QSAR analysis of antimicrobial and haemolytic effects of cyclic cationic antimicrobial peptides derived from protegrin-1

QSAR Reveals Decreased Lipophilicity of Polar Residues Determines the Selectivity of Antimicrobial Peptide Activity

Antimicrobial resistance has increased rapidly, causing daunting morbidity and mortality rates worldwide. Antimicrobial peptides (AMPs) have emerged as promising alternatives to traditional antibiotics due to their broad range of targets and low tendency to elicit resistance. However, potent antimicrobial activity is often accompanied by excessive cytotoxicity toward host cells, leading to a halt in AMP therapeutic development. Here, we present multivariate analyses that correlate 28 peptide properties to the activity and toxicity of 46 diverse African-derived AMPs and identify the negative lipophilicity of polar residues as an essential physiochemical property for selective antimicrobial activity. Twenty-seven active AMPs are identified, of which the majority are of scorpion or frog origin. Of these, thirteen are novel with no previously reported activities. Principal component analysis and quantitative structure-activity relationships (QSAR) reveal that overall hydrophobicity, lipophilicity, and residue side chain surface area affect the antimicrobial and cytotoxic activity of an AMP. This has been well documented previously, but the present QSAR analysis additionally reveals that a decrease in the lipophilicity, contributed by those amino acids classified as polar, confers selectivity for a peptide to pathogen over mammalian cells. Furthermore, an increase in overall peptide charge aids selectivity toward Gram-negative bacteria and fungi, while selectivity toward Gram-positive bacteria is obtained through an increased number of small lipophilic residues. Finally, a conservative increase in peptide size in terms of sequence length and molecular weight also contributes to improved activity without affecting toxicity. Our findings suggest a novel approach for the rational design or modification of existing AMPs to increase pathogen selectivity and enhance therapeutic potential.

Rational design of stapled antimicrobial peptides

The global increase in antimicrobial drug resistance has dramatically reduced the effectiveness of traditional antibiotics. Structurally diverse antibiotics are urgently needed to combat multiple-resistant bacterial infections. As part of innate immunity, antimicrobial peptides have been recognized as the most promising candidates because they comprise diverse sequences and mechanisms of action and have a relatively low induction rate of resistance. However, because of their low chemical stability, susceptibility to proteases, and high hemolytic effect, their usage is subject to many restrictions. Chemical modifications such as D-amino acid substitution, cyclization, and unnatural amino acid modification have been used to improve the stability of antimicrobial peptides for decades. Among them, a side-chain covalent bridge modification, the so-called stapled peptide, has attracted much attention. The stapled side-chain bridge stabilizes the secondary structure, induces protease resistance, and increases cell penetration and biological activity. Recent progress in computer-aided drug design and artificial intelligence methods has also been used in the design of stapled antimicrobial peptides and has led to the successful discovery of many prospective peptides. This article reviews the possible structure-activity relationships of stapled antimicrobial peptides, the physicochemical properties that influence their activity (such as net charge, hydrophobicity, helicity, and dipole moment), and computer-aided methods of stapled peptide design. Antimicrobial peptides under clinical trial: Pexiganan (NCT01594762, 2012-05-07). Omiganan (NCT02576847, 2015-10-13).

Machine Learning in Antibacterial Drug Design

Advances in computer hardware and the availability of high-performance supercomputing platforms and parallel computing, along with artificial intelligence methods are successfully complementing traditional approaches in medicinal chemistry. In particular, machine learning is gaining importance with the growth of the available data collections. One of the critical areas where this methodology can be successfully applied is in the development of new antibacterial agents. The latter is essential because of the high attrition rates in new drug discovery, both in industry and in academic research programs. Scientific involvement in this area is even more urgent as antibacterial drug resistance becomes a public health concern worldwide and pushes us increasingly into the post-antibiotic era. In this review, we focus on the latest machine learning approaches used in the discovery of new antibacterial agents and targets, covering both small molecules and antibacterial peptides. For the benefit of the reader, we summarize all applied machine learning approaches and available databases useful for the design of new antibacterial agents and address the current shortcomings.

