The Structure/Function Relationship in Antimicrobial Peptides: What Can we Obtain From Structural Data?

Peptide Dendrimer-Based Antibacterial Agents: Synthesis and Applications

Pathogenic bacteria cause the deaths of millions of people every year. With the development of antibiotics, hundreds and thousands of people's lives have been saved. Nevertheless, bacteria can develop resistance to antibiotics, rendering them insensitive to antibiotics over time. Peptides containing specific amino acids can be used as antibacterial agents; however, they can be easily degraded by proteases in vivo. To address these issues, branched peptide dendrimers are now being considered as good antibacterial agents due to their high efficacy, resistance to protease degradation, and low cytotoxicity. The ease with which peptide dendrimers can be synthesized and modified makes them accessible for use in various biological and nonbiological fields. That is, peptide dendrimers hold a promising future as antibacterial agents with prolonged efficacy without bacterial resistance development. Their in vivo stability and multivalence allow them to effectively target multi-drug-resistant strains and prevent biofilm formation. Thus, it is interesting to have an overview of the development and applications of peptide dendrimers in antibacterial research, including the possibility of employing machine learning approaches for the design of AMPs and dendrimers. This review summarizes the synthesis and applications of peptide dendrimers as antibacterial agents. The challenges and perspectives of using peptide dendrimers as the antibacterial agents are also discussed.

Insights into the Adsorption Mechanisms of the Antimicrobial Peptide CIDEM-501 on Membrane Models

CIDEM-501 is a hybrid antimicrobial peptide rationally designed based on the structure of panusin and panulirin template peptides. The new peptide exhibits significant antibacterial activity against multidrug-resistant pathogens (MIC = 2-4 μM) while conserving no toxicity in human cell lines. We conducted molecular dynamics (MD) simulations using the CHARMM-36 force field to explore the CIDEM-501 adsorption mechanism with different membrane compositions. Several parameters that characterize these interactions were analyzed to elucidate individual residues' structural and thermodynamic contributions. The membrane models were constructed using CHARMM-GUI, mimicking the bacterial and eukaryotic phospholipid compositions. Molecular dynamics simulations were conducted over 500 ns, showing rapid and highly stable peptide adsorption to bacterial lipids components rather than the zwitterionic eucaryotic model membrane. A predominant peptide orientation was observed in all models dominated by an electric dipole. The peptide remained parallel to the membrane surface with the center loop oriented to the lipids. Our findings shed light on the antibacterial activity of CIDEM-501 on bacterial membranes and yield insights valuable for designing potent antimicrobial peptides targeting multi- and extreme drug-resistant bacteria.

Antimicrobial Peptide Synergies for Fighting Infectious Diseases

Antimicrobial peptides (AMPs) are essential elements of thehost defense system. Characterized by heterogenous structures and broad-spectrumaction, they are promising candidates for combating multidrug resistance. Thecombined use of AMPs with other antimicrobial agents provides a new arsenal ofdrugs with synergistic action, thereby overcoming the drawback of monotherapiesduring infections. AMPs kill microbes via pore formation, thus inhibitingintracellular functions. This mechanism of action by AMPs is an advantage overantibiotics as it hinders the development of drug resistance. The synergisticeffect of AMPs will allow the repurposing of conventional antimicrobials andenhance their clinical outcomes, reduce toxicity, and, most significantly,prevent the development of resistance. In this review, various synergies ofAMPs with antimicrobials and miscellaneous agents are discussed. The effect ofstructural diversity and chemical modification on AMP properties is firstaddressed and then different combinations that can lead to synergistic action,whether this combination is between AMPs and antimicrobials, or AMPs andmiscellaneous compounds, are attended. This review can serve as guidance whenredesigning and repurposing the use of AMPs in combination with other antimicrobialagents for enhanced clinical outcomes.

The biological role of charge distribution in linear antimicrobial peptides

INTRODUCTION

Antimicrobial peptides (AMP) have received particular attention due to their capacity to kill bacteria. Although much is known about them, peptides are currently being further researched. A large number of AMPs have been discovered, but only a few have been approved for topical use, due to their promiscuity and other challenges, which need to be overcome.

AREAS COVERED

AMPs are diverse in structure. Consequently, they have varied action mechanisms when targeting microorganisms or eukaryotic cells. Herein, the authors focus on linear peptides, particularly those that are alpha-helical structured, and examine how their charge distribution and hydrophobic amino acids could modulate their biological activity.

