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

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.

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.

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.

Connecting the dots: from nanodomains to physiological functions of REMORINs

REMORINs (REMs) are a plant-specific protein family, proposed regulators of membrane-associated molecular assemblies and well-established markers of plasma membrane nanodomains. REMs play a diverse set of functions in plant interactions with pathogens and symbionts, responses to abiotic stresses, hormone signaling and cell-to-cell communication. In this review, we highlight the established and more putative roles of REMs throughout the literature. We discuss the physiological functions of REMs, the mechanisms underlying their nanodomain-organization and their putative role as regulators of nanodomain-associated molecular assemblies. Furthermore, we discuss how REM phosphorylation may regulate their functional versatility. Overall, through data-mining and comparative analysis of the literature, we suggest how to further study the molecular mechanisms underpinning the functions of REMs.

Molecular Dynamics for Antimicrobial Peptide Discovery

Although antimicrobial resistance is an increasingly significant public health concern, there have only been two new classes of antibiotics approved for human use since the 1960s. Understanding the mechanisms of action of antibiotics is critical for novel antibiotic discovery, but novel approaches are needed that do not exclusively rely on experiments. Molecular dynamics simulation is a computational tool that uses simple models of the atoms in a system to discover nanoscale insights into the dynamic relationship between mechanism and biological function. Such insights can lay the framework for elucidating the mechanism of action and optimizing antibiotic templates. Antimicrobial peptides represent a promising solution to escalating antimicrobial resistance, given their lesser tendency to induce resistance than that of small-molecule antibiotics. Simulations of these agents have already revealed how they interact with bacterial membranes and the underlying physiochemical features directing their structure and function. In this minireview, we discuss how traditional molecular dynamics simulation works and its role and potential for the development of new antibiotic candidates with an emphasis on antimicrobial peptides.

Synthetic Biology and Computer-Based Frameworks for Antimicrobial Peptide Discovery

Antibiotic resistance is one of the greatest challenges of our time. This global health problem originated from a paucity of truly effective antibiotic classes and an increased incidence of multi-drug-resistant bacterial isolates in hospitals worldwide. Indeed, it has been recently estimated that 10 million people will die annually from drug-resistant infections by the year 2050. Therefore, the need to develop out-of-the-box strategies to combat antibiotic resistance is urgent. The biological world has provided natural templates, called antimicrobial peptides (AMPs), which exhibit multiple intrinsic medical properties including the targeting of bacteria. AMPs can be used as scaffolds and, via engineering, can be reconfigured for optimized potency and targetability toward drug-resistant pathogens. Here, we review the recent development of tools for the discovery, design, and production of AMPs and propose that the future of peptide drug discovery will involve the convergence of computational and synthetic biology principles.

Estimation of pore dimensions in lipid membranes induced by peptides and other biomolecules: A review

The cytoplasmic membrane is one of the most frequent cell targets of antimicrobial peptides (AMPs) and other biomolecules. Understanding the mechanism of action of AMPs at the molecular level is of utmost importance for designing of new membrane-specific molecules. In particular, the formation of pores, the structure and size of these pores are of great interest and require nanoscale resolution approaches, therefore, biophysical strategies are essential to achieve an understanding of these processes at this scale. In the case of membrane active peptides, pore formation or general membrane disruption is usually the last step before cell death, and so, pore size is generally directly associated to pore structure and stability and loss of cellular homeostasis, implicated in overall peptide activity. Up to date, there has not been a critical review discussing the methods that can be used specifically for estimating the pore dimensions induced by membrane active peptides. In this review we discuss the scope, relevance and popularity of the different biophysical techniques such as liposome leakage experiments, advanced microscopy, neutron or X-ray scattering, electrophysiological techniques and molecular dynamics studies, all of them useful for determining pore structure and dimension.

A Global Review on Short Peptides: Frontiers and Perspectives

Peptides are fragments of proteins that carry out biological functions. They act as signaling entities via all domains of life and interfere with protein-protein interactions, which are indispensable in bio-processes. Short peptides include fundamental molecular information for a prelude to the symphony of life. They have aroused considerable interest due to their unique features and great promise in innovative bio-therapies. This work focusing on the current state-of-the-art short peptide-based therapeutical developments is the first global review written by researchers from all continents, as a celebration of 100 years of peptide therapeutics since the commencement of insulin therapy in the 1920s. Peptide "drugs" initially played only the role of hormone analogs to balance disorders. Nowadays, they achieve numerous biomedical tasks, can cross membranes, or reach intracellular targets. The role of peptides in bio-processes can hardly be mimicked by other chemical substances. The article is divided into independent sections, which are related to either the progress in short peptide-based theranostics or the problems posing challenge to bio-medicine. In particular, the SWOT analysis of short peptides, their relevance in therapies of diverse diseases, improvements in (bio)synthesis platforms, advanced nano-supramolecular technologies, aptamers, altered peptide ligands and in silico methodologies to overcome peptide limitations, modern smart bio-functional materials, vaccines, and drug/gene-targeted delivery systems are discussed.

