Biological Membrane-Penetrating Peptides: Computational Prediction and Applications

Peptide‑based therapeutic strategies for glioma: Current state and prospects

Glioma is a prevalent form of primary malignant central nervous system tumor, characterized by its cellular invasiveness, rapid growth, and the presence of the blood-brain barrier (BBB)/blood-brain tumor barrier (BBTB). Current therapeutic approaches, such as chemotherapy and radiotherapy, have shown limited efficacy in achieving significant antitumor effects. Therefore, there is an urgent demand for new treatments. Therapeutic peptides represent an innovative class of pharmaceutical agents with lower immunogenicity and toxicity. They are easily modifiable via chemical means and possess deep tissue penetration capabilities which reduce side effects and drug resistance. These unique pharmacokinetic characteristics make peptides a rapidly growing class of new therapeutics that have demonstrated significant progress in glioma treatment. This review outlines the efforts and accomplishments in peptide-based therapeutic strategies for glioma. These therapeutic peptides can be classified into four types based on their anti-tumor function: tumor-homing peptides, inhibitor/antagonist peptides targeting cell surface receptors, interference peptides, and peptide vaccines. Furthermore, we briefly summarize the results from clinical trials of therapeutic peptides in glioma, which shows that peptide-based therapeutic strategies exhibit great potential as multifunctional players in glioma therapy.

Improving the antimicrobial activity of RP9 peptide through theoretical and experimental investigation

Future threats to humanity may stem from the rise of antimicrobial resistance, which has compromised the effectiveness of existing antibiotics. Antimicrobial peptides possess the ability to directly eliminate pathogens and cancer cells, generally without the development of resistance. Among these peptides is RP9 (RGSALTHLP), derived from the white blood cells of crocodiles. In this research, three mutations were initially designed: LR-mut (RGSALTHLR), KR-mut (RGSAKTHLR), and WP-mut (RGSAWTHLP). The physicochemical characteristics of these peptides were assessed, revealing that KR-mut exhibited the most favorable biophysical properties. Subsequently, twenty molecular dynamics simulations were conducted for all peptides in pure water and at four different octanol concentrations (30 %, 50 %, 70 %, and 100 %) to evaluate their biophysical attributes. The findings from the 4000 ns molecular dynamics simulations revealed that the KR-mut exhibited reduced values of RMSD, the radius of gyration, solvent accessible surface area, and RMSF, while simultaneously showing an increased number of hydrogen bonds and interactions with water molecules. This peptide also showed the lowest free energy of solvation and the highest solubility across various octanol concentrations compared to the other peptides. The results obtained from the biophysical assessments and molecular dynamics simulations were consistent, resulting in the conclusion that KR-mut is expected to exhibit superior antibacterial activity compared to both the other mutated peptides and the wild type peptides. These theoretical findings were validated through experimental minimum inhibitory concentration (MIC) tests on gram-negative Escherichia coli and gram-positive Staphylococcus aureus. The outcomes of this study suggest that molecular dynamics simulations can effectively predict changes in the bactericidal efficacy of peptides at varying octanol concentrations, potentially enhancing the speed and efficiency of antimicrobial peptide design while reducing associated costs.

Computational Insights into Membrane Disruption by Cell-Penetrating Peptides

Cell-penetrating peptides (CPPs) can translocate into cells without inducing cytotoxicity. The internalization process implies several steps at different time scales ranging from microseconds to minutes. We combine adaptive Steered Molecular Dynamics (aSMD) with conventional Molecular Dynamics (cMD) to observe nonequilibrium and equilibrium states to study the early mechanisms of peptide-bilayer interaction leading to CPPs internalization. We define three membrane compositions representing bilayer sections, neutral lipids (i.e., upper leaflet), neutral lipids with cholesterol (i.e., hydrophobic core), and neutral/negatively charged lipids with cholesterol (i.e., lower leaflet) to study the energy barriers and disruption mechanisms of Arg9, MAP, and TP2, representing cationic, amphiphilic, and hydrophobic CPPs, respectively. Cholesterol and negatively charged lipids increase the energetic barriers for the peptide-bilayer crossing. TP2 interacts with the bilayer by hydrophobic insertion, while Arg9 disrupts the bilayer by forming transient or stable pores. MAP has shown both behaviors. Collectively, these findings underscore the significance of innovative computational approaches in studying membrane-disruptive peptides and, more specifically, in harnessing their potential for cell penetration.

