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

Modeling membrane geometries implicitly in Rosetta

Interactions between membrane proteins (MPs) and lipid bilayers are critical for many cellular functions. In the Rosetta molecular modeling suite, the implicit membrane energy function is based on a "slab" model, which represent the membrane as a flat bilayer. However, in nature membranes often have a curvature that is important for function and/or stability. Even more prevalent, in structural biology research MPs are reconstituted in model membrane systems such as micelles, bicelles, nanodiscs, or liposomes. Thus, we have modified the existing membrane energy potentials within the RosettaMP framework to allow users to model MPs in different membrane geometries. We show that these modifications can be utilized in core applications within Rosetta such as structure refinement, protein-protein docking, and protein design. For MP structures found in curved membranes, refining these structures in curved, implicit membranes produces higher quality models with structures closer to experimentally determined structures. For MP systems embedded in multiple membranes, representing both membranes results in more favorable scores compared to only representing one of the membranes. Modeling MPs in geometries mimicking the membrane model system used in structure determination can improve model quality and model discrimination.

Transmembrane β-Barrel Models of α-Synuclein Oligomers

The aggregation of α-synuclein is implicated in a number of neurodegenerative diseases, such as Parkinson's and Multiple System Atrophy, but the role of these aggregates in disease development is not clear. One possible mechanism of cytotoxicity is the disturbance or permeabilization of cell membranes by certain types of oligomers. However, no high-resolution structure of such membrane-embedded complexes has ever been determined. Here we construct and evaluate putative transmembrane β-barrels formed by this protein. Examination of the α-synuclein sequence reveals two regions that could form membrane-embedded β-hairpins: 64-92 (the NAC), and 35-56, which harbors many familial Parkinson's mutations. The stability of β-barrels formed by these hairpins is examined first in implicit membrane pores and then by multimicrosecond all-atom simulations. We find that a NAC region barrel remains stably inserted and hydrated for at least 10 μs. A 35-56 barrel remains stably inserted in the membrane but dehydrates and collapses if all His50 are neutral or if His50 is replaced by Q. If half of the His50 are doubly protonated, the barrel takes an oval shape but remains hydrated for at least 10 μs. Possible implications of these findings for α-synuclein pathology are discussed.

Simulations suggest a scaffolding mechanism of membrane deformation by the caveolin 8S complex

Caveolins form complexes of various sizes that deform membranes into polyhedral shapes. However, the recent structure of the 8S complex was disk-like with a flat membrane-binding surface. How can a flat complex deform membranes into nonplanar structures? Molecular dynamics simulations revealed that the 8S complex rapidly takes the form of a suction cup. Simulations on implicit membrane vesicles determined that binding is stronger when E140 gets protonated. In that case, the complex binds much more strongly to 5- and 10-nm-radius vesicles. A concave membrane-binding surface readily explains the membrane-deforming ability of caveolins by direct scaffolding. We propose that the 8S complex sits at the vertices of the caveolar polyhedra, rather than at the center of the polyhedral faces.

Temperature perception by plants

Plants constantly face fluctuating ambient temperatures and must adapt to survive under stressful conditions. Temperature affects many aspects of plant growth and development through a complex network of transcriptional responses. Although temperature sensing is a crucial primary step in initiating transcriptional responses via Ca2+ and/or reactive oxygen species signaling, an understanding of how plants perceive temperature has remained elusive. However, recent studies have yielded breakthroughs in our understanding of temperature sensors and thermosensation mechanisms. We review recent findings on potential temperature sensors and emerging thermosensation mechanisms, including biomolecular condensate formation through phase separation in plants. We also compare the temperature perception mechanisms of plants with those of other organisms to provide insights into understanding temperature sensing by plants.