Binding and crossing: Methods for the characterization of membrane-active peptides interactions with membranes at the molecular level

Antimicrobial and cell-penetrating peptides have been the object of extensive studies for more than 60 years. Initially these two families were studied separately, and more recently parallels have been drawn. These studies have given rise to numerous methodological developments both in terms of observation techniques and membrane models. This review presents some of the most recent original and innovative developments in this field, namely droplet interface bilayers (DIBs), new fluorescence approaches, force measurements, and photolabelling.

High-speed atomic force microscopy highlights new molecular mechanism of daptomycin action

The increase in speed of the high-speed atomic force microscopy (HS-AFM) compared to that of the conventional AFM made possible the first-ever visualisation at the molecular-level of the activity of an antimicrobial peptide on a membrane. We investigated the medically prescribed but poorly understood lipopeptide Daptomycin under infection-like conditions (37 °C, bacterial lipid composition and antibiotic concentrations). We confirmed so far hypothetical models: Dap oligomerization and the existence of half pores. Moreover, we detected unknown molecular mechanisms: new mechanisms to form toroidal pores or to resist Dap action, and to unprecedently quantify the energy profile of interacting oligomers. Finally, the biological and medical relevance of the findings was ensured by a multi-scale multi-nativeness-from the molecule to the cell-correlation of molecular-level information from living bacteria (Bacillus subtilis strains) to liquid-suspended vesicles and supported-membranes using electron and optical microscopies and the lipid tension probe FliptR, where we found that the cells with a healthier state of their cell wall show smaller membrane deformations.

Rapid, accurate, precise and reproducible ligand-protein binding free energy prediction

A central quantity of interest in molecular biology and medicine is the free energy of binding of a molecule to a target biomacromolecule. Until recently, the accurate prediction of binding affinity had been widely regarded as out of reach of theoretical methods owing to the lack of reproducibility of the available methods, not to mention their complexity, computational cost and time-consuming procedures. The lack of reproducibility stems primarily from the chaotic nature of classical molecular dynamics (MD) and the associated extreme sensitivity of trajectories to their initial conditions. Here, we review computational approaches for both relative and absolute binding free energy calculations, and illustrate their application to a diverse set of ligands bound to a range of proteins with immediate relevance in a number of medical domains. We focus on ensemble-based methods which are essential in order to compute statistically robust results, including two we have recently developed, namely thermodynamic integration with enhanced sampling and enhanced sampling of MD with an approximation of continuum solvent. Together, these form a set of rapid, accurate, precise and reproducible free energy methods. They can be used in real-world problems such as hit-to-lead and lead optimization stages in drug discovery, and in personalized medicine. These applications show that individual binding affinities equipped with uncertainty quantification may be computed in a few hours on a massive scale given access to suitable high-end computing resources and workflow automation. A high level of accuracy can be achieved using these approaches.

Approaches for the discovery of new cell-penetrating peptides

Introduction: The capability of cell-penetrating peptides (CPP), also known as protein transduction domains (PTD), to enter into cells possibly with an attached cargo, makes their application as delivery vectors or as direct therapeutics compelling. They are generally biocompatible, nontoxic, and easy to synthesize and modify. Three decades after the discovery of the first CPPs, ~2,000 CPP sequences have been identified, and many more predicted. Nevertheless, the field has a strong commitment to authenticate new, more efficient, and specific CPPs.Areas covered: Although a scattering of CPPs have been found by chance, various systematic approaches have been developed and refined over the years to directly aid the identification and depiction of new peptide-based delivery vectors or therapeutics. Here, the authors give an overview of CPPs, and review various approaches of discovering new ones. An emphasis is placed on in silico methods, as these have advanced rapidly in recent years.Expert opinion: Although there are many known CPPs, there is a need to find more efficient and specific CPPs. Several approaches are used to identify such sequences. The success of these approaches depends on the advancement of others and the successful prediction of CPP sequences relies on experimental data.

