Molecular Dynamics Simulations Are Redefining Our View of Peptides Interacting with Biological Membranes

Advances in antimicrobial peptides: From mechanistic insights to chemical modifications

This review provides a comprehensive analysis of antimicrobial peptides (AMPs), exploring their diverse sources, secondary structures, and unique characteristics. The review explores into the mechanisms underlying the antibacterial, immunomodulatory effects, antiviral, antiparasitic and antitumour of AMPs. Furthermore, it discusses the three principal synthesis pathways for AMPs and assesses their current clinical applications and preclinical research status. The paper also addresses the limitations of AMPs, including issues related to stability, resistance, and toxicity, while offering insights into strategies for their enhancement. Recent advancements in AMP research, such as chemical modifications (including amino acid sequence optimisation, terminal and side-chain modifications, PEGylation, conjugation with small molecules, conjugation with photosensitisers, metal ligands, polymerisation, cyclisation and specifically targeted antimicrobial peptides) are highlighted. The goal is to provide a foundation for the future design and optimisation of AMPs.

Lipid Shape as a Membrane Activity Modulator of a Fusogenic Antimicrobial Peptide

An intriguing feature of many bacterial membranes is their prevalence of non-bilayer-forming lipids, such as the cone-shaped phosphatidylethanolamines and cardiolipins. Many membrane-active antimicrobial peptides lower the bilayer-to-hexagonal phase transition energy barrier in membranes containing such types of cone-shaped lipids. Here, we systematically studied how the molecular shape of lipids affects the activity of antimicrobial peptide EcDBS1R4, which is known to be an efficient fusogenic peptide. Using coarse-grained molecular dynamics simulations, we show the ability of EcDBS1R4 to form "hourglass-shaped" pores, which is inhibited by cone-shaped lipids. The abundance of cone-shaped lipids further correlates with the propensity of this peptide to oligomerize preferentially in antiparallel dimers. We also observe that EcDBS1R4 promotes the segregation of the anionic lipids. When coupled to dimerization, this charge segregation leads to regions in the bilayer that are devoid of peptides and rich in zwitterionic lipids. Our results indicate a protective role of cone-shaped lipids in bacterial membranes against pore-mediated permeabilization by EcDBS1R4.

Evaluation of the antimicrobial efficiency of three novel chimeric peptides through biochemical and biophysical analyses

Three chimeric membrane-active antimicrobial peptides (AMPs) were designed from previously characterized parental molecules, namely pandinin-2, ascaphin-8, and maximin-3. The aim of constructing these chimeras was to obtain sequences with improved therapeutic indices or increased activity, while simultaneously investigating the functional roles of key segments of the parental peptides. Chimera-1 was the most active peptide against clinically relevant bacterial species, followed by chimera-2, and chimera-3, respectively, with no clear preference towards Gram-negative or Gram-positive strains. Escherichia coli and Pseudomonas aeruginosa were the most sensitive bacteria, while Klebsiella pneumoniae and Staphylococcus aureus were resistant to AMP activity. All peptides presented significantly lower activities towards human erythrocytes, with chimera-1 being the most selective. Additionally, only chimera-2 showed cytotoxicity towards Vero cells. Calcein leakage and dynamic light scattering assays using liposomal formulations indicated that the chimeras conserved the pore forming membrane perturbation mechanisms of the parental molecules. Peptide interaction also reduced membrane fluidity. Circular dichroism (CD) data showed disordered peptides in aqueous solution that transitioned into alpha helical structures lipid bilayer environments. In silico assessments correlated well with microbiological and in vitro experimental data. All peptides established greater contact with the bacterial biomimetic membrane compared to the erythrocyte system, as analyzed by distance from membrane surface, number of contacts, solvent accessible surface area, and number of hydrogen bonds. Additionally, the presence of the bilayer lipid patches favored peptide folding, consistent with CD experiments. Molecular dynamics simulations of peptide aggregation revealed that chimera-2 formed the largest oligomers, consistent with the predicted aggregation propensities and the predicted physico-chemical properties. Interaction with membrane surfaces resulted in smaller clusters while low or lack of interaction favored larger aggregates. Overall, the chimeric peptides displayed higher activity and selectivity compared to the parental ones. The contribution of the flanking regions of pandidin-2 and maximin-3 with respect to the core region of ascaphin-8 was not clear.

Unlocking the power of membrane biophysics: enhancing the study of antimicrobial peptides activity and selectivity

The application of membrane-active antimicrobial peptides (AMPs) is considered to be a viable alternative to conventional antibiotics for treating infections caused by multidrug-resistant pathogenic microorganisms. In vitro and in silico biophysical approaches are indispensable for understanding the underlying molecular mechanisms of membrane-active AMPs. Lipid bilayer models are widely used to mimic and study the implication of various factors affecting these bio-active molecules, and their relationship with the physical parameters of the different membranes themselves. The quality and resemblance of these models to their target is crucial for elucidating how these AMPs work. Unfortunately, over the last few decades, no notable efforts have been made to improve or refine membrane mimetics, as it pertains to the elucidation of AMPs molecular mechanisms. In this review, we discuss the importance of improving the quality and resemblance of target membrane models, in terms of lipid composition and distribution, which ultimately directly influence physical parameters such as charge, fluidity, and thickness. In conjunction, membrane and peptide properties determine the global effect of selectivity, activity, and potency. It is therefore essential to define these interactions, and to do so, more refined lipid models are necessary. In this review, we focus on the significant advancements in promoting biomimetic membranes that closely resemble native ones, for which thorough biophysical characterization is key. This includes utilizing more complex lipid compositions that mimic various cell types. Additionally, we discuss important considerations to be taken into account when working with more complex systems.

Permeability Benchmarking: Guidelines for Comparing in Silico, in Vitro, and in Vivo Measurements

Permeability is a measure of the degree to which cells can transport molecules across biological barriers. Units of permeability are distance per unit time (typically cm/s), where accurate measurements are needed to define drug delivery in homeostasis and to model dysfunction occurring during disease. This perspective offers a set of community-led guidelines to benchmark permeability data across multidisciplinary approaches and different biological contexts. First, we lay out the analytical framework for three methodologies to calculate permeability: in silico assays using either transition-based counting or the inhomogeneous-solubility diffusion approaches, in vitro permeability assays using cells cultured in 2D or 3D geometries, and in vivo assays utilizing in situ brain perfusion or multiple time-point regression analysis. Then, we demonstrate a systematic benchmarking of in silico to both in vitro and in vivo, depicting the ways in which each benchmarking is sensitive to the choices of assay design. Finally, we outline seven recommendations for best practices in permeability benchmarking and underscore the significance of tailored permeability assays in driving advancements in drug delivery research and development. Our exploration encompasses a discussion of "generic" and tissue-specific biological barriers, including the blood-brain barrier (BBB), which is a major hurdle for the delivery of therapeutic agents into the brain. By addressing challenges in reconciling simulated data with experimental assays, we aim to provide insights essential for optimizing accuracy and reliability in permeability modeling.