Flexible fluorine-thiol displacement stapled peptides with enhanced membrane penetration for the estrogen receptor/coactivator interaction

Understanding how natural and engineered peptides enter cells would facilitate the elucidation of biochemical mechanisms underlying cell biology and is pivotal for developing effective intracellular targeting strategies. In this study, we demonstrate that our peptide stapling technique, fluorine-thiol displacement reaction (FTDR), can produce flexibly constrained peptides with significantly improved cellular uptake, particularly into the nucleus. This platform confers enhanced flexibility, which is further amplified by the inclusion of a D-amino acid, while maintaining environment-dependent α helicity, resulting in highly permeable peptides without the need for additional cell-penetrating motifs. Targeting the estrogen receptor α (ERα)-coactivator interaction prevalent in estrogen receptor-positive (ER+) breast cancers, we showcased that FTDR-stapled peptides, notably SRC2-LD, achieved superior internalization, including cytoplasmic and enriched nuclear uptake, compared to peptides stapled by ring-closing metathesis. These FTDR-stapled peptides use different mechanisms of cellular uptake, including energy-dependent transport such as actin-mediated endocytosis and macropinocytosis. As a result, FTDR peptides exhibit enhanced antiproliferative effects despite their slightly decreased target affinity. Our findings challenge existing perceptions of cell permeability, emphasizing the possibly incomplete understanding of the structural determinants vital for cellular uptake of peptide-like macromolecules. Notably, while α helicity and lipophilicity are positive indicators, they alone are insufficient to determine high-cell permeability, as evidenced by our less helical, more flexible, and less lipophilic FTDR-stapled peptides.

Designed Cell-Penetrating Peptide Constructs for Inhibition of Pathogenic Protein Self-Assembly

Peptides possess a number of pharmacologically desirable properties, including greater chemical diversity than other biomolecule classes and the ability to selectively bind to specific targets with high potency, as well as biocompatibility, biodegradability, and ease and low cost of production. Consequently, there has been considerable interest in developing peptide-based therapeutics, including amyloid inhibitors. However, a major hindrance to the successful therapeutic application of peptides is their poor delivery to target tissues, cells or subcellular organelles. To overcome these issues, recent efforts have focused on engineering cell-penetrating peptide (CPP) antagonists of amyloidogenesis, which combine the attractive intrinsic properties of peptides with potent therapeutic effects (i.e., inhibition of amyloid formation and the associated cytotoxicity) and highly efficient delivery (to target tissue, cells, and organelles). This review highlights some promising CPP constructs designed to target amyloid aggregation associated with a diverse range of disorders, including Alzheimer's disease, transmissible spongiform encephalopathies (or prion diseases), Parkinson's disease, and cancer.

MolGC: molecular geometry comparator algorithm for bond length mean absolute error computation on molecules

Density Functional Theory (DFT) is extensively used in theoretical and computational chemistry to study molecular and crystal properties across diverse fields, including quantum chemistry, materials physics, catalysis, biochemistry, and surface science. Despite advances in DFT hardware and software for optimized geometries, achieving consensus in molecular structure comparisons with experimental counterparts remains a challenge. This difficulty is exacerbated by the lack of automated bond length comparison tools, resulting in labor-intensive and error-prone manual processes. To address these challenges, we propose MolGC, a Molecular Geometry Comparator algorithm that automates the comparison of optimized geometries from different theoretical levels. MolGC calculates the mean absolute error (MAE) of bond lengths by integrating data from various DFT software. It provides interactive and customizable visualization of geometries, enabling users to explore different views for enhanced analysis. In addition, it saves MAE computations for further analysis and offers a comprehensive statistical summary of the results. MolGC effectively addresses complex graph labeling challenges, ensuring accurate identification and categorization of bonds in diverse chemical structures. It achieves a 98.91% average rate in correct bond label assignments on an antibiotics dataset, showcasing its effectiveness for comparing molecular bond lengths across geometries of varying complexity and size. The executable file and software resources for running MolGC can be downloaded from https://github.com/AbimaelGP/MolGC/tree/main .