EXPERT OPINION

The world currently needs urgent solutions to the infective problems caused by resistant pathogens. In order to start the race for antimicrobial development from the charge distribution viewpoint, bioinformatic tools will be necessary. Currently, there is no software available that allows to discriminate charge distribution in AMPs and predicts the biological effects of this event. Furthermore, there is no software available that predicts the side-chain length of residues and its role in biological functions. More specialized software is necessary.

Screening for cysteine-stabilized scaffolds for developing proteolytic-resistant AMPs

Antimicrobial peptides (AMP) are present in all organisms and can present several activities and potential applications in human and animal health. Screening these molecules scaffolds represents a key point for discovering and developing novel biotechnological products, including antimicrobial, antiviral and anticancer drugs candidates and insecticidal molecules with potential applications in agriculture. Therefore, considering the amount of biological data currently deposited on public databases, computational approaches have been commonly used to predicted and identify novel cysteine-rich peptides scaffolds with known or unknown biological properties. Here, we describe a step-by-step in silico screening for cysteine-rich peptides employing molecular modeling (with a core focus on comparative modeling) and atomistic molecular dynamics simulations. Moreover, we also present the concept of additional tools aiming at the computer-aided screening of new Cs-AMPs based drug candidates. After the computational screening and peptide chemical synthesis, we also provide the reader with a step-by-step in vitro activity evaluation of these candidates, including antibacterial, antifungal, and antiviral assays.

Antimicrobial peptides (AMPs): A promising class of antimicrobial compounds

Antimicrobial peptides (AMPs) are compounds, which have inhibitory activity against microorganisms. In the last decades, AMPs have become powerful alternative agents that have met the need for novel anti-infectives to overcome increasing antibiotic resistance problems. Moreover, recent epidemics and pandemics are increasing the popularity of AMPs, due to the urgent necessity for effective antimicrobial agents in combating the new emergence of microbial diseases. AMPs inhibit a wide range of microorganisms through diverse and special mechanisms by targeting mainly cell membranes or specific intracellular components. In addition to extraction from natural sources, AMPs are produced in various hosts using recombinant methods. More recently, the synthetic analogues of AMPs, designed with some modifications, are predicted to overcome the limitations of stability, toxicity and activity associated with natural AMPs. AMPs have potential applications as antimicrobial agents in food, agriculture, environment, animal husbandry and pharmaceutical industries. In this review, we have provided an overview of the structure, classification and mechanism of action of AMPs, as well as discussed opportunities for their current and potential applications.

Thermodynamics-Based Molecular Modeling of α-Helices in Membranes and Micelles

The Folding of Membrane-Associated Peptides (FMAP) method was developed for modeling α-helix formation by linear peptides in micelles and lipid bilayers. FMAP 2.0 identifies locations of α-helices in the amino acid sequence, generates their three-dimensional models in planar bilayers or spherical micelles, and estimates their thermodynamic stabilities and tilt angles, depending on temperature and pH. The method was tested for 723 peptides (926 data points) experimentally studied in different environments and for 170 single-pass transmembrane (TM) proteins with available crystal structures. FMAP 2.0 detected more than 95% of experimentally observed α-helices with an average error in helix end determination of around 2, 3, 4, and 5 residues per helix for peptides in water, micelles, bilayers, and TM proteins, respectively. Helical and nonhelical residue states were predicted with an accuracy from 0.86 to 0.96, and the Matthews correlation coefficient was from 0.64 to 0.88 depending on the environment. Experimental micelle- and membrane-binding energies and tilt angles of peptides were reproduced with a root-mean-square deviation of around 2 kcal/mol and 7°, respectively. The TM and non-TM states of hydrophobic and pH-triggered α-helical peptides in various lipid bilayers were reproduced in more than 95% of cases. The FMAP 2.0 web server (https://membranome.org/fmap) is publicly available to explore the structural polymorphism of antimicrobial, cell-penetrating, fusion, and other membrane-binding peptides, which is important for understanding the mechanisms of their biological activities.