Flexible Tail of Antimicrobial Peptide PGLa Facilitates Water Pore Formation in Membranes

PGLa, an antimicrobial peptide (AMP), primarily exerts its antibacterial effects by disrupting bacterial cell membrane integrity. Previous theoretical studies mainly focused on the binding mechanism of PGLa with membranes, while the mechanism of water pore formation induced by PGLa peptides, especially the role of structural flexibility in the process, remains unclear. In this study, using all-atom simulations, we investigated the entire process of membrane deformation caused by the interaction of PGLa with an anionic cell membrane composed of dimyristoylphosphatidylcholine (DMPC) and dimyristoylphosphatidylglycerol (DMPG). Using a deep learning-based key intermediate identification algorithm, we found that the C-terminal tail plays a crucial role for PGLa insertion into the membrane, and that with its assistance, a variety of water pores formed inside the membrane. Mutation of the tail residues revealed that, in addition to electrostatic and hydrophobic interactions, the flexibility of the tail residues is crucial for peptide insertion and pore formation. The full extension of these flexible residues enhances peptide-peptide and peptide-membrane interactions, guiding the transmembrane movement of PGLa and the aggregation of PGLa monomers within the membrane, ultimately leading to the formation of water-filled pores in the membrane. Overall, this study provides a deep understanding of the transmembrane mechanism of PGLa and similar AMPs, particularly elucidating for the first time the importance of C-terminal flexibility in both insertion and oligomerization processes.

A novel synthetic peptide analog enhanced antibacterial activity of the frog-derived skin peptide wuchuanin-A1

In recent years, there has been a growing focus on the development of novel antibacterial compounds for clinical applications, such as antimicrobial peptide (AMP). Among the developed AMP, wuchuanin-A1, a coil-shaped bioactive peptide derived from Odorrana wuchuanensis frog skin, has been reported to exhibit antibacterial, antifungal, and antioxidant activity, but there are limited studies on its potential as an antibacterial agent. Therefore, this study aims to molecularly modify the sequence of wuchuanin-A1 to enhance its antibacterial properties. The interaction of both the native and analog peptide with bacterial inner membranes was initially assessed using computational methods. Specific amino acid substitutions were then used to enhance the modified peptide's antibacterial efficacy, followed by several preliminary tests to evaluate its activity. This study bridges the gap in exploring the potential of wuchuanin-A1 for antibacterial purposes, providing insights into the design of effective antimicrobial agents.Communicated by Ramaswamy H. Sarma.

Insertion and Anchoring of the HIV-1 Fusion Peptide into a Complex Membrane Mimicking the Human T-Cell

A fundamental understanding of how the HIV-1 envelope (Env) protein facilitates fusion is still lacking. The HIV-1 fusion peptide, consisting of 15 to 22 residues, is the N-terminus of the gp41 subunit of the Env protein. Further, this peptide, a promising vaccine candidate, initiates viral entry into target cells by inserting and anchoring into human immune cells. The influence of membrane lipid reorganization and the conformational changes of the fusion peptide during the membrane insertion and anchoring processes, which can significantly affect HIV-1 cell entry, remains largely unexplored due to the limitations of experimental measurements. In this work, we investigate the insertion of the fusion peptide into an immune cell membrane mimic through multiscale molecular dynamics simulations. We mimic the native T-cell by constructing a nine-lipid asymmetric membrane, along with geometrical restraints accounting for insertion in the context of gp41. To account for the slow time scale of lipid mixing while enabling conformational changes, we implement a protocol to go back and forth between atomistic and coarse-grained simulations. Our study provides a molecular understanding of the interactions between the HIV-1 fusion peptide and the T-cell membrane, highlighting the importance of the conformational flexibility of fusion peptides and local lipid reorganization in stabilizing the anchoring of gp41 into the targeted host membrane during the early events of HIV-1 cell entry. Importantly, we identify a motif within the fusion peptide critical for fusion that can be further manipulated in future immunological studies.

Exploring the Chemical Features and Biomedical Relevance of Cell-Penetrating Peptides

Cell-penetrating peptides (CPPs) are a diverse group of peptides, typically composed of 4 to 40 amino acids, known for their unique ability to transport a wide range of substances-such as small molecules, plasmid DNA, small interfering RNA, proteins, viruses, and nanoparticles-across cellular membranes while preserving the integrity of the cargo. CPPs exhibit passive and non-selective behavior, often requiring functionalization or chemical modification to enhance their specificity and efficacy. The precise mechanisms governing the cellular uptake of CPPs remain ambiguous; however, electrostatic interactions between positively charged amino acids and negatively charged glycosaminoglycans on the membrane, particularly heparan sulfate proteoglycans, are considered the initial crucial step for CPP uptake. Clinical trials have highlighted the potential of CPPs in diagnosing and treating various diseases, including cancer, central nervous system disorders, eye disorders, and diabetes. This review provides a comprehensive overview of CPP classifications, potential applications, transduction mechanisms, and the most relevant algorithms to improve the accuracy and reliability of predictions in CPP development.

Cm-p5, a molluscan-derived antifungal peptide exerts its activity by a membrane surface covering in a non-penetrating mode

Amidst the health crisis caused by the rise of multi-resistant pathogenic microorganisms, Antimicrobial Peptides (AMPs) have emerged as a potential alternative to traditional antibiotics. In this sense, Cm-p5 is an AMP with fungistatic activity against the yeast Candida albicans. Its antimicrobial activity and selectivity have been well characterized; however, the mechanism of action is still unknown. This study used biophysical approaches to gain insight into how this peptide exerts its activity. Stability and fluidity of lipid membrane were explored by liposome leakage and Laurdan generalized polarization (GP) respectively, suggesting that Cm-p5 does not perturb lipid membranes even at very high concentrations (≥100 µm.L-1). Likewise, no depolarizing action was observed using 3,3'-propil-2,2'-thyodicarbocianine, a potential membrane fluorescent reporter, with C. albicans cells or the corresponding liposome models. Changes in liposome size were analyzed by Dynamic Light Scattering (DLS) data, indicating that Cm-p5 covers the vesicular surface slightly increasing liposome hydrodynamic size, without liposome rupture. These results were further corroborated with Langmuir monolayer isotherms, where no significant changes in lateral pressure or area per lipid were detected, indicating little or no insertion. Finally, data obtained from molecular dynamics simulations aligned with in vitro observations, whereby Cm-p5 slightly interacted with the fungal membrane model surface without causing significant perturbation. These results suggest Cm-p5 is not a pore-forming anti-fungal peptide and that other mechanisms of action on the membrane as some limitation of fungal nutrition or receptor-dependent transduction for depressing growth development should be explored.

Computational investigation of the effect of BODIPY labelling on peptide-membrane interaction

Optical monitoring of peptide binding to live cells is hampered by the abundance of naturally occurring fluorophores such as tryptophan. Unnatural amino acids incorporating synthetic fluorophores such as BODIPY overcome these optical limitations. A drawback to using fluorophores in lipid binding peptide design is their propensity to override other interactions, potentially causing the peptides to lose their binding selectivity. Here, the binding strength of a selection of peptides incorporating a variety of BODIPY derivatized amino acids has been studied via molecular dynamics simulations to quantify the impact of BODIPY incorporation on peptide-membrane binding behaviour.