Comparing the effects of proteins with IDRs on membrane system in yeast, mammalian cells, and the model plant Arabidopsis

Membrane vesiculation is an energy-costing process. Previous studies paid much attention to proteins with curvature-inducing motifs. Recent publications reveal that the liquid-like protein assembly on membrane surfaces provides an efficient yet structure-independent mechanism for increasing the membrane curvature, which plays important roles in vesicle transport in many aspects. Intrinsically disordered regions (IDRs) within the proteins are highly potent drivers of membrane curvature by providing large hydrodynamic radii to generate steric pressure. Biomolecular condensates formed by phase separation can provide a reaction platform for sequential processes or generate a wetting surface to sequestrate cargos and trigger membrane remodeling. We review the latest progress in yeast and mammalian cells, focus on the mechanism of clathrin-mediated endocytosis (CME) and autophagy initiation, and compare with what we know in model plant Arabidopsis. The comparison may give important insights into the understanding of basic membrane trafficking mechanisms in plant cells.

Cyanobacterial membrane dynamics in the light of eukaryotic principles

Intracellular compartmentalization is a hallmark of eukaryotic cells. Dynamic membrane remodeling, involving membrane fission/fusion events, clearly is crucial for cell viability and function, as well as membrane stabilization and/or repair, e.g., during or after injury. In recent decades, several proteins involved in membrane stabilization and/or dynamic membrane remodeling have been identified and described in eukaryotes. Yet, while typically not having a cellular organization as complex as eukaryotes, also bacteria can contain extra internal membrane systems besides the cytoplasmic membranes (CMs). Thus, also in bacteria mechanisms must have evolved to stabilize membranes and/or trigger dynamic membrane remodeling processes. In fact, in recent years proteins, which were initially defined being eukaryotic inventions, have been recognized also in bacteria, and likely these proteins shape membranes also in these organisms. One example of a complex prokaryotic inner membrane system is the thylakoid membrane (TM) of cyanobacteria, which contains the complexes of the photosynthesis light reaction. Cyanobacteria are evolutionary closely related to chloroplasts, and extensive remodeling of the internal membrane systems has been observed in chloroplasts and cyanobacteria during membrane biogenesis and/or at changing light conditions. We here discuss common principles guiding eukaryotic and prokaryotic membrane dynamics and the proteins involved, with a special focus on the dynamics of the cyanobacterial TMs and CMs.

Computational Advances of Protein/Neurotransmitter-membrane Interactions Involved in Vesicle Fusion and Neurotransmitter Release

Vesicle fusion is of crucial importance to neuronal communication at neuron terminals. The exquisite but complex fusion machinery for neurotransmitter release is tightly controlled and regulated by protein/neurotransmitter-membrane interactions. Computational 'microscopies', in particular molecular dynamics simulations and related techniques, have provided notable insight into the physiological process over the past decades, and have made enormous contributions to fields such as neurology, pharmacology and pathophysiology. Here we review the computational advances of protein/neurotransmitter-membrane interactions related to presynaptic vesicle-membrane fusion and neurotransmitter release, and outline the in silico challenges ahead for understanding this important physiological process.

Overview of the structure and function of the dopamine transporter and its protein interactions

The dopamine transporter (DAT) plays an integral role in dopamine neurotransmission through the clearance of dopamine from the extracellular space. Dysregulation of DAT is central to the pathophysiology of numerous neuropsychiatric disorders and as such is an attractive therapeutic target. DAT belongs to the solute carrier family 6 (SLC6) class of Na⁺/Cl^- dependent transporters that move various cargo into neurons against their concentration gradient. This review focuses on DAT (SCL6A3 protein) while extending the narrative to the closely related transporters for serotonin and norepinephrine where needed for comparison or functional relevance. Cloning and site-directed mutagenesis experiments provided early structural knowledge of DAT but our contemporary understanding was achieved through a combination of crystallization of the related bacterial transporter LeuT, homology modeling, and subsequently the crystallization of drosophila DAT. These seminal findings enabled a better understanding of the conformational states involved in the transport of substrate, subsequently aiding state-specific drug design. Post-translational modifications to DAT such as phosphorylation, palmitoylation, ubiquitination also influence the plasma membrane localization and kinetics. Substrates and drugs can interact with multiple sites within DAT including the primary S1 and S2 sites involved in dopamine binding and novel allosteric sites. Major research has centered around the question what determines the substrate and inhibitor selectivity of DAT in comparison to serotonin and norepinephrine transporters. DAT has been implicated in many neurological disorders and may play a role in the pathology of HIV and Parkinson's disease via direct physical interaction with HIV-1 Tat and α-synuclein proteins respectively.