Application of a Distance-Dependent Sigmoidal Dielectric Constant to the REMC/SAAP3D Simulations of Chignolin, Trp-Cage, and the G10q Mutant

The replica-exchange Monte Carlo method based on the single amino acid potential (SAAP) force field, i.e., REMC/SAAP3D, was recently developed by our group for the molecular simulation of short peptides. In this study, the method has been improved by applying a distance-dependent dielectric (DDD) constant and extended to the peptides containing D-amino acid (AA) residues. For chignolin (10 AAs), a sigmoidal DDD model reasonably allocated the native-like β-hairpin structure with all-atom root mean square deviation (RMSD) = 2.0 Å as a global energy minimum. The optimal DDD condition was subsequently applied for Trp-cage (20 AAs) and its G10q mutant. The native-like α-rich folded structures with main-chain RMSD = 3.7 and 3.8 Å were obtained as global energy minima for Trp-cage and G10q, respectively. The results suggested that the REMC/SAAP3D method with the sigmoidal DDD model is useful for structural prediction for the short peptides comprised of up to 20 AAs. In addition, the relative contributions of SAAP to the total energy (%SAAP) were evaluated by energetic component analysis. The ratios of %SAAP were about 40 and 20% for chignolin and Trp-cage (or G10q), respectively. It was proposed that SAAP is more important for the secondary structure formation than for the assembly to a higher-order folded structure, in which the attractive van der Waals interaction may play a more important role.

Integral Representation of Electrostatic Interactions inside a Lipid Membrane

Interactions between charges and dipoles inside a lipid membrane are partially screened. The screening arises both from the polarization of water and from the structure of the electric double layer formed by the salt ions outside the membrane. Assuming that the membrane can be represented as a dielectric slab of low dielectric constant sandwiched by an aqueous solution containing mobile ions, a theoretical model is developed to quantify the strength of electrostatic interactions inside a lipid membrane that is valid in the linear limit of Poisson-Boltzmann theory. We determine the electrostatic potential produced by a single point charge that resides inside the slab and from that calculate charge-charge and dipole-dipole interactions as a function of separation. Our approach yields integral representations for these interactions that can easily be evaluated numerically for any choice of parameters and be further simplified in limiting cases.

Interplay of hydrophobic and hydrophilic interactions in sequence-dependent cell penetration of spontaneous membrane-translocating peptides revealed by bias-exchange metadynamics simulations

Spontaneous Membrane Translocating Peptides (SMTPs) can translocate silently across the bilayer and, thus, have the best potential to improve the delivery of therapeutic molecules to cells without toxicity. However, how their translocation mechanisms are affected by a specific peptide sequence remains poorly understood. Here, bias-exchange metadynamics simulations were employed to investigate the translocation mechanisms of five SMTPs with the same composition of amino acids (LLRLR, LRLLR, LLLRR, RLLLR, and LRLRL). Simulation results yield sequence-dependent free energy barrier using the FESs along the z-directional distance. An in-depth analysis of sequence-dependent interactions in different regions of the bilayers indicates that the free-energy barrier height of a specific sequence is resulted from the accessibility balance of isolated or clustered hydrophobic residues (L) and hydrophilic residues (R) that leads to different levels of resistance for moving of a peptide into the hydrophobic center of the membrane. At the maximal of the free-energy barrier, all peptides have a conformation parallel to the membrane surface with the barrier height determined by their affinity to the hydrophobic region. The appropriate bilayer perturbation and GDM⁺ pairing are beneficial for peptide translocation. These results provide an improved microscopic understanding of how peptide sequence influences the translocation efficiency and mechanism.

Mesophilic Pyrophosphatase Function at High Temperature: A Molecular Dynamics Simulation Study

The mesophilic inorganic pyrophosphatase from Escherichia coli (EcPPase) retains function at 353 K, the physiological temperature of hyperthermophilic Thermococcus thioreducens, whereas the homolog protein (TtPPase) from this hyperthermophilic organism cannot function at room temperature. To explain this asymmetric behavior, we examined structural and dynamical properties of the two proteins using molecular dynamics simulations. The global flexibility of TtPPase is significantly higher than its mesophilic homolog at all tested temperature/pressure conditions. However, at 353 K, EcPPase reduces its solvent-exposed surface area and increases subunit compaction while maintaining flexibility in its catalytic pocket. In contrast, TtPPase lacks this adaptability and has increased rigidity and reduced protein/water interactions in its catalytic pocket at room temperature, providing a plausible explanation for its inactivity near room temperature.

Understanding and modelling the interactions of peptides with membranes: from partitioning to self-assembly

Atomic detail simulations are starting to reveal how flexible polypeptides interact with fluid lipid bilayers. These insights are transforming our understanding of one of the fundamental processes in biology: membrane protein folding and assembly. Advanced molecular dynamics (MD) simulation techniques enable accurate prediction of protein structure, folding pathways and assembly in microsecond-timescales. Such simulations show how membrane-active peptides self-assemble in cell membranes, revealing their binding, folding, insertion, and aggregation, while at the same time providing atomic resolution details of peptide-lipid interactions. Essential to the impact of simulations are experimental approaches that enable calibration and validation of the computational models and techniques. In this review, we summarize the current development of applying unbiased atomic detail MD simulations and the relation to experimental techniques, to study peptide folding and provide our perspective of the field.