Non-Lytic Antibacterial Peptides That Translocate Through Bacterial Membranes to Act on Intracellular Targets

The advent of multidrug resistance among pathogenic bacteria has attracted great attention worldwide. As a response to this growing challenge, diverse studies have focused on the development of novel anti-infective therapies, including antimicrobial peptides (AMPs). The biological properties of this class of antimicrobials have been thoroughly investigated, and membranolytic activities are the most reported mechanisms by which AMPs kill bacteria. Nevertheless, an increasing number of works have pointed to a different direction, in which AMPs are seen to be capable of displaying non-lytic modes of action by internalizing bacterial cells. In this context, this review focused on the description of the in vitro and in vivo antibacterial and antibiofilm activities of non-lytic AMPs, including indolicidin, buforin II PR-39, bactenecins, apidaecin, and drosocin, also shedding light on how AMPs interact with and further translocate through bacterial membranes to act on intracellular targets, including DNA, RNA, cell wall and protein synthesis.

A Web Server and Mobile App for Computing Hemolytic Potency of Peptides

Numerous therapeutic peptides do not enter the clinical trials just because of their high hemolytic activity. Recently, we developed a database, Hemolytik, for maintaining experimentally validated hemolytic and non-hemolytic peptides. The present study describes a web server and mobile app developed for predicting, and screening of peptides having hemolytic potency. Firstly, we generated a dataset HemoPI-1 that contains 552 hemolytic peptides extracted from Hemolytik database and 552 random non-hemolytic peptides (from Swiss-Prot). The sequence analysis of these peptides revealed that certain residues (e.g., L, K, F, W) and motifs (e.g., "FKK", "LKL", "KKLL", "KWK", "VLK", "CYCR", "CRR", "RFC", "RRR", "LKKL") are more abundant in hemolytic peptides. Therefore, we developed models for discriminating hemolytic and non-hemolytic peptides using various machine learning techniques and achieved more than 95% accuracy. We also developed models for discriminating peptides having high and low hemolytic potential on different datasets called HemoPI-2 and HemoPI-3. In order to serve the scientific community, we developed a web server, mobile app and JAVA-based standalone software (http://crdd.osdd.net/raghava/hemopi/).

Identification of Peptide Inhibitors of Enveloped Viruses Using Support Vector Machine

The peptides derived from envelope proteins have been shown to inhibit the protein-protein interactions in the virus membrane fusion process and thus have a great potential to be developed into effective antiviral therapies. There are three types of envelope proteins each exhibiting distinct structure folds. Although the exact fusion mechanism remains elusive, it was suggested that the three classes of viral fusion proteins share a similar mechanism of membrane fusion. The common mechanism of action makes it possible to correlate the properties of self-derived peptide inhibitors with their activities. Here we developed a support vector machine model using sequence-based statistical scores of self-derived peptide inhibitors as input features to correlate with their activities. The model displayed 92% prediction accuracy with the Matthew's correlation coefficient of 0.84, obviously superior to those using physicochemical properties and amino acid decomposition as input. The predictive support vector machine model for self- derived peptides of envelope proteins would be useful in development of antiviral peptide inhibitors targeting the virus fusion process.

Emerging concepts promising new horizons for marine biodiscovery and synthetic biology

The vast oceans of the world, which comprise a huge variety of unique ecosystems, are emerging as a rich and relatively untapped source of novel bioactive compounds with invaluable biotechnological and pharmaceutical potential. Evidence accumulated over the last decade has revealed that the diversity of marine microorganisms is enormous with many thousands of bacterial species detected that were previously unknown. Associated with this diversity is the production of diverse repertoires of bioactive compounds ranging from peptides and enzymes to more complex secondary metabolites that have significant bioactivity and thus the potential to be exploited for innovative biotechnology. Here we review the discovery and functional potential of marine bioactive peptides such as lantibiotics, nanoantibiotics and peptidomimetics, which have received particular attention in recent years in light of their broad spectrum of bioactivity. The significance of marine peptides in cell-to-cell communication and how this may be exploited in the discovery of novel bioactivity is also explored. Finally, with the recent advances in bioinformatics and synthetic biology, it is becoming clear that the integration of these disciplines with genetic and biochemical characterization of the novel marine peptides, offers the most potential in the development of the next generation of societal solutions.

Mapping activity elements of protegrin antimicrobial peptides by HomoSAR

HomoSAR has been able to shed light on the relationship between sequences of protegrin peptides and their activity on six specific micro-organisms.