Peptidomimetics design and characterization: Bridging experimental and computer-based approaches

Peptidomimetics, designed to mimic peptide biological activity with more drug-like properties, are increasingly pivotal in medicinal chemistry. They offer enhanced systemic delivery, cell penetration, target specificity, and protection against peptidases when compared to their native peptide counterparts. Already utilized in treating diverse diseases like neurodegenerative disorders, cancer and infectious diseases, their future in medicine seems bright, with many peptidomimetics in clinical trials or development stages. Peptidomimetics are well-suited for addressing disturbed protein-protein interactions (PPIs), which often underlie various pathologies. Structural biology and computational methods like molecular dynamics simulations facilitate rational design, whereas machine learning algorithms accelerate protein structure prediction, enabling efficient drug development. Experimental validation via various spectroscopic, biophysical, and biochemical assays confirms computational predictions and guides further optimization. Peptidomimetics, with their tailored constrained structures, represent a frontier in drug design focused on targeting PPIs. In this overview, we present a comprehensive landscape of peptidomimetics, encompassing perspectives on involvement in pathologies, chemical strategies, and methodologies for their characterization, spanning in silico, in vitro and in cell approaches. With increasing interest from pharmaceutical sectors, peptidomimetics hold promise for revolutionizing therapeutic approaches, marking a new era of precision drug discovery.

Polyamidoamine Dendrimers: Brain-Targeted Drug Delivery Systems in Glioma Therapy

Glioma is the most common primary intracranial tumor, which is formed by the malignant transformation of glial cells in the brain and spinal cord. It has the characteristics of high incidence, high recurrence rate, high mortality and low cure rate. The treatments for glioma include surgical removal, chemotherapy and radiotherapy. Due to the obstruction of the biological barrier of brain tissue, it is difficult to achieve the desired therapeutic effects. To address the limitations imposed by the brain's natural barriers and enhance the treatment efficacy, researchers have effectively used brain-targeted drug delivery systems (DDSs) in glioma therapy. Polyamidoamine (PAMAM) dendrimers, as branched macromolecular architectures, represent promising candidates for studies in glioma therapy. This review focuses on PAMAM-based DDSs in the treatment of glioma, highlighting their physicochemical characteristics, structural properties as well as an overview of the toxicity and safety profiles.

Structure-aware machine learning strategies for antimicrobial peptide discovery

Machine learning models are revolutionizing our approaches to discovering and designing bioactive peptides. These models often need protein structure awareness, as they heavily rely on sequential data. The models excel at identifying sequences of a particular biological nature or activity, but they frequently fail to comprehend their intricate mechanism(s) of action. To solve two problems at once, we studied the mechanisms of action and structural landscape of antimicrobial peptides as (i) membrane-disrupting peptides, (ii) membrane-penetrating peptides, and (iii) protein-binding peptides. By analyzing critical features such as dipeptides and physicochemical descriptors, we developed models with high accuracy (86-88%) in predicting these categories. However, our initial models (1.0 and 2.0) exhibited a bias towards α-helical and coiled structures, influencing predictions. To address this structural bias, we implemented subset selection and data reduction strategies. The former gave three structure-specific models for peptides likely to fold into α-helices (models 1.1 and 2.1), coils (1.3 and 2.3), or mixed structures (1.4 and 2.4). The latter depleted over-represented structures, leading to structure-agnostic predictors 1.5 and 2.5. Additionally, our research highlights the sensitivity of important features to different structure classes across models.

Conjugation of sulpiride with a cell penetrating peptide to augment the antidepressant efficacy and reduce serum prolactin levels

Depression ranks as the fourth most prevalent global disease, with suicide incidents occurring at a younger age. Sulpiride (SUL), an atypical antidepressant drug acting as a dopamine D2 receptor antagonist and possessing anti-inflammatory properties, exhibits limited ability to penetrate the blood brain barrier (BBB). This weak penetration hampers its inhibitory effect on prolactin release in the pituitary gland, consequently leading to hyperprolactinemia. In order to enhance the central nervous system efficacy of sulpiride and reduce serum prolactin levels, we covalently linked sulpiride to VPALR derived from the nuclear DNA repair protein ku70. In vivo study on depressive mice using intraperitoneal injection of VPALR-SUL demonstrated a significant increase in struggle time and total distance compared to those treated with only sulpiride while also reducing serum prolactin concentration. The pharmacokinetic study results showed that VPALR-SUL prolonged half-life and increased bioavailability. In conclusion, VPALR-SUL exhibited potential for enhancing sulpiride transport across the BBB, augmenting its antidepressant effects, and reducing serum prolactin levels. This study laid a foundation for improving sulpiride delivery and developing novel antidepressants.