Feleucin-K3 Analogue with an α-(4-Pentenyl)-Ala Substitution at the Key Site Has More Potent Antimicrobial and Antibiofilm Activities in Vitro and in Vivo

The development of antimicrobial compounds is now regarded as an urgent problem. Antimicrobial peptides (AMPs) have great potential to become novel antimicrobial drugs. Feleucin-K3 is an α-helical cationic AMP isolated from the skin secretion of the Asian bombinid toad species Bombina orientalis and has antimicrobial activity. In our previous studies, amino acid scanning of Feleucin-K3 was performed to determine the key site affecting its activity. In this study, we investigated and synthesized a series of analogues that have either a natural or an unnatural hydrophobic amino acid substitution at the fourth amino acid residue of Feleucin-K3. Among these analogues, Feleucin-K59 (K59), which has an α-(4-pentenyl)-Ala substitution, was shown to have increased antimicrobial activity against both standard and drug-resistant strains of clinical common bacteria, improved stability, no hemolytic activity at antimicrobial concentrations, and no resistance. In addition, K59 has potent antibiofilm activity in vitro. More importantly, K59 showed better antimicrobial and antibiofilm activities against drug-resistant bacteria in in vivo experiments in mice than traditional antibiotics. In this preliminary study of the mechanism of action, we found that K59 could rapidly kill bacteria by a dual-action mechanism of disrupting the cell membrane and binding to intracellular DNA, thus making it difficult for bacteria to develop resistance.

Conformational Changes of Anoplin, W-MreB1-9, and (KFF)3K Peptides near the Membranes

Many peptides interact with biological membranes, but elucidating these interactions is challenging because cellular membranes are complex and peptides are structurally flexible. To contribute to understanding how the membrane-active peptides behave near the membranes, we investigated peptide structural changes in different lipid surroundings. We focused on two antimicrobial peptides, anoplin and W-MreB1-9, and one cell-penetrating peptide, (KFF)3K. Firstly, by using circular dichroism spectroscopy, we determined the secondary structures of these peptides when interacting with micelles, liposomes, E. coli lipopolysaccharides, and live E. coli bacteria. The peptides were disordered in the buffer, but anoplin and W-MreB1-9 displayed lipid-induced helicity. Yet, structural changes of the peptide depended on the composition and concentration of the membranes. Secondly, we quantified the destructive activity of peptides against liposomes by monitoring the release of a fluorescent dye (calcein) from the liposomes treated with peptides. We observed that only for anoplin and W-MreB1-9 calcein leakage from liposomes depended on the peptide concentration. Thirdly, bacterial growth inhibition assays showed that peptide conformational changes, evoked by the lipid environments, do not directly correlate with the antimicrobial activity of the peptides. However, understanding the relation between peptide structural properties, mechanisms of membrane disruption, and their biological activities can guide the design of membrane-active peptides.

Design and characterization of new antimicrobial peptides derived from aurein 1.2 with enhanced antibacterial activity

Antimicrobial peptides (AMPs) are promising alternative agents for treating multidrug-resistant bacterial infections. Aurein 1.2 is a natural 13-amino acid AMP with antibacterial activity against Gram-positive bacteria. In this study, we designed three novel AMPs: aurein M1 (A10W), aurein M2 (D4K, E11K), and aurein M3 (A10W, D4K, E11K) to analyze the effect of Trp substitution and enhancement of positive charge on the activity of aurein 1.2. The AMP probability, physicochemical properties, secondary and tertiary structures, and amphipathic structure were predicted by various bioinformatics tools. After the synthesis of the peptides, their antibacterial activity, hemolysis, cytotoxicity, and structural analysis were assayed. Compared to the selectivity of aurein 1.2, the selectivity of aurein M2 and M3 with a net positive charge of +5 was improved 11.30- and 8.00-fold against Gram-positive and -negative bacteria, respectively. The hemolytic activity of aurein M2 was lower than that of aurein 1.2 and M3, while the higher percentage of human fibroblast cells were alive in the presence of aurein M3. Also, the MICs of aurein M3 toward Staphylococcus aureus and Escherichia coli at the physiologic salt were ≤16, which is recommended as a promising candidate for clinical investigation. Circular dichroism analysis indicated an alpha-helical structure in the peptide analogs that is similar to aurein 1.2 in the presence of 10 mM SDS. Therefore, increasing positive charge can be used successfully as an approach for improving the potency and selectivity of AMPs. Moreover, the beneficial effect of Trp substitution depends on its position and the sequence of peptides.

Variational Autoencoder for Generation of Antimicrobial Peptides

Over millennia, natural evolution has allowed for the emergence of countless biomolecules with highly specific roles within natural systems. As seen with peptides and proteins, often evolution produces molecules with a similar function but with variable amino acid composition and structure but diverging from a common ancestor, which can limit sequence diversity. Using antimicrobial peptides as a model biomolecule, we train a generative deep learning algorithm on a database of known antimicrobial peptides to generate novel peptide sequences with antimicrobial activity. Using a variational autoencoder, we are able to generate a latent space plot that can be surveyed for peptides with known properties and interpolated across a predictive vector between two defined points to identify novel peptides that show dose-responsive antimicrobial activity. These proof-of-concept studies demonstrate the potential for artificial intelligence-directed methods to generate new antimicrobial peptides and motivate their potential application toward peptide and protein design without the need for exhaustive screening of sequence libraries.