Recent Advances of Studies on Cell-Penetrating Peptides Based on Molecular Dynamics Simulations

With the ability to transport cargo molecules across cell membranes with low toxicity, cell-penetrating peptides (CPPs) have become promising candidates for next generation peptide-based drug delivery vectors. Over the past three decades since the first CPP was discovered, a great deal of work has been done on the cellular uptake mechanisms and the applications for the delivery of therapeutic molecules, and significant advances have been made. But so far, we still do not have a precise and unified understanding of the structure-activity relationship of the CPPs. Molecular dynamics (MD) simulations provide a method to reveal peptide-membrane interactions at the atomistic level and have become an effective complement to experiments. In this paper, we review the progress of the MD simulations on CPP-membrane interactions, including the computational methods and technical improvements in the MD simulations, the research achievements in the CPP internalization mechanism, CPP decoration and coupling, and the peptide-induced membrane reactions during the penetration process, as well as the comparison of simulated and experimental results.

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.

A continuum membrane model can predict curvature sensing by helix insertion

Protein domains, such as ENTH (epsin N-terminal homology) and BAR (bin/amphiphysin/rvs), contain amphipathic helices that drive preferential binding to curved membranes. However, predicting how the physical parameters of these domains control this 'curvature sensing' behavior is challenging due to the local membrane deformations generated by the nanoscopic helix on the surface of a large sphere. We here use a deformable continuum model that accounts for the physical properties of the membrane and the helix insertion to predict curvature sensing behavior, with direct validation against multiple experimental datasets. We show that the insertion can be modeled as a local change to the membrane's spontaneous curvature, cins0, producing excellent agreement with the energetics extracted from experiments on ENTH binding to vesicles and cylinders, and of ArfGAP helices to vesicles. For small vesicles with high curvature, the insertion lowers the membrane energy by relieving strain on a membrane that is far from its preferred curvature of zero. For larger vesicles, however, the insertion has the inverse effect, de-stabilizing the membrane by introducing more strain. We formulate here an empirical expression that accurately captures numerically calculated membrane energies as a function of both basic membrane properties (bending modulus κ and radius R) as well as stresses applied by the inserted helix (cins0 and area A_ins). We therefore predict how these physical parameters will alter the energetics of helix binding to curved vesicles, which is an essential step in understanding their localization dynamics during membrane remodeling processes.

Mechanism of negative membrane curvature generation by I-BAR domains

The membrane sculpting ability of BAR domains has been attributed to the intrinsic curvature of their banana-shaped dimeric structure. However, there is often a mismatch between this intrinsic curvature and the diameter of the membrane tubules generated. I-BAR domains are especially mysterious since they are almost flat but generate high negative membrane curvature. Here, we use atomistic implicit-solvent computer modeling to show that the membrane bending of the IRSp53 I-BAR domain is dictated by its higher oligomeric structure, whose curvature is completely unrelated to the intrinsic curvature of the dimer. Two other I-BARs give similar results, whereas a flat F-BAR sheet develops a concave membrane-binding interface, consistent with its observed positive membrane curvature generation. Laterally interacting helical spirals of I-BAR dimers on tube interiors are stable and have an enhanced binding energy that is sufficient for membrane bending to experimentally observed tubule diameters at a reasonable surface density.

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.

Membrane Interactions of α-Synuclein Revealed by Multiscale Molecular Dynamics Simulations, Markov State Models, and NMR