Inhibition of agronomically relevant fungal phytopathogens by tyrocidines, cyclic antimicrobial peptides isolated from Bacillus aneurinolyticus

The tyrocidines, a complex of analogous cyclic decapeptides produced by Bacillus aneurinolyticus, exhibited noteworthy activity against a range of phytopathogenic fungi, including Fusarium verticillioides, Fusarium solani and Botrytis cinerea. The activity of the tyrocidine peptide complex (Trc mixture) and purified tyrocidines exhibited minimum inhibition concentrations below 13 µg ml−1 (~10 µM) and was significantly more potent than that of the commercial imidazole fungicide, bifonazole. Although the tyrocidines’ activity was negatively influenced by the presence of Ca2+, it remained unaffected by the presence of Mg2+, Na+ and K+. Microscopic analysis revealed significant impact on the morphology of F. solani and Bot. cinerea including retarded germination and hyperbranching of hyphae. Studies with membrane-impermeable dyes, SYTOX green and propidium iodide suggested that the main mode of action of tyrocidines involves the disruption of fungal membrane integrity. Because of the tyrocidines’ broad spectrum and potent antifungal activity, possible multiple targets reducing the risk of overt resistance and general salt tolerance, they are promising candidates that warrant further investigation as bio-fungicides.

Prediction of linear cationic antimicrobial peptides based on characteristics responsible for their interaction with the membranes

Most available antimicrobial peptides (AMP) prediction methods use common approach for different classes of AMP. Contrary to available approaches, we suggest that a strategy of prediction should be based on the fact that there are several kinds of AMP that vary in mechanisms of action, structure, mode of interaction with membrane, etc. According to our suggestion for each kind of AMP, a particular approach has to be developed in order to get high efficacy. Consequently, in this paper, a particular but the biggest class of AMP, linear cationic antimicrobial peptides (LCAP), has been considered and a newly developed simple method of LCAP prediction described. The aim of this study is the development of a simple method of discrimination of AMP from non-AMP, the efficiency of which will be determined by efficiencies of selected descriptors only and comparison the results of the discrimination procedure with the results obtained by more complicated discriminative methods. As descriptors the physicochemical characteristics responsible for capability of the peptide to interact with an anionic membrane were considered. The following characteristics such as hydrophobicity, amphiphaticity, location of the peptide in relation to membrane, charge density, propensities to disordered structure and aggregation were studied. On the basis of these characteristics, a new simple algorithm of prediction is developed and evaluation of efficacies of the characteristics as descriptors performed. The results show that three descriptors, hydrophobic moment, charge density and location of the peptide along the membranes, can be used as discriminators of LCAPs. For the training set, our method gives the same level of accuracy as more complicated machine learning approaches offered as CAMP database service tools. For the test set accuracy obtained by our method gives even higher value than the one obtained by CAMP prediction tools. The AMP prediction tool based on the considered method is available at http://www.biomedicine.org.ge/dbaasp/.

Synergistic activity of the tyrocidines, antimicrobial cyclodecapeptides from Bacillus aneurinolyticus, with amphotericin B and caspofungin against Candida albicans biofilms

Tyrocidines are cationic cyclodecapeptides from Bacillus aneurinolyticus that are characterized by potent antibacterial and antimalarial activities. In this study, we show that various tyrocidines have significant activity against planktonic Candida albicans in the low-micromolar range. These tyrocidines also prevented C. albicans biofilm formation in vitro. Studies with the membrane-impermeable dye propidium iodide showed that the tyrocidines disrupt the membrane integrity of mature C. albicans biofilm cells. This membrane activity correlated with the permeabilization and rapid lysis of model fungal membranes containing phosphatidylcholine and ergosterol (70:30 ratio) induced by the tyrocidines. The tyrocidines exhibited pronounced synergistic biofilm-eradicating activity in combination with two key antifungal drugs, amphotericin B and caspofungin. Using a Caenorhabditis elegans infection model, we found that tyrocidine A potentiated the activity of caspofungin. Therefore, tyrocidines are promising candidates for further research as antifungal drugs and as agents for combinatorial treatment.

Cyclotide structure-activity relationships: qualitative and quantitative approaches linking cytotoxic and anthelmintic activity to the clustering of physicochemical forces

Cyclotides are a family of plant-derived proteins that are characterized by a cyclic backbone and a knotted disulfide topology. Their cyclic cystine knot (CCK) motif makes them exceptionally resistant to thermal, chemical, and enzymatic degradation. Cyclotides exert much of their biological activity via interactions with cell membranes. In this work, we qualitatively and quantitatively analyze the cytotoxic and anthelmintic membrane activities of cyclotides. The qualitative and quantitative models describe the potency of cyclotides using four simple physicochemical terms relevant to membrane contact. Specifically, surface areas of the cyclotides representing lipophilic and hydrogen bond donating properties were quantified and their distribution across the molecular surface was determined. The resulting quantitative structure-activity relation (QSAR) models suggest that the activity of the cyclotides is proportional to their lipophilic and positively charged surface areas, provided that the distribution of these surfaces is asymmetric. In addition, we qualitatively analyzed the physicochemical differences between the various cyclotide subfamilies and their effects on the cyclotides' orientation on the membrane and membrane activity.