Computer-Aided Design of Antimicrobial Peptides: Are We Generating Effective Drug Candidates?

Antimicrobial peptides (AMPs), especially antibacterial peptides, have been widely investigated as potential alternatives to antibiotic-based therapies. Indeed, naturally occurring and synthetic AMPs have shown promising results against a series of clinically relevant bacteria. Even so, this class of antimicrobials has continuously failed clinical trials at some point, highlighting the importance of AMP optimization. In this context, the computer-aided design of AMPs has put together crucial information on chemical parameters and bioactivities in AMP sequences, thus providing modes of prediction to evaluate the antibacterial potential of a candidate sequence before synthesis. Quantitative structure-activity relationship (QSAR) computational models, for instance, have greatly contributed to AMP sequence optimization aimed at improved biological activities. In addition to machine-learning methods, the de novo design, linguistic model, pattern insertion methods, and genetic algorithms, have shown the potential to boost the automated design of AMPs. However, how successful have these approaches been in generating effective antibacterial drug candidates? Bearing this in mind, this review will focus on the main computational strategies that have generated AMPs with promising activities against pathogenic bacteria, as well as anti-infective potential in different animal models, including sepsis and cutaneous infections. Moreover, we will point out recent studies on the computer-aided design of antibiofilm peptides. As expected from automated design strategies, diverse candidate sequences with different structural arrangements have been generated and deposited in databases. We will, therefore, also discuss the structural diversity that has been engendered.

Snake Venom Cathelicidins as Natural Antimicrobial Peptides

Bioactive small molecules isolated from animals, plants, fungi and bacteria, including natural antimicrobial peptides, have shown great therapeutic potential worldwide. Among these peptides, snake venom cathelicidins are being widely exploited, because the variation in the composition of the venom reflects a range of biological activities that may be of biotechnological interest. Cathelicidins are short, cationic, and amphipathic molecules. They play an important role in host defense against microbial infections. We are currently facing a strong limitation on pharmacological interventions for infection control, which has become increasingly complex due to the lack of effective therapeutic options. In this review, we will focus on natural snake venom cathelicidins as promising candidates for the development of new antibacterial agents to fight antibiotic-resistant bacteria. We will highlight their antibacterial and antibiofilm activities, mechanism of action, and modulation of the innate immune response.

Encodings and models for antimicrobial peptide classification for multi-resistant pathogens

Antimicrobial peptides (AMPs) are part of the inherent immune system. In fact, they occur in almost all organisms including, e.g., plants, animals, and humans. Remarkably, they show effectivity also against multi-resistant pathogens with a high selectivity. This is especially crucial in times, where society is faced with the major threat of an ever-increasing amount of antibiotic resistant microbes. In addition, AMPs can also exhibit antitumor and antiviral effects, thus a variety of scientific studies dealt with the prediction of active peptides in recent years. Due to their potential, even the pharmaceutical industry is keen on discovering and developing novel AMPs. However, AMPs are difficult to verify in vitro, hence researchers conduct sequence similarity experiments against known, active peptides. Unfortunately, this approach is very time-consuming and limits potential candidates to sequences with a high similarity to known AMPs. Machine learning methods offer the opportunity to explore the huge space of sequence variations in a timely manner. These algorithms have, in principal, paved the way for an automated discovery of AMPs. However, machine learning models require a numerical input, thus an informative encoding is very important. Unfortunately, developing an appropriate encoding is a major challenge, which has not been entirely solved so far. For this reason, the development of novel amino acid encodings is established as a stand-alone research branch. The present review introduces state-of-the-art encodings of amino acids as well as their properties in sequence and structure based aggregation. Moreover, albeit a well-chosen encoding is essential, performant classifiers are required, which is reflected by a tendency towards specifically designed models in the literature. Furthermore, we introduce these models with a particular focus on encodings derived from support vector machines and deep learning approaches. Albeit a strong focus has been set on AMP predictions, not all of the mentioned encodings have been elaborated as part of antimicrobial research studies, but rather as general protein or peptide representations.

Membrane Active Peptides and Their Biophysical Characterization

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