α-Synuclein (αS) is a presynaptic protein that binds to cell membranes and is linked to Parkinson's disease (PD). Binding of αS to membranes is a likely first step in the molecular pathophysiology of PD. The αS molecule can adopt multiple conformations, being largely disordered in water, adopting a β-sheet conformation when present in amyloid fibrils, and forming a dynamic multiplicity of α-helical conformations when bound to lipid bilayers and related membrane-mimetic surfaces. Multiscale molecular dynamics simulations in conjunction with nuclear magnetic resonance (NMR) and cross-linking mass spectrometry (XLMS) measurements are used to explore the interactions of αS with an anionic lipid bilayer. The simulations and NMR measurements together reveal a break in the helical structure of the central non-amyloid-β component (NAC) region of αS in the vicinity of residues 65-70, which may facilitate subsequent oligomer formation. Coarse-grained simulations of αS starting from the structure of αS when bound to a detergent micelle reveal the overall pattern of protein contacts to anionic lipid bilayers, while subsequent all-atom simulations provide details of conformational changes upon membrane binding. In particular, simulations and NMR data for liposome-bound αS indicate incipient β-strand formation in the NAC region, which is supported by intramolecular contacts seen via XLMS and simulations. Markov state models based on the all-atom simulations suggest a mechanism of conformational change of membrane-bound αS via a dynamic helix break in the region of residue 65 in the NAC region. The emergent dynamic model of membrane-interacting αS advances our understanding of the mechanism of PD, potentially aiding the design of novel therapeutic approaches.

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.

Mechanisms of negative membrane curvature sensing and generation by ESCRT III subunit Snf7

Certain proteins have the propensity to bind to negatively curved membranes and generate negative membrane curvature. The mechanism of action of these proteins is much less studied and understood than those that sense and generate positive curvature. In this work, we use implicit membrane modeling to explore the mechanism of an important negative curvature sensing and generating protein: the main ESCRT III subunit Snf7. We find that Snf7 monomers alone can sense negative curvature and that curvature sensitivity increases for dimers and trimers. We have observed spontaneous bending of Snf7 oligomers into circular structures with preferred radius of ~20 nm. The preferred curvature of Snf7 filaments is further confirmed by the simulations of preformed spirals on a cylindrical membrane surface. Snf7 filaments cannot bind with the same interface to flat and curved membranes. We find that even when a filament has the preferred radius, it is always less stable on the flat membrane surface than on the interior cylindrical membrane surface. This provides an additional energy for membrane bending which has not been considered in the spiral spring model. Furthermore, the rings on the cylindrical spirals are bridged together by helix 4 and hence are extra stabilized compared to the spirals on the flat membrane surface.

Protein Structure Prediction and Design in a Biologically Realistic Implicit Membrane

Protein design is a powerful tool for elucidating mechanisms of function and engineering new therapeutics and nanotechnologies. Although soluble protein design has advanced, membrane protein design remains challenging because of difficulties in modeling the lipid bilayer. In this work, we developed an implicit approach that captures the anisotropic structure, shape of water-filled pores, and nanoscale dimensions of membranes with different lipid compositions. The model improves performance in computational benchmarks against experimental targets, including prediction of protein orientations in the bilayer, ΔΔG calculations, native structure discrimination, and native sequence recovery. When applied to de novo protein design, this approach designs sequences with an amino acid distribution near the native amino acid distribution in membrane proteins, overcoming a critical flaw in previous membrane models that were prone to generating leucine-rich designs. Furthermore, the proteins designed in the new membrane model exhibit native-like features including interfacial aromatic side chains, hydrophobic lengths compatible with bilayer thickness, and polar pores. Our method advances high-resolution membrane protein structure prediction and design toward tackling key biological questions and engineering challenges.

Amphipathic Helices of Cellular Proteins Can Replace the Helix in M2 of Influenza A Virus with Only Small Effects on Virus Replication

M2 of influenza virus functions as a proton channel during virus entry. In addition, an amphipathic helix in its cytoplasmic tail plays a role during budding. It targets M2 to the assembly site where it inserts into the inner membrane leaflet to induce curvature that causes virus scission. Since vesicularization of membranes can be performed by a variety of amphiphilic peptides, we used reverse genetics to investigate whether the peptides can substitute for M2's helix. Virus could not be generated if M2's helix was deleted or replaced by a peptide predicted not to form an amphiphilic helix. In contrast, viruses could be rescued if the M2 helix was exchanged by helices known to induce membrane curvature. Infectious virus titers were marginally reduced if M2 contains the helix of the amphipathic lipid packing sensor from the Epsin N-terminal homology domain or the nonnatural membrane inducer RW16. Transmission electron microscopy of infected cells did not reveal unequivocal evidence that virus budding or membrane scission was disturbed in any of the mutants. Instead, individual virus mutants exhibit other defects in M2, such as reduced surface expression, incorporation into virus particles, and ion channel activity. The protein composition and specific infectivity were also altered for mutant virions. We conclude that the presence of an amphiphilic helix in M2 is essential for virus replication but that other helices can replace its basic (curvature-inducing) function.IMPORTANCE Influenza virus is unique among enveloped viruses since it does not rely on the cellular ESCRT machinery for budding. Instead, viruses encode their own scission machine, the M2 protein. M2 is targeted to the edge of the viral assembly site, where it inserts an amphiphilic helix into the membrane to induce curvature. Cellular proteins utilize a similar mechanism for scission of vesicles. We show that the helix of M2 can be replaced by helices from cellular proteins with only small effects on virus replication. No evidence was obtained that budding is disturbed, but individual mutants exhibit other defects in M2 that explain the reduced virus titers. In contrast, no virus could be generated if the helix of M2 is deleted or replaced by irrelevant sequences. These experiments support the concept that M2 requires an amphiphilic helix to induce membrane curvature, but its biophysical properties are more important than the amino acid sequence.