Molecular and energetic analysis of the interaction and specificity of Maximin 3 with lipid membranes: In vitro and in silico assessments

In this study, the interaction of antimicrobial peptide Maximin 3 (Max3) with three different lipid bilayer models was investigated to gain insight into its mechanism of action and membrane specificity. Bilayer perturbation assays using liposome calcein leakage dose-response curves revealed that Max3 is a selective membrane-active peptide. Dynamic light scattering recordings suggest that the peptide incorporates into the liposomal structure without producing a detergent effect. Langmuir monolayer compression assays confirmed the membrane inserting capacity of the peptide. Attenuated total reflection-Fourier transform infrared spectroscopy showed that the fingerprint signals of lipid phospholipid hydrophilic head groups and hydrophobic acyl chains are altered due to Max3-membrane interaction. On the other hand, all-atom molecular dynamics simulations (MDS) of the initial interaction with the membrane surface corroborated peptide-membrane selectivity. Peptide transmembrane MDS shed light on how the peptide differentially modifies lipid bilayer properties. Molecular mechanics Poisson-Boltzmann surface area calculations revealed a specific electrostatic interaction fingerprint of the peptide for each membrane model with which they were tested. The data generated from the in silico approach could account for some of the differences observed experimentally in the activity and selectivity of Max3.

Membrane-active peptides for anticancer therapies

Membrane-active peptides are found in many living organisms and play a critical role in their immune systems by combating various infectious diseases. These host defense peptides employ multiple mechanisms against different microorganisms and possess unique functions, such as anti-inflammatory and immunomodulatory effects, often working in synergy with other antimicrobial agents. Despite extensive research over the past few decades and the identification of thousands of sequences, only a few have been successfully applied in clinical settings and received approval from the U.S. Food and Drug Administration. In this chapter, we explore all peptide therapeutics that have reached the market, as well as candidates in preclinical and clinical trials, to understand their success and potential applications in cancer therapy. Our findings indicate that at least four membrane-active peptide drugs have progressed to preclinical or clinical phases, dmonstrating promising results for cancer treatment. We summarize our insights in this chapter, highlighting the potential of membrane-active anticancer peptide therapeutics and their applications as targeting ligands in various biomedical fields.

Pore Formation by Amyloid-like Peptides: Effects of the Nonpolar-Polar Sequence Pattern

One of the mechanisms accounting for the toxicity of amyloid peptides in diseases like Alzheimer's and Parkinson's is the formation of pores on the plasma membrane of neurons. Here, we perform unbiased all-atom simulations of the full membrane damaging pathway, which includes adsorption, aggregation, and perforation of the lipid bilayer accounting for pore-like structures. Simulations are performed using four peptides made with the same amino acids. Differences in the nonpolar-polar sequence pattern of these peptides prompt them to adsorb into the membrane with the extended conformations oriented either parallel [peptide labeled F1, Ac-(FKFE)2-NH2], perpendicular (F4, Ac-FFFFKKEE-NH2), or with an intermediate orientation (F2, Ac-FFKKFFEE-NH2, and F3, Ac-FFFKFEKE-NH2) in regard to the membrane surface. At the water-lipid interface, only F1 fully self-assembles into β-sheets, and F2 peptides partially fold into an α-helical structure. The β-sheets of F1 emerge as electrostatic interactions attract neighboring peptides to intermediate distances where nonpolar side chains can interact within the dry core of the bilayer. This complex interplay between electrostatic and nonpolar interactions is not observed for the other peptides. Although β-sheets of F1 peptides are mostly parallel to the membrane, some of their edges penetrate deep inside the bilayer, dragging water molecules with them. This precedes pore formation, which starts with the flow of two water layers through the membrane that expand into a stable cylindrical pore delimited by polar faces of β-sheets spanning both leaflets of the bilayer.

Melittin can permeabilize membranes via large transient pores

Membrane active peptides are known to porate lipid bilayers, but their exact permeabilization mechanism and the structure of the nanoaggregates they form in membranes have often been difficult to determine experimentally. For many sequences at lower peptide concentrations, transient leakage is observed in experiments, suggesting the existence of transient pores. For two well-know peptides, alamethicin and melittin, we show here that molecular mechanics simulations i) can directly distinguish equilibrium poration and non-equilibrium transient leakage processes, and ii) can be used to observe the detailed pore structures and mechanism of permeabilization in both cases. Our results are in very high agreement with numerous experimental evidence for these two peptides. This suggests that molecular simulations can capture key membrane poration phenomena directly and in the future may develop to be a useful tool that can assist experimental peptide design.

Insertion and Anchoring of HIV-1 Fusion Peptide into Complex Membrane Mimicking Human T-cell

A fundamental understanding of how HIV-1 envelope (Env) protein facilitates fusion is still lacking. The HIV-1 fusion peptide, consisting of 15 to 22 residues, is the N-terminus of the gp41 subunit of the Env protein. Further, this peptide, a promising vaccine candidate, initiates viral entry into target cells by inserting and anchoring into human immune cells. The influence of membrane lipid reorganization and the conformational changes of the fusion peptide during the membrane insertion and anchoring processes, which can significantly affect HIV-1 cell entry, remains largely unexplored due to the limitations of experimental measurements. In this work, we investigate the insertion of the fusion peptide into an immune cell membrane mimic through multiscale molecular dynamics simulations. We mimic the native T-cell by constructing a 9-lipid asymmetric membrane, along with geometrical restraints accounting for insertion in the context of gp41. To account for the slow timescale of lipid mixing while enabling conformational changes, we implement a protocol to go back and forth between atomistic and coarse-grained simulations. Our study provides a molecular understanding of the interactions between the HIV-1 fusion peptide and the T-cell membrane, highlighting the importance of conformational flexibility of fusion peptides and local lipid reorganization in stabilizing the anchoring of gp41 into the targeted host membrane during the early events of HIV-1 cell entry. Importantly, we identify a motif within the fusion peptide critical for fusion that can be further manipulated in future immunological studies.

Delineating the shape of COat Protein complex-II coated membrane bud

Curvature-generating proteins that direct membrane trafficking assemble on the surface of lipid bilayers to bud transport intermediates, which move protein and lipid cargoes from one cellular compartment to another. However, it remains unclear what controls the overall shape of the membrane bud once curvature induction has begun. In vitro experiments showed that excessive concentrations of the COPII protein Sar1 promoted the formation of membrane tubules from synthetic vesicles, while COPII-coated transport intermediates in cells are generally more spherical or lobed in shape. To understand the origin of these morphological differences, we employ atomistic, coarse-grained (CG), and continuum mesoscopic simulations of membranes in the presence of multiple curvature-generating proteins. We first characterize the membrane-bending ability of amphipathic peptides derived from the amino terminus of Sar1, as a function of interpeptide angle and concentration using an atomistic bicelle simulation protocol. Then, we employ CG simulations to reveal that Sec23 and Sec24 control the relative spacing between Sar1 protomers and form the inner-coat unit through an attachment with Sar1. Finally, using dynamical triangulated surface simulations based on the Helfrich Hamiltonian, we demonstrate that the uniform distribution of spacer molecules among curvature-generating proteins is crucial to the spherical budding of the membrane. Overall, our analyses suggest a new role for Sec23, Sec24, and cargo proteins in COPII-mediated membrane budding process in which they act as spacers to preserve a dispersed arrangement of Sar1 protomers and help determine the overall shape of the membrane bud.