Novel method to identify the optimal antimicrobial peptide in a combination matrix, using anoplin as an example

Microbial resistance is an increasing health concern and a true danger to human well-being. A worldwide search for new compounds is ongoing, and antimicrobial peptides are promising lead candidates for tomorrow's antibiotics. The decapeptide anoplin (GLLKRIKTLL-NH2) is an especially interesting candidate because of its small size as well as its antimicrobial and nonhemolytic properties. Optimization of the properties of an antimicrobial peptide such as anoplin requires multidimensional searching in a complex chemical space. Typically, such optimization is performed by labor-intensive and costly trial-and-error methods. In this study, we show the benefit of fractional factorial design for identification of the optimal antimicrobial peptide in a combination matrix. We synthesized and analyzed a training set of 12 anoplin analogs, representative of 64 analogs in total. Using MIC, hemolysis, and high-performance liquid chromatography retention time data, we constructed analysis-of-variance models that describe the relationship between these properties and the structural characteristics of the analogs. We show that the mathematical models derived from the training set data can be used to predict the properties of other analogs in the chemical space. Hence, this method provides an efficient means of identification of the optimal peptide in the searched chemical space.

Activity determinants of helical antimicrobial peptides: a large-scale computational study

Antimicrobial peptides (AMPs), produced by a wide range of organisms, have attracted attention due to their potential use as novel antibiotics. The majority of these peptides are cationic and are thought to function by permeabilizing the bacterial membrane, either by making pores or by dissolving it ('carpet' model). A key hypothesis in the literature is that antimicrobial and hemolytic activity correlate with binding affinity to anionic and zwitterionic membranes, respectively. Here we test this hypothesis by using binding free energy data collected from the literature and theoretical binding energies calculated from implicit membrane models for 53 helical AMPs. We indeed find a correlation between binding energy and biological activity, depending on membrane anionic content: antibacterial activity correlates best with transfer energy to membranes with anionic lipid fraction higher than 30% and hemolytic activity correlates best with transfer energy to a 10% anionic membrane. However, the correlations are weak, with correlation coefficient up to 0.4. Weak correlations of the biological activities have also been found with other physical descriptors of the peptides, such as surface area occupation, which correlates significantly with antibacterial activity; insertion depth, which correlates significantly with hemolytic activity; and structural fluctuation, which correlates significantly with both activities. The membrane surface coverage by many peptides at the MIC is estimated to be much lower than would be required for the 'carpet' mechanism. Those peptides that are active at low surface coverage tend to be those identified in the literature as pore-forming. The transfer energy from planar membrane to cylindrical and toroidal pores was also calculated for these peptides. The transfer energy to toroidal pores is negative in almost all cases while that to cylindrical pores is more favorable in neutral than in anionic membranes. The transfer energy to pores correlates with the deviation from predictions of the 'carpet' model.

Designing antimicrobial peptides: form follows function

Multidrug-resistant bacteria are a severe threat to public health. Conventional antibiotics are becoming increasingly ineffective as a result of resistance, and it is imperative to find new antibacterial strategies. Natural antimicrobials, known as host defence peptides or antimicrobial peptides, defend host organisms against microbes but most have modest direct antibiotic activity. Enhanced variants have been developed using straightforward design and optimization strategies and are being tested clinically. Here, we describe advanced computer-assisted design strategies that address the difficult problem of relating primary sequence to peptide structure, and are delivering more potent, cost-effective, broad-spectrum peptides as potential next-generation antibiotics.