Amphipathic helical peptide-based fluorogenic probes for a marker-free analysis of exosomes based on membrane-curvature sensing

With increasing knowledge about the diverse roles of exosomes in the biological process, much attention has been paid to develop analytical methods for detection and quantification of exosomes. Immunoassays based on the recognition of exosomal protein markers by antibodies were widely used. However, considering that exosomal protein composition varies with the cell type, the protein markers should be carefully selected for a sensitive and selective analysis of target exosomes. Herein, we developed a new class of exosome-binding fluorogenic probes based on membrane curvature (MC) sensing of amphipathic helical (AH) peptides for exosome analysis without the need to use protein markers on the exosomal membranes. The C-terminal region of apolipoprotein A-I labeled with Nile red (ApoC-NR) exhibited a significant fluorescence enhancement upon selective binding to the highly curved membranes of synthetic vesicles. Circular dichroism (CD) measurements involving 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC)/1-2-dioleoyl-sn-glycerol (DOG) vesicles suggested that ApoC-NR recognizes the lipid packing defects in the surface of highly curved membranes via the hydrophobic insertion of the α-helix structure of the ApoC unit. ApoC-NR exhibited a stronger binding affinity for exosome-sized vesicles and a higher MC selectivity compared to all other previously reported peptide probes. ApoC-NR can be used in a simple and rapid “mix and read” analysis of various kinds of exosomes derived from different cell types (limit of detection: –10⁵ particles/μL) without being influenced by the variation in the expression of the surface proteins of the exosomes, which stands in sharp contrast to immunoassays.

Fluorogenic probes based on membrane curvature sensing-amphipathic helical peptides have been developed for a marker-free exosome analysis.

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.

Membrane Active Peptides and Their Biophysical Characterization

In the last 20 years, an increasing number of studies have been reported on membrane active peptides. These peptides exert their biological activity by interacting with the cell membrane, either to disrupt it and lead to cell lysis or to translocate through it to deliver cargos into the cell and reach their target. Membrane active peptides are attractive alternatives to currently used pharmaceuticals and the number of antimicrobial peptides (AMPs) and peptides designed for drug and gene delivery in the drug pipeline is increasing. Here, we focus on two most prominent classes of membrane active peptides; AMPs and cell-penetrating peptides (CPPs). Antimicrobial peptides are a group of membrane active peptides that disrupt the membrane integrity or inhibit the cellular functions of bacteria, virus, and fungi. Cell penetrating peptides are another group of membrane active peptides that mainly function as cargo-carriers even though they may also show antimicrobial activity. Biophysical techniques shed light on peptide–membrane interactions at higher resolution due to the advances in optics, image processing, and computational resources. Structural investigation of membrane active peptides in the presence of the membrane provides important clues on the effect of the membrane environment on peptide conformations. Live imaging techniques allow examination of peptide action at a single cell or single molecule level. In addition to these experimental biophysical techniques, molecular dynamics simulations provide clues on the peptide–lipid interactions and dynamics of the cell entry process at atomic detail. In this review, we summarize the recent advances in experimental and computational investigation of membrane active peptides with particular emphasis on two amphipathic membrane active peptides, the AMP melittin and the CPP pVEC.