BrainPepPass: A Framework Based on Supervised Dimensionality Reduction for Predicting Blood-Brain Barrier-Penetrating Peptides

Peptides that pass through the blood-brain barrier (BBB) not only are implicated in brain-related pathologies but also are promising therapeutic tools for treating brain diseases, e.g., as shuttles carrying active medicines across the BBB. Computational prediction of BBB-penetrating peptides (B3PPs) has emerged as an interesting approach because of its ability to screen large peptide libraries in a cost-effective manner. In this study, we present BrainPepPass, a machine learning (ML) framework that utilizes supervised manifold dimensionality reduction and extreme gradient boosting (XGB) algorithms to predict natural and chemically modified B3PPs. The results indicate that the proposed tool outperforms other classifiers, with average accuracies exceeding 94% and 98% in 10-fold cross-validation and leave-one-out cross-validation (LOOCV), respectively. In addition, accuracy values ranging from 45% to 97.05% were achieved in the independent tests. The BrainPepPass tool is available in a public repository for academic use (https://github.com/ewerton-cristhian/BrainPepPass).

Advances in peptide-based drug delivery systems

Drug delivery systems (DDSs) are designed to deliver drugs to their specific targets to minimize their toxic effects and improve their susceptibility to clearance during targeted transport. Peptides have high affinity, low immunogenicity, simple amino acid composition, and adjustable molecular size; therefore, most peptides can be coupled to drugs via linkers to form peptide-drug conjugates (PDCs) and act as active pro-drugs. PDCs are widely thought to be promising DDSs, given their ability to improve drug bio-compatibility and physiological stability. Peptide-based DDSs are often used to deliver therapeutic substances such as anti-cancer drugs and nucleic acid-based drugs, which not only slow the degradation rate of drugs in vivo but also ensure the drug concentration at the targeted site and prolong the half-life of drugs in vivo. This article provides an profile of the advancements and future development in functional peptide-based DDSs both domestically and internationally in recent years, in the expectation of achieving targeted drug delivery incorporating functional peptides and taking full advantage of synergistic effects.

Lipid-based nanoparticles to address the limitations of GBM therapy by overcoming the blood-brain barrier, targeting glioblastoma stem cells, and counteracting the immunosuppressive tumor microenvironment

Glioblastoma multiforme (GBM) is the most common primary malignant brain tumor, characterized by high heterogeneity, strong invasiveness, poor prognosis, and a low survival rate. A broad range of nanoparticles have been recently developed as drug delivery systems for GBM therapy owing to their inherent size effect and ability to cross the blood-brain barrier (BBB). Lipid-based nanoparticles (LBNPs), such as liposomes, solid lipid NPs (SLNs), and nano-structured lipid carriers (NLCs), have emerged as the most promising drug delivery system for the treatment of GBM because of their unique size, surface modification possibilities, and proven bio-safety. In this review, the main challenges of the current clinical treatment of GBM and the strategies on how novel LBNPs overcome them were explored. The application and progress of LBNP-based drug delivery systems in GBM chemotherapy, immunotherapy, and gene therapy in recent years were systematically reviewed, and the prospect of LBNPs for GBM treatment was discussed.

Exploring the neuroprotective potential of antimicrobial peptides from Dinoponera quadriceps venom against pentylenetetrazole-induced seizures in vivo

Epilepsy affects around 50 million people worldwide and 30% of patients have difficulty controlling the disease. The search for substances that can fill the existing gaps in the treatment of epilepsy is of great importance. Arthropod venoms are promising sources for this purpose due to the presence of small peptides that modulate the activity of ion channels and neuron receptors. The aim of this study was to investigate dinoponeratoxins from the Dinoponera quadriceps ant venom (M-PONTX-Dq3a, M-PONTX-Dq3b and M-PONTX-Dq3c) as potential anticonvulsants. We evaluated them in a seizure model induced by pentylenetetrazole (PTZ) in male swiss mice. Interestingly, intraperitoneal treatment with each peptide increased the time until the first seizure and the percentage of survival, with M-PONTX-Dq3b showing the best results. M-PONTX-Dq3a was discarded due to the appearance of some signs of toxicity with the increase in malondialdehyde (MDA) levels in the striatum. Both, M-PONTX-Dq3b and M-PONTX-Dq3c decreased iNOS and TNF-α in the hippocampus. Notably, M-PONTX-Dq3c treatment decreased the levels of MDA and nitrite in the cortex and hippocampus. Our results indicate that, M-PONTX-Dq3b and M-PONTX-Dq3c have anticonvulsant activity and exhibit anti-inflammatory effects in epilepsy, offering new perspectives for biopharmaceutical development.