Antimicrobial peptides: key components of the innate immune system

Life-threatening infectious diseases are on their way to cause a worldwide crisis, as treating them effectively is becoming increasingly difficult due to the emergence of antibiotic resistant strains. Antimicrobial peptides (AMPs) form an ancient type of innate immunity found universally in all living organisms, providing a principal first-line of defense against the invading pathogens. The unique diverse function and architecture of AMPs has attracted considerable attention by scientists, both in terms of understanding the basic biology of the innate immune system, and as a tool in the design of molecular templates for new anti-infective drugs. AMPs are gene-encoded short (<100 amino acids), amphipathic molecules with hydrophobic and cationic amino acids arranged spatially, which exhibit broad spectrum antimicrobial activity. AMPs have been the subject of natural evolution, as have the microbes, for hundreds of millions of years. Despite this long history of co-evolution, AMPs have not lost their ability to kill or inhibit the microbes totally, nor have the microbes learnt to avoid the lethal punch of AMPs. AMPs therefore have potential to provide an important breakthrough and form the basis for a new class of antibiotics. In this review, we would like to give an overview of cationic antimicrobial peptides, origin, structure, functions, and mode of action of AMPs, which are highly expressed and found in humans, as well as a brief discussion about widely abundant, well characterized AMPs in mammals, in addition to pharmaceutical aspects and the additional functions of AMPs.

One step at a time: action mechanism of Sushi 1 antimicrobial peptide and derived molecules

Antimicrobial peptides (AMPs) are a crucial part of the innate immune system of eukaryotes and present a possible alternative to common antibiotics. It is therefore of great importance to understand their modes of action. Using a single-molecule approach in combination with high resolution imaging and bio-functional assays we were able to determine the different steps occurring during the action of the α-helical AMP Sushi 1 during bacterial lysis in spatial and temporal resolution in a biologically relevant context. Furthermore, we comment on the use of Sushi 1 as a template for new peptides to learn more about structure-function relationship of AMPs.

Connecting peptide physicochemical and antimicrobial properties by a rational prediction model

The increasing rate in antibiotic-resistant bacterial strains has become an imperative health issue. Thus, pharmaceutical industries have focussed their efforts to find new potent, non-toxic compounds to treat bacterial infections. Antimicrobial peptides (AMPs) are promising candidates in the fight against antibiotic-resistant pathogens due to their low toxicity, broad range of activity and unspecific mechanism of action. In this context, bioinformatics' strategies can inspire the design of new peptide leads with enhanced activity. Here, we describe an artificial neural network approach, based on the AMP's physicochemical characteristics, that is able not only to identify active peptides but also to assess its antimicrobial potency. The physicochemical properties considered are directly derived from the peptide sequence and comprise a complete set of parameters that accurately describe AMPs. Most interesting, the results obtained dovetail with a model for the AMP's mechanism of action that takes into account new concepts such as peptide aggregation. Moreover, this classification system displays high accuracy and is well correlated with the experimentally reported data. All together, these results suggest that the physicochemical properties of AMPs determine its action. In addition, we conclude that sequence derived parameters are enough to characterize antimicrobial peptides.

Descriptors for antimicrobial peptides

INTRODUCTION

A frightening increase in the number of isolated multidrug resistant bacterial strains linked to the decline in novel antimicrobial drugs entering the market is a great cause for concern. Cationic antimicrobial peptides (AMPs) have lately been introduced as a potential new class of antimicrobial drugs, and computational methods utilizing molecular descriptors can significantly accelerate the development of new peptide drug candidates.

AREAS COVERED

This paper gives a broad overview of peptide and amino-acid scale descriptors available for AMP modeling and highlights which of these are currently being used in quantitative structure-activity relationship (QSAR) studies for AMP optimization. Additionally, some key commercial computational tools are discussed, and both successful and less successful studies are referenced, illustrating some of the challenges facing AMP scientists. Through examples of different peptide QSAR studies, this review highlights some of the missing links and illuminates some of the questions that would be interesting to challenge in a more systematic fashion.

EXPERT OPINION

Computer-aided peptide QSAR using molecular descriptors may provide the necessary edge to peptide drug discovery, enabling successful design of a new generation anti-infective drug molecules. However, if this wonderful scenario is to play out, computational chemists and peptide microbiologists would need to start playing together and not just side by side.

Computational studies of protegrin antimicrobial peptides: a review

Antimicrobial peptides (AMPs) are small, naturally occurring peptides that exhibit strong antibacterial properties generally believed to be a result of selective bacterial membrane disruption. As a result, there has been significant interest in the development of therapeutic antibiotics based on AMPs; however, the poor understanding of the fundamental mechanism of action of these peptides has largely hampered such efforts. We present a summary of computational and theoretical investigations of protegrin, a particularly potent peptide that is both an excellent model for the mechanism of action of AMPs and a promising therapeutic candidate. Experimental investigations have shed light on many of the key steps in the action of protegrin: protegrin monomers are known to dimerize in various lipid environments; protegrin peptides interact strongly with lipid bilayer membranes, particularly anionic lipids; protegrins have been shown to form pores in lipid bilayers, which results in uncontrolled ion transport and may be a key factor in bacterial death. In this work, we present a comprehensive review of the computational and theoretical studies that have complemented and extended the information obtained from experimental work with protegrins, as well as a brief survey of the experimental biophysical studies that are most pertinent to such computational work. We show that a consistent, mechanistic description of the bactericidal mechanism of action of protegrins is emerging, and briefly outline areas where the current understanding is deficient. We hope that the research reviewed herein offers compelling evidence of the benefits of computational investigations of protegrins and other AMPs, as well as providing a useful guide to future work in this area.