Vesicle protrusion induced by antimicrobial peptides suggests common carpet mechanism for short antimicrobial peptides

Short-cationic alpha-helical antimicrobial peptides (SCHAMPs) are promising candidates to combat the growing global threat of antimicrobial resistance. They are short-sequenced, selective against bacteria, and have rapid action by destroying membranes. A full understanding of their mechanism of action will provide key information to design more potent and selective SCHAMPs. Molecular Dynamics (MD) simulations are invaluable tools that provide detailed insights into the peptide-membrane interaction at the atomic- and meso-scale level. We use atomistic and coarse-grained MD to look into the exact steps that four promising SCHAMPs-BP100, Decoralin, Neurokinin-1, and Temporin L-take when they interact with membranes. Following experimental set-ups, we explored the effects of SCHAMPs on anionic membranes and vesicles at multiple peptide concentrations. Our results showed all four peptides shared similar binding steps, initially binding to the membrane through electrostatic interactions and then flipping on their axes, dehydrating, and inserting their hydrophobic moieties into the membrane core. At higher concentrations, fully alpha-helical peptides induced membrane budding and protrusions. Our results suggest the carpet mode of action is fit for the description of SCHAMPs lysis activity and discuss the importance of large hydrophobic residues in SCHAMPs design and activity.

Novel kokumi peptides from yeast extract and their taste mechanism via an in silico study

Yeast extract, a widely utilized natural substance in the food industry and biopharmaceutical field, holds significant potential for flavor enhancement. Kokumi peptides within yeast extracts were isolated through ultrafiltration and gel chromatography, followed by identification using liquid chromatography tandem mass spectrometry (LC-MS/MS). Two peptides, IQGFK and EDFFVR, were identified and synthesized using solid-phase methods based on molecular docking outcomes. Sensory evaluations and electronic tongue analyses conducted with chicken broth solutions revealed taste thresholds of 0.12 mmol L-1 for IQGFK and 0.16 mmol L-1 for EDFFVR, respectively, and both peptides exhibited kokumi properties. Additionally, through molecular dynamics simulations, the binding mechanisms between these peptides and the calcium-sensing receptor (CaSR) were explored. The findings indicated stable binding of both peptides to the receptor. IQGFK primarily interacted through electrostatic interactions, with key binding sites including Asp275, Asn102, Pro274, Trp70, Tyr218, and Ser147. EDFFVR mainly engaged via van der Waals energy and polar solvation free energy, with key binding sites being Asp275, Ile416, Pro274, Arg66, Ala298, and Tyr218. This suggests that both peptides can activate the CaSR, thereby inducing kokumi activity. This study provides a theoretical foundation and reference for the screening and identification of kokumi peptides, successfully uncovering two novel kokumi peptides derived from yeast extract.

Recent Advances on Antimicrobial Peptides from Milk: Molecular Properties, Mechanisms, and Applications

Traditional antibiotics are facing a tremendous challenge due to increased antimicrobial resistance; hence, there is an urgent need to find novel antibiotic alternatives. Milk protein-derived antimicrobial peptides (AMPs) are currently attracting substantial attention considering that they showcase an extensive spectrum of antimicrobial activities, with slower development of antimicrobial resistance and safety of raw materials. This review summarizes the molecular properties, and activity mechanisms and highlights the applications and limitations of AMPs derived from milk proteins comprehensively. Also the analytical technologies, especially bioinformatics methodologies, applied in the process of screening, identification, and mechanism illustration of AMPs were underlined. This review will give some ideas for further research and broadening of the applications of milk protein-derived AMPs in the food field.

Molecular Dynamics Simulations of Drug-Conjugated Cell-Penetrating Peptides

Cell-penetrating peptides (CPPs) are small peptides capable of translocating through biological membranes carrying various attached cargo into cells and even into the nucleus. They may also participate in transcellular transport. Our in silico study intends to model several peptides and their conjugates. We have selected three CPPs with a linear backbone, including penetratin, a naturally occurring oligopeptide; two of its modified sequence analogues (6,14-Phe-penetratin and dodeca-penetratin); and three natural CPPs with a cyclic backbone: Kalata B1, the Sunflower trypsin inhibitor 1 (SFT1), and Momordica cochinchinensis trypsin inhibitor II (MCoTI-II). We have also built conjugates with the small-molecule drug compounds doxorubicin, zidovudine, and rasagiline for each peptide. Molecular dynamics (MD) simulations were carried out with explicit membrane models. The analysis of the trajectories showed that the interaction of penetratin with the membrane led to spectacular rearrangements in the secondary structure of the peptide, while cyclic peptides remained unchanged due to their high conformational stability. Membrane-peptide and membrane-conjugate interactions have been identified and compared. Taking into account well-known examples from the literature, our simulations demonstrated the utility of computational methods for CPP complexes, and they may contribute to a better understanding of the mechanism of penetration, which could serve as the basis for delivering conjugated drug molecules to their intracellular targets.

AMP-EBiLSTM: employing novel deep learning strategies for the accurate prediction of antimicrobial peptides

Antimicrobial peptides are present ubiquitously in intra- and extra-biological environments and display considerable antibacterial and antifungal activities. Clinically, it has shown good antibacterial effect in the treatment of diabetic foot and its complications. However, the discovery and screening of antimicrobial peptides primarily rely on wet lab experiments, which are inefficient. This study endeavors to create a precise and efficient method of predicting antimicrobial peptides by incorporating novel machine learning technologies. We proposed a deep learning strategy named AMP-EBiLSTM to accurately predict them, and compared its performance with ensemble learning and baseline models. We utilized Binary Profile Feature (BPF) and Pseudo Amino Acid Composition (PSEAAC) for effective local sequence capture and amino acid information extraction, respectively, in deep learning and ensemble learning. Each model was cross-validated and externally tested independently. The results demonstrate that the Enhanced Bi-directional Long Short-Term Memory (EBiLSTM) deep learning model outperformed others with an accuracy of 92.39% and AUC value of 0.9771 on the test set. On the other hand, the ensemble learning models demonstrated cost-effectiveness in terms of training time on a T4 server equipped with 16 GB of GPU memory and 8 vCPUs, with training durations varying from 0 to 30 s. Therefore, the strategy we propose is expected to predict antimicrobial peptides more accurately in the future.

In Search of a Molecular View of Peptide-Lipid Interactions in Membranes

Lipid bilayer membranes are often represented as a continuous nonpolar slab with a certain thickness bounded by two more polar interfaces. Phenomena such as peptide binding to the membrane surface, folding, insertion, translocation, and diffusion are typically interpreted on the basis of this view. In this Perspective, I argue that this membrane representation as a hydrophobic continuum solvent is not adequate to understand peptide-lipid interactions. Lipids are not small compared to membrane-active peptides: their sizes are similar. Therefore, peptide diffusion needs to be understood in terms of free volume, not classical continuum mechanics; peptide solubility or partitioning in membranes cannot be interpreted in terms of hydrophobic mismatch between membrane thickness and peptide length; peptide folding and translocation, often involving cationic peptides, can only be understood if realizing that lipids adapt to the presence of peptides and the membrane may undergo considerable lipid redistribution in the process. In all of those instances, the detailed molecular interactions between the peptide residues and the lipid components are essential to understand the mechanisms involved.

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.

The role of peptides in reversing chemoresistance of breast cancer: current facts and future prospects

Breast cancer is the first malignant tumor in women, and its incidence is also increasing year by year. Chemotherapy is one of the standard therapies for breast cancer, but the resistance of breast cancer cells to chemotherapy drugs is a huge challenge for the effective treatment of breast cancer. At present, in the study of reversing the drug resistance of solid tumors such as breast cancer, peptides have the advantages of high selectivity, high tissue penetration, and good biocompatibility. Some of the peptides that have been studied can overcome the resistance of tumor cells to chemotherapeutic drugs in the experiment, and effectively control the growth and metastasis of breast cancer cells. Here, we describe the mechanism of different peptides in reversing breast cancer resistance, including promoting cancer cell apoptosis; promoting non-apoptotic regulatory cell death of cancer cells; inhibiting the DNA repair mechanism of cancer cells; improving the tumor microenvironment; inhibiting drug efflux mechanism; and enhancing drug uptake. This review focuses on the different mechanisms of peptides in reversing breast cancer drug resistance, and these peptides are also expected to create clinical breakthroughs in promoting the therapeutic effect of chemotherapy drugs in breast cancer patients and improving the survival rate of patients.

Relating Molecular Dynamics Simulations to Functional Activity for Gly-Rich Membranolytic Helical Kiadin Peptides

Kiadins are in silico designed peptides with a strong similarity to diPGLa-H, a tandem sequence of PGLa-H (KIAKVALKAL) and with single, double or quadruple glycine substitutions. They were found to show high variability in their activity and selectivity against Gram-negative and Gram-positive bacteria, as well as cytotoxicity against host cells, which are influenced by the number and placing of glycine residues along the sequence. The conformational flexibility introduced by these substitutions contributes differently peptide structuring and to their interactions with the model membranes, as observed by molecular dynamics simulations. We relate these results to experimentally determined data on the structure of kiadins and their interactions with liposomes having a phospholipid membrane composition similar to simulation membrane models, as well as to their antibacterial and cytotoxic activities, and also discuss the challenges in interpreting these multiscale experiments and understanding why the presence of glycine residues in the sequence affected the antibacterial potency and toxicity towards host cells in a different manner.

Understanding Passive Membrane Permeation of Peptides: Physical Models and Sampling Methods Compared

The early characterization of drug membrane permeability is an important step in pharmaceutical developments to limit possible late failures in preclinical studies. This is particularly crucial for therapeutic peptides whose size generally prevents them from passively entering cells. However, a sequence-structure-dynamics-permeability relationship for peptides still needs further insight to help efficient therapeutic peptide design. In this perspective, we conducted here a computational study for estimating the permeability coefficient of a benchmark peptide by considering and comparing two different physical models: on the one hand, the inhomogeneous solubility-diffusion model, which requires umbrella-sampling simulations, and on the other hand, a chemical kinetics model which necessitates multiple unconstrained simulations. Notably, we assessed the accuracy of the two approaches in relation to their computational cost.

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

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

Peptide adsorption on silica surfaces: Simulation and experimental insights

The understanding of interactions between proteins with silica surface is crucial for a wide range of different applications: from medical devices, drug delivery and bioelectronics to biotechnology and downstream processing. We show the application of EISM (Effective Implicit Surface Model) for discovering the set of peptide interactions with silica surface. The EISM is employed for a high-speed computational screening of peptides to model the binding affinity of small peptides to silica surfaces. The simulations are complemented with experimental data of peptides with silica nanoparticles from microscale thermophoresis and from infrared spectroscopy. The experimental work shows excellent agreement with computational results and verifies the EISM model for the prediction of peptide-surface interactions. 57 peptides, with amino acids favorable for adsorption on Silica surface, are screened by EISM model for obtaining results, which are worth to be considered as a guidance for future experimental and theoretical works. This model can be used as a broad platform for multiple challenges at surfaces which can be applied for multiple surfaces and biomolecules beyond silica and peptides.

Anisaxins, helical antimicrobial peptides from marine parasites, kill resistant bacteria by lipid extraction and membrane disruption

An infecting and propagating parasite relies on its innate defense system to evade the host's immune response and to survive challenges from commensal bacteria. More so for the nematode Anisakis, a marine parasite that during its life cycle encounters both vertebrate and invertebrate hosts and their highly diverse microbiotas. Although much is still unknown about how the nematode mitigates the effects of these microbiota, its antimicrobial peptides likely play an important role in its survival. We identified anisaxins, the first cecropin-like helical antimicrobial peptides originating from a marine parasite, by mining available genomic and transcriptomic data for Anisakis spp. These peptides are potent bactericidal agents in vitro, selectively active against Gram-negative bacteria, including multi-drug resistant strains, at sub-micromolar concentrations. Their interaction with bacterial membranes was confirmed by solid state NMR (ssNMR) and is highly dependent on the peptide concentration as well as peptide to lipid ratio, as evidenced by molecular dynamics (MD) simulations. MD results indicated that an initial step in the membranolytic mode of action involves membrane bulging and lipid extraction; a novel mechanism which may underline the peptides' potency. Subsequent steps include membrane permeabilization leading to leakage of molecules and eventually cell death, but without visible macroscopic damage, as shown by atomic force microscopy and flow cytometry. This membranolytic antibacterial activity does not translate to cytotoxicity towards human peripheral blood mononuclear cells (HPBMCs), which was minimal at well above bactericidal concentrations, making anisaxins promising candidates for further drug development. STATEMENT OF SIGNIFICANCE: Witnessing the rapid spread of antibiotic resistance resulting in millions of infected and dozens of thousands dying worldwide every year, we identified anisaxins, antimicrobial peptides (AMPs) from marine parasites, Anisakis spp., with potent bactericidal activity and selectivity towards multi-drug resistant Gram-negative bacteria. Anisaxins are membrane-active peptides, whose activity, very sensitive to local peptide concentrations, involves membrane bulging and lipid extraction, leading to membrane permeabilization and bacterial cell death. At the same time, their toxicity towards host cells is negligible, which is often not the case for membrane-active AMPs, therefore making them suitable drug candidates. Membrane bulging and lipid extraction are novel concepts that broaden our understanding of peptide interactions with bacterial functional structures, essential for future design of such biomaterials.