Cell-Penetrating Milk-Derived Peptides with a Non-Inflammatory Profile

Milk-derived peptides are known to confer anti-inflammatory effects. We hypothesised that milk-derived cell-penetrating peptides might modulate inflammation in useful ways. Using computational techniques, we identified and synthesised peptides from the milk protein Alpha-S1-casein that were predicted to be cell-penetrating using a machine learning predictor. We modified the interpretation of the prediction results to consider the effects of histidine. Peptides were then selected for testing to determine their cell penetrability and anti-inflammatory effects using HeLa cells and J774.2 mouse macrophage cell lines. The selected peptides all showed cell penetrating behaviour, as judged using confocal microscopy of fluorescently labelled peptides. None of the peptides had an effect on either the NF-κB transcription factor or TNFα and IL-1β secretion. Thus, the identified milk-derived sequences have the ability to be internalised into the cell without affecting cell homeostatic mechanisms such as NF-κB activation. These peptides are worthy of further investigation for other potential bioactivities or as a naturally derived carrier to promote the cellular internalisation of other active peptides.

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.

Effects of C-Terminal Lys-Arg Residue of AapA1 Protein on Toxicity and Structural Mechanism

Previous experimental investigations have established the indispensability of the C-terminal Lys-Arg residues in the toxic activity of the AapA1 toxin protein. AapA1 is classified as a type I toxin-antitoxin (TA) bacterial toxin, and the precise impact of the C-terminal Lys-Arg residues on its structure and mechanism of action remains elusive. To address this knowledge gap, the present study employed molecular dynamics (MD) and enhanced sampling Well-tempered Two-dimensional Metadynamics (2D-MetaD) simulations to examine the behavior of the C-terminal Lys-Arg residues of truncated AapA1 toxin (AapA1-28) within the inner membrane of Escherichia coli. Specifically, the study focused on the elucidation of possible conformation states of AapA1-28 protein in POPE/POPG (3:1) bilayers and their interactions between the protein and POPE/POPG (3:1) bilayers. The findings of our investigation indicate that the AapA1-28 protein does not adopt a vertical orientation upon membrane insertion; rather, it assumes an angled conformation, with the side chain of Lys-23 directed toward the upper layer of the membrane. This non-transmembrane conformation of AapA1-28 protein impedes its ability to form pores within the membrane, resulting in reduced toxicity towards Escherichia coli. These results suggest that C-Terminal positively charged residues are essential for electrostatic binding to the negatively charged head group of bottom bilayer membrane, which stabilize the transmembrane conformation. These outcomes contribute to our comprehension of the impact of C-terminal charged residues on the structure and functionality of membrane-associated proteins, and provide an improved understanding of how protein sequence influences the antimicrobial effect.

Antimicrobial and Cell-Penetrating Peptides: Understanding Penetration for the Design of Novel Conjugate Antibiotics

Antimicrobial peptides (AMPs) are short oligopeptides that can penetrate the bacterial inner and outer membranes. Together with cell-penetrating peptides (CPPs), they are called membrane active peptides; peptides which can translocate across biological membranes. Over the last fifty years, attempts have been made to understand the molecular features that drive the interactions of membranes with membrane active peptides. This review examines the features of a membrane these peptides exploit for translocation, as well as the physicochemical characteristics of membrane active peptides which are important for translocation. Moreover, it presents examples of how these features have been used in recent years to create conjugates consisting of a membrane active peptide, called a "vector", attached to either a current or novel antibiotic, called a "cargo" or "payload". In addition, the review discusses what properties may contribute to an ideal peptide vector able to deliver cargoes across the bacterial outer membrane as the rising issue of antimicrobial resistance demands new strategies to be employed to combat this global public health threat.

Peptide Shuttles for Blood–Brain Barrier Drug Delivery

The blood–brain barrier (BBB) limits the delivery of therapeutics to the brain but also represents the main gate for nutrient entrance. Targeting the natural transport mechanisms of the BBB offers an attractive route for brain drug delivery. Peptide shuttles are able to use these mechanisms to increase the transport of compounds that cannot cross the BBB unaided. As peptides are a group of biomolecules with unique physicochemical and structural properties, the field of peptide shuttles has substantially evolved in the last few years. In this review, we analyze the main classifications of BBB–peptide shuttles and the leading sources used to discover them.

An optimized ionizable cationic lipid for brain tumor-targeted siRNA delivery and glioblastoma immunotherapy

Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor with a high mortality rate. Immunotherapy has achieved promising clinical results in multiple cancers, but shows unsatisfactory outcome in GBM patients, and poor drug delivery across the blood-brain barrier (BBB) is believed to be one of the main limitations that hinder the therapeutic efficacy of drugs. Herein, a new cationic lipid nanoparticle (LNP) that can efficiently deliver siRNA across BBB and target mouse brain is prepared for modulating the tumor microenvironment for GBM immunotherapy. By designing and screening cationic LNPs with different ionizable amine headgroups, a lipid (named as BAMPA-O16B) is identified with an optimal acid dissociation constant (pKa) that significantly enhances the cellular uptake and endosomal escape of siRNA lipoplex in mouse GBM cells. Importantly, BAMPA-O16B/siRNA lipoplex is highly effective to deliver siRNA against CD47 and PD-L1 across the BBB into cranial GBM in mice, and downregulate target gene expression in the tumor, resulting in synergistically activating a T cell-dependent antitumor immunity in orthotopic GBM. Collectively, this study offers an effective strategy for brain targeted siRNA delivery and gene silencing by optimizing the physicochemical property of LNPs. The effectiveness of modulating immune environment of GBM could further be expanded for potential treatment of other brain tumors.

Start Me Up: How Can Surrounding Gangliosides Affect Sodium-Potassium ATPase Activity and Steer towards Pathological Ion Imbalance in Neurons?

Gangliosides, amphiphilic glycosphingolipids, tend to associate laterally with other membrane constituents and undergo extensive interactions with membrane proteins in cis or trans configurations. Studies of human diseases resulting from mutations in the ganglioside biosynthesis pathway and research on transgenic mice with the same mutations implicate gangliosides in the pathogenesis of epilepsy. Gangliosides are reported to affect the activity of the Na⁺/K⁺-ATPase, the ubiquitously expressed plasma membrane pump responsible for the stabilization of the resting membrane potential by hyperpolarization, firing up the action potential and ion homeostasis. Impaired Na⁺/K⁺-ATPase activity has also been hypothesized to cause seizures by several mechanisms. In this review we present different epileptic phenotypes that are caused by impaired activity of Na⁺/K⁺-ATPase or changed membrane ganglioside composition. We further discuss how gangliosides may influence Na⁺/K⁺-ATPase activity by acting as lipid sorting machinery providing the optimal stage for Na⁺/K⁺-ATPase function. By establishing a distinct lipid environment, together with other membrane lipids, gangliosides possibly modulate Na⁺/K⁺-ATPase activity and aid in “starting up” and “turning off” this vital pump. Therefore, structural changes of neuronal membranes caused by altered ganglioside composition can be a contributing factor leading to aberrant Na⁺/K⁺-ATPase activity and ion imbalance priming neurons for pathological firing.

Is It Possible to Find an Antimicrobial Peptide That Passes the Membrane Bilayer with Minimal Force Resistance? An Attempt at a Predictive Approach by Molecular Dynamics Simulation

There is still no answer to the mechanism of penetration of AMP peptides through the membrane bilayer. Several mechanisms for such a process have been proposed. It is necessary to understand whether it is possible, using the molecular dynamics method, to determine the ability of peptides of different compositions and lengths to pass through a membrane bilayer. To explain the passage of a peptide through a membrane bilayer, a method for preparing a membrane phospholipid bilayer was proposed, and 656 steered molecular dynamics calculations were carried out for pulling 7 amyloidogenic peptides with antimicrobial potential, and monopeptides (homo-repeats consisting of 10 residues of the same amino acid: Poly (Ala), Poly (Leu), Poly (Met), Poly (Arg), and Poly (Glu)) with various sequences through the membrane. Among the 15 studied peptides, the peptides exhibiting the least force resistance when passing through the bilayer were found, and the maximum reaction occurred at the boundary of the membrane bilayer entry. We found that the best correlation between the maximum membrane reaction force and the calculated parameters corresponds to the instability index (the correlation coefficient is above 0.9). One of the interesting results of this study is that the 10 residue amyloidogenic peptides and their extended peptides, with nine added residue cell-penetrating peptides and four residue linkers, both with established antimicrobial activity, have the same bilayer resistance force. All calculated data are summarized and posted on the server.