Structural features governing the activity of lactoferricin-derived peptides that act in synergy with antibiotics against Pseudomonas aeruginosa in vitro and in vivo

Pseudomonas aeruginosa is naturally resistant to many antibiotics, and infections caused by this organism are a serious threat, especially to hospitalized patients. The intrinsic low permeability of P. aeruginosa to antibiotics results from the coordinated action of several mechanisms, such as the presence of restrictive porins and the expression of multidrug efflux pump systems. Our goal was to develop antimicrobial peptides with an improved bacterial membrane-permeabilizing ability, so that they enhance the antibacterial activity of antibiotics. We carried out a structure activity relationship analysis to investigate the parameters that govern the permeabilizing activity of short (8- to 12-amino-acid) lactoferricin-derived peptides. We used a new class of constitutional and sequence-dependent descriptors called PEDES (peptide descriptors from sequence) that allowed us to predict (Spearman's ρ = 0.74; P < 0.001) the permeabilizing activity of a new peptide generation. To study if peptide-mediated permeabilization could neutralize antibiotic resistance mechanisms, the most potent peptides were combined with antibiotics, and the antimicrobial activities of the combinations were determined on P. aeruginosa strains whose mechanisms of resistance to those antibiotics had been previously characterized. A subinhibitory concentration of compound P2-15 or P2-27 sensitized P. aeruginosa to most classes of antibiotics tested and counteracted several mechanisms of antibiotic resistance, including loss of the OprD porin and overexpression of several multidrug efflux pump systems. Using a mouse model of lethal infection, we demonstrated that whereas P2-15 and erythromycin were unable to protect mice when administered separately, concomitant administration of the compounds afforded long-lasting protection to one-third of the animals.

Metal-binding dependent disruption of membranes by designed helices

The de novo design of molecular switching peptides is of increasing interest because it tests and extends our fundamental understanding of this process while laying the groundwork for the creation of new chemical and biological sensors. Here, an alpha-helical amphiphilic cell-lytic peptide, mastoparan X, was engineered to bind divalent cations. Binding of Zn(II) or Ni(II) to the designed peptide Mst-HH stabilizes the lytic amphiphilic structure and increases the activity of the peptide. Although both Zn(II) and Ni(II) activate Mst-HH for membrane lysis, they appear to do so via different mechanisms. Additionally, a series of metal binding-site mutants were synthesized to assess the relationship of charge and helical propensity to the toxicity and switchability. Additionally, by changing the characteristics of the metal-binding ligands, we can vary the selectivity of the site.

Peptoid macrocycles: making the rounds with peptidomimetic oligomers

Macrocyclic constraints are often employed to rigidify the conformation of flexible oligomeric systems. This approach has recently been used to organize the structure of peptoid oligomers, which are peptidomimetics composed of chemically diverse N-substituted glycine monomer units. In this review, we describe advances in the synthesis and characterization of cyclic peptoids. We evaluate how the installation of covalent constraints between the oligomer termini or side chains has been effective in defining peptoid conformations. We also discuss the potential applications for this promising family of macrocyclic peptidomimetics.

Antimicrobial protegrin-1 forms ion channels: molecular dynamic simulation, atomic force microscopy, and electrical conductance studies

Antimicrobial peptides (AMPs) are an emerging class of antibiotics for controlling health effects of antibiotic-resistant microbial strains. Protegrin-1 (PG-1) is a model antibiotic among beta-sheet AMPs. Antibiotic activity of AMPs involves cell membrane damage, yet their membrane interactions, their 3D membrane-associated structures and the mechanism underlying their ability to disrupt cell membrane are poorly understood. Using complementary approaches, including molecular dynamics simulations, atomic force microscopy (AFM) imaging, and planar lipid bilayer reconstitution, we provide computational and experimental evidence that PG-1, a beta-hairpin peptide, forms ion channels. Simulations indