with experimental observations. Here, we use molecular-dynamics (MD) simulations to characterize ALPS binding to such lipid bilayers. The ALPS motif recognizes lipid-packing defects by a conserved mechanism: peptide partitioning is driven by the insertion of hydrophobic residues into large packing defects that are preformed in the bilayer. This insertion induces only minor modifications in the statistical distribution of the free packing defects. ALPS insertion is severely hampered when monounsaturated lipids are replaced by saturated lipids, leading to a decrease in packing defects. We propose that the hypersensitivity of ALPS motifs to lipid packing defects results from the repetitive use of hydrophobic insertions along the monotonous ALPS sequence.