Integrated Design of a Membrane-Lytic Peptide-Based Intravenous Nanotherapeutic Suppresses Triple-Negative Breast Cancer

Membrane-lytic peptides offer broad synthetic flexibilities and design potential to the arsenal of anticancer therapeutics, which can be limited by cytotoxicity to noncancerous cells and induction of drug resistance via stress-induced mutagenesis. Despite continued research efforts on membrane-perforating peptides for antimicrobial applications, success in anticancer peptide therapeutics remains elusive given the muted distinction between cancerous and normal cell membranes and the challenge of peptide degradation and neutralization upon intravenous delivery. Using triple-negative breast cancer as a model, the authors report the development of a new class of anticancer peptides. Through function-conserving mutations, the authors achieved cancer cell selective membrane perforation, with leads exhibiting a 200-fold selectivity over non-cancerogenic cells and superior cytotoxicity over doxorubicin against breast cancer tumorspheres. Upon continuous exposure to the anticancer peptides at growth-arresting concentrations, cancer cells do not exhibit resistance phenotype, frequently observed under chemotherapeutic treatment. The authors further demonstrate efficient encapsulation of the anticancer peptides in 20 nm polymeric nanocarriers, which possess high tolerability and lead to effective tumor growth inhibition in a mouse model of MDA-MB-231 triple-negative breast cancer. This work demonstrates a multidisciplinary approach for enabling translationally relevant membrane-lytic peptides in oncology, opening up a vast chemical repertoire to the arms race against cancer.

Hydrophobic mismatch is a key factor in protein transport across lipid bilayer membranes via the Tat pathway

The twin-arginine translocation (Tat) pathway transports folded proteins across membranes in bacteria, thylakoids, plant mitochondria, and archaea. In most species, the active Tat machinery consists of three independent subunits: TatA, TatB, and TatC. TatA and TatB possess short transmembrane alpha helices (TMHs), both of which are only 15 residues long in Escherichia coli. Such short TMHs cause a hydrophobic mismatch between Tat subunits and the membrane bilayer, although the functional significance of this mismatch is unclear. Here, we sought to address the functional importance of the hydrophobic mismatch in the Tat transport mechanism in E. coli. We conducted three different assays to evaluate the effect of TMH length mutants on Tat activity and observed that the TMHs of TatA and TatB appear to be evolutionarily tuned to 15 amino acids, with activity dropping off following any modification of this length. Surprisingly, TatA and TatB with as few as 11 residues in their TMHs can still insert into the membrane bilayer, albeit with a decline in membrane integrity. These findings support a model of Tat transport utilizing localized toroidal pores that form when the membrane bilayer is thinned to a critical threshold. In this context, we conclude that the 15-residue length of the TatA and TatB TMHs can be seen as a compromise between the need for some hydrophobic mismatch to allow the membrane to reversibly reach the threshold thinness required for toroidal pore formation and the permanently destabilizing effect of placing even shorter helices into these energy-transducing membranes.

Synthetic molecular evolution of antimicrobial peptides

As we learn more about how peptide structure and activity are related, we anticipate that antimicrobial peptides will be engineered to have strong potency and distinct functions and that synthetic peptides will have new biomedical applications, such as treatments for emerging infectious diseases. As a result of the enormous number of possible amino acid sequences and the low-throughput nature of antimicrobial peptide assays, computational tools for peptide design and optimization are needed for direct experimentation toward obtaining functional sequences. Recent developments in computational tools have improved peptide design, saving labor, reagents, costs, and time. At the same time, improvements in peptide synthesis and experimental platforms continue to reduce the cost and increase the throughput of peptide-drug screening. In this review, we discuss the current methods of peptide design and engineering, including in silico methods and peptide synthesis and screening, and highlight areas of potential improvement.

How lipids affect the energetics of co-translational alpha helical membrane protein folding

Membrane proteins need to fold with precision in order to function correctly, with misfolding potentially leading to disease. The proteins reside within a hydrophobic lipid membrane and must insert into the membrane and fold correctly, generally whilst they are being translated by the ribosome. Favourable and unfavourable free energy contributions are present throughout each stage of insertion and folding. The unfavourable energy cost of transferring peptide bonds into the hydrophobic membrane interior is compensated for by the favourable hydrophobic effect of partitioning a hydrophobic transmembrane alpha-helix into the membrane. Native membranes are composed of many different types of lipids, but how these different lipids influence folding and the associated free energies is not well understood. Altering the lipids in the bilayer is known to affect the probability of transmembrane helix insertion into the membrane, and lipids also affect protein stability and can promote successful folding. This review will summarise the free energy contributions associated with insertion and folding of alpha helical membrane proteins, as well as how lipids can make these processes more or less favourable. We will also discuss the implications of this work for the free energy landscape during the co-translational folding of alpha helical membrane proteins.

Lipid-mediated antimicrobial resistance: a phantom menace or a new hope?

The proposition of a post-antimicrobial era is all the more realistic with the continued rise of antimicrobial resistance. The development of new antimicrobials is failing to counter the ever-increasing rates of bacterial antimicrobial resistance. This necessitates novel antimicrobials and drug targets. The bacterial cell membrane is an essential and highly conserved cellular component in bacteria and acts as the primary barrier for entry of antimicrobials into the cell. Although previously under-exploited as an antimicrobial target, the bacterial cell membrane is attractive for the development of novel antimicrobials due to its importance in pathogen viability. Bacterial cell membranes are diverse assemblies of macromolecules built around a central lipid bilayer core. This lipid bilayer governs the overall membrane biophysical properties and function of its membrane-embedded proteins. This mini-review will outline the mechanisms by which the bacterial membrane causes and controls resistance, with a focus on alterations in the membrane lipid composition, chemical modification of constituent lipids, and the efflux of antimicrobials by membrane-embedded efflux systems. Thorough insight into the interplay between membrane-active antimicrobials and lipid-mediated resistance is needed to enable the rational development of new antimicrobials. In particular, the union of computational approaches and experimental techniques for the development of innovative and efficacious membrane-active antimicrobials is explored.

Conformational Change from U- to I-Shape of Ion Transporters Facilitates K+ Transport across Lipid Bilayers

We have investigated, at the atomic level, the ion-fishing mechanism underlying the ion transport across membranes mediated by an artificial ion transporter composed of a hydroxyl-rich cholesterol group, a flexible alkyl chain, and a crown ether. Our results show that the transporter can spontaneously insert into the membrane and switch between the folded (U-shaped) and extended (I-shaped) conformations. The free-energy profile associated with the conformational transition indicates that compared with the U-shaped conformation of the transporter, the I-shaped one is thermodynamically more favorable. Furthermore, the free-energy profiles describing the ion translocation reveal that the transporter capturing the ion in U-shape on one side of the membrane and releasing it in I-shape on the other side constitutes a key way for the highly efficient transport of K⁺ ions. We present herewith a rigorous and rational framework to decipher the detailed ion-fishing mechanism of transmembrane ion transport with exceptionally high activity.

Lipid21: Complex Lipid Membrane Simulations with AMBER

We extend the modular AMBER lipid force field to include anionic lipids, polyunsaturated fatty acid (PUFA) lipids, and sphingomyelin, allowing the simulation of realistic cell membrane lipid compositions, including raft-like domains. Head group torsion parameters are revised, resulting in improved agreement with NMR order parameters, and hydrocarbon chain parameters are updated, providing a better match with phase transition temperature. Extensive validation runs (0.9 μs per lipid type) show good agreement with experimental measurements. Furthermore, the simulation of raft-like bilayers demonstrates the perturbing effect of increasing PUFA concentrations on cholesterol molecules. The force field derivation is consistent with the AMBER philosophy, meaning it can be easily mixed with protein, small molecule, nucleic acid, and carbohydrate force fields.

Helical structure motifs made searchable for functional peptide design

The systematic design of functional peptides has technological and therapeutic applications. However, there is a need for pattern-based search engines that help locate desired functional motifs in primary sequences regardless of their evolutionary conservation. Existing databases such as The Protein Secondary Structure database (PSS) no longer serves the community, while the Dictionary of Protein Secondary Structure (DSSP) annotates the secondary structures when tertiary structures of proteins are provided. Here, we extract 1.7 million helices from the PDB and compile them into a database (Therapeutic Peptide Design database; TP-DB) that allows queries of compounded patterns to facilitate the identification of sequence motifs of helical structures. We show how TP-DB helps us identify a known purification-tag-specific antibody that can be repurposed into a diagnostic kit for Helicobacter pylori. We also show how the database can be used to design a new antimicrobial peptide that shows better Candida albicans clearance and lower hemolysis than its template homologs. Finally, we demonstrate how TP-DB can suggest point mutations in helical peptide blockers to prevent a targeted tumorigenic protein-protein interaction. TP-DB is made available at http://dyn.life.nthu.edu.tw/design/ .

Predicting Membrane-Active Peptide Dynamics in Fluidic Lipid Membranes

Understanding the interactions between peptides and lipid membranes could not only accelerate the development of antimicrobial peptides as treatments for infections but also be applied to finding targeted therapies for cancer and other diseases. However, designing biophysical experiments to study molecular interactions between flexible peptides and fluidic lipid membranes has been an ongoing challenge. Recently, with hardware advances, algorithm improvements, and more accurate parameterizations (i.e., force fields), all-atom molecular dynamics (MD) simulations have been used as a "computational microscope" to investigate the molecular interactions and mechanisms of membrane-active peptides in cell membranes (Chen et al., Curr Opin Struct Biol 61:160-166, 2020; Ulmschneider and Ulmschneider, Acc Chem Res 51(5):1106-1116, 2018; Dror et al., Annu Rev Biophys 41:429-452, 2012). In this chapter, we describe how to utilize MD simulations to predict and study peptide dynamics and how to validate the simulations by circular dichroism, intrinsic fluorescent probe, membrane leakage assay, electrical impedance, and isothermal titration calorimetry. Experimentally validated MD simulations open a new route towards peptide design starting from sequence and structure and leading to desirable functions.

Computational methods and theory for ion channel research

Ion channels are fundamental biological devices that act as gates in order to ensure selective ion transport across cellular membranes; their operation constitutes the molecular mechanism through which basic biological functions, such as nerve signal transmission and muscle contraction, are carried out. Here, we review recent results in the field of computational research on ion channels, covering theoretical advances, state-of-the-art simulation approaches, and frontline modeling techniques. We also report on few selected applications of continuum and atomistic methods to characterize the mechanisms of permeation, selectivity, and gating in biological and model channels.

Antimicrobial Peptides: An Update on Classifications and Databases

Antimicrobial peptides (AMPs) are distributed across all kingdoms of life and are an indispensable component of host defenses. They consist of predominantly short cationic peptides with a wide variety of structures and targets. Given the ever-emerging resistance of various pathogens to existing antimicrobial therapies, AMPs have recently attracted extensive interest as potential therapeutic agents. As the discovery of new AMPs has increased, many databases specializing in AMPs have been developed to collect both fundamental and pharmacological information. In this review, we summarize the sources, structures, modes of action, and classifications of AMPs. Additionally, we examine current AMP databases, compare valuable computational tools used to predict antimicrobial activity and mechanisms of action, and highlight new machine learning approaches that can be employed to improve AMP activity to combat global antimicrobial resistance.

Modeling lipid-protein interactions for coarse-grained lipid and Cα protein models

Biological membranes that play major roles in diverse functions are composed of numerous lipids and proteins, making them an important target for coarse-grained (CG) molecular dynamics (MD) simulations. Recently, we have developed the CG implicit solvent lipid force field (iSoLF) that has a resolution compatible with the widely used Cα protein representation [D. Ugarte La Torre and S. Takada, J. Chem. Phys. 153, 205101 (2020)]. In this study, we extended it and developed a lipid-protein interaction model that allows the combination of the iSoLF and the Cα protein force field, AICG2+. The hydrophobic-hydrophilic interaction is modeled as a modified Lennard-Jones potential in which parameters were tuned partly to reproduce the experimental transfer free energy and partly based on the free energy profile normal to the membrane surface from previous all-atom MD simulations. Then, the obtained lipid-protein interaction is tested for the configuration and placement of transmembrane proteins, water-soluble proteins, and peripheral proteins, showing good agreement with prior knowledge. The interaction is generally applicable and is implemented in the publicly available software, CafeMol.

Spontaneous transmembrane pore formation by short-chain synthetic peptide

Amphiphilic β-peptides, which are synthetically designed short-chain helical foldamers of β-amino acids, are established potent biomimetic alternatives of natural antimicrobial peptides. An intriguing question is how the distinct molecular architecture of these short-chain and rigid synthetic peptides translates to its potent membrane-disruption ability. Here, we address this question via a combination of all-atom and coarse-grained molecular dynamics simulations of the interaction of mixed phospholipid bilayer with an antimicrobial 10-residue globally amphiphilic helical β-peptide at a wide range of concentrations. The simulation demonstrates that multiple copies of this synthetic peptide, initially placed in aqueous solution, readily self-assemble and adsorb at membrane interface. Subsequently, beyond a threshold peptide/lipid ratio, the surface-adsorbed oligomeric aggregate moves inside the membrane and spontaneously forms stable water-filled transmembrane pores via a cooperative mechanism. The defects induced by these pores lead to the dislocation of interfacial lipid headgroups, membrane thinning, and substantial water leakage inside the hydrophobic core of the membrane. A molecular analysis reveals that despite having a short architecture, these synthetic peptides, once inside the membrane, would stretch themselves toward the distal leaflet in favor of potential contact with polar headgroups and interfacial water layer. The pore formed in coarse-grained simulation was found to be resilient upon structural refinement. Interestingly, the pore-inducing ability was found to be elusive in a non-globally amphiphilic sequence isomer of the same β-peptide, indicating strong sequence dependence. Taken together, this work puts forward key perspectives of membrane activity of minimally designed synthetic biomimetic oligomers relative to the natural antimicrobial peptides.

A photoswitchable helical peptide with light-controllable interface/transmembrane topology in lipidic membranes

The spontaneous insertion of helical transmembrane (TM) polypeptides into lipid bilayers is driven by three sequential equilibria: solution-to-membrane interface (MI) partition, unstructured-to-helical folding, and MI-to-TM helix insertion. A bottleneck for understanding these three steps is the lack of experimental approaches to perturb membrane-bound hydrophobic polypeptides out of equilibrium rapidly and reversibly. Here, we report on a 24-residues-long hydrophobic α-helical polypeptide, covalently coupled to an azobenzene photoswitch (KCALP-azo), which displays a light-controllable TM/MI equilibrium in hydrated lipid bilayers. FTIR spectroscopy reveals that trans KCALP-azo folds as a TM α-helix (TM topology). After trans-to-cis photoisomerization of the azobenzene moiety with UV light (reversed with blue light), the helical structure of KCALP-azo is maintained, but its helix tilt increased from 32 ± 5° to 79 ± 8°, indication of a reversible TM-to-MI transition. Further analysis indicates that this transition is incomplete, with cis KCALP-azo existing in a ∼90% TM and ∼10% MI mixture.

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We present an α-helical transmembrane peptide modified with a molecular photoswitch

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The peptide exhibits reversible photocontrol of its membrane topology

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A fraction moves to the membrane interface with UV and inserts back with blue light

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This system will be useful to address the molecular mechanism for membrane insertion

Computational Methods and Tools in Antimicrobial Peptide Research

The evolution of antibiotic-resistant bacteria is an ongoing and troubling development that has increased the number of diseases and infections that risk going untreated. There is an urgent need to develop alternative strategies and treatments to address this issue. One class of molecules that is attracting significant interest is that of antimicrobial peptides (AMPs). Their design and development has been aided considerably by the applications of molecular models, and we review these here. These methods include the use of tools to explore the relationships between their structures, dynamics, and functions and the increasing application of machine learning and molecular dynamics simulations. This review compiles resources such as AMP databases, AMP-related web servers, and commonly used techniques, together aimed at aiding researchers in the area toward complementing experimental studies with computational approaches.

Improved Protocol to Tackle the pH Effects on Membrane-Inserting Peptides

Many important biological pathways rely on membrane-interacting peptides or proteins, which can alter the biophysical properties of the cell membrane by simply adsorbing to its surface to undergo a full insertion process. To study these phenomena with atomistic detail, model peptides have been used to refine the current computational methodologies. Improvements have been made with force-field parameters, enhanced sampling techniques to obtain faster sampling, and the addition of chemical-physical properties, such as pH, whose influence dramatically increases at the water/membrane interface. The pH (low) insertion peptide (pHLIP) is a peptide that inserts across a membrane bilayer depending on the pH due to the presence of a key residue (Asp14) whose acidity-induced protonation triggers the whole process. The complex nature of these peptide/membrane interactions resulted in sampling limitations of the protonation and configurational space albeit using state-of-the-art methods such as the constant-pH molecular dynamics. To address this issue and circumvent those limitations, new simulations were performed with our newly developed pH-replica exchange method using wild-type (wt)-pHLIP in different 2-oleoyl-1-palmitoyl-sn-glycero-3-phosphocholine membrane sizes. This technique provided enhanced sampling and allowed for the calculation of more complete Asp14 pK_a profiles. The conformational heterogeneity derived from strong electrostatic interactions between Asp14 and the lipid phosphate groups was identified as the source of most pK_a variability. In spite of these persistent and harder-to-equilibrate phosphate interactions, the pK_a values at deeper regions (6.0-6.2) still predicted the experimental pK of insertion (6.0) since the electrostatic perturbation decays as the residue inserts further into the membrane. We also observed that reducing the system size leads to membrane deformations where it increasingly loses the ability to accommodate the pHLIP-induced perturbations. This indicates that large membrane patches, such as 256 or even 352 lipids, are needed to obtain stable and more realistic pHLIP/membrane systems. These results strengthen our method pK_a predictive and analytical capabilities to study the intricate play of electrostatic effects of the peptide/membrane interface, granting confidence for future applications in similar systems.

"Dividing and Conquering" and "Caching" in Molecular Modeling

Molecular modeling is widely utilized in subjects including but not limited to physics, chemistry, biology, materials science and engineering. Impressive progress has been made in development of theories, algorithms and software packages. To divide and conquer, and to cache intermediate results have been long standing principles in development of algorithms. Not surprisingly, most important methodological advancements in more than half century of molecular modeling are various implementations of these two fundamental principles. In the mainstream classical computational molecular science, tremendous efforts have been invested on two lines of algorithm development. The first is coarse graining, which is to represent multiple basic particles in higher resolution modeling as a single larger and softer particle in lower resolution counterpart, with resulting force fields of partial transferability at the expense of some information loss. The second is enhanced sampling, which realizes "dividing and conquering" and/or "caching" in configurational space with focus either on reaction coordinates and collective variables as in metadynamics and related algorithms, or on the transition matrix and state discretization as in Markov state models. For this line of algorithms, spatial resolution is maintained but results are not transferable. Deep learning has been utilized to realize more efficient and accurate ways of "dividing and conquering" and "caching" along these two lines of algorithmic research. We proposed and demonstrated the local free energy landscape approach, a new framework for classical computational molecular science. This framework is based on a third class of algorithm that facilitates molecular modeling through partially transferable in resolution "caching" of distributions for local clusters of molecular degrees of freedom. Differences, connections and potential interactions among these three algorithmic directions are discussed, with the hope to stimulate development of more elegant, efficient and reliable formulations and algorithms for "dividing and conquering" and "caching" in complex molecular systems.

Emerging Emulsifiers: Conceptual Basis for the Identification and Rational Design of Peptides with Surface Activity

Emulsifiers are gradually evolving from synthetic molecules of petrochemical origin to biomolecules mainly due to health and environmental concerns. Peptides represent a type of biomolecules whose molecular structure is composed of a sequence of amino acids that can be easily tailored to have specific properties. However, the lack of knowledge about emulsifier behavior, structure-performance relationships, and the implementation of different design routes have limited the application of these peptides. Some computational and experimental approaches have tried to close this knowledge gap, but restrictions in understanding the fundamental phenomena and the limited property data availability have made the performance prediction for emulsifier peptides an area of intensive research. This study provides the concepts necessary to understand the emulsifying behavior of peptides. Additionally, a straightforward description is given of how the molecular structure and conditions of the system directly impact the peptides' ability to stabilize emulsion droplets. Moreover, the routes to design and discover novel peptides with interfacial and emulsifying activity are also discussed, along with the strategies to address some of their major pitfalls and challenges. Finally, this contribution reviews methodologies to build and use data sets containing standard properties of emulsifying peptides by looking at successful applications in different fields.

The Effect of Cholesterol on Membrane-Bound Islet Amyloid Polypeptide

Islet amyloid polypeptide (IAPP) is a proposed cause of the decreased beta-cell mass in patients with type-II diabetes. The molecular composition of the cell-membrane is important for regulating IAPP cytotoxicity and aggregation. Cholesterol is present at high concentrations in the pancreatic beta-cells, and in-vitro experiments have indicated that it affects the amyloid formation of IAPP either by direct interactions or by changing the properties of the membrane. In this study we apply atomistic, unbiased molecular dynamics simulations at a microsecond timescale to investigate the effect of cholesterol on membrane bound IAPP. Simulations were performed with various combinations of cholesterol, phosphatidylcholine (PC) and phosphatidylserine (PS) lipids. In all simulations, the helical structure of monomer IAPP was stabilized by the membrane. We found that cholesterol decreased the insertion depth of IAPP compared to pure phospholipid membranes, while PS lipids counteract the effect of cholesterol. The aggregation propensity has previously been proposed to correlate with the insertion depth of IAPP, which we found to decrease with the increased ordering of the lipids induced by cholesterol. Cholesterol is depleted in the vicinity of IAPP, and thus our results suggest that the effect of cholesterol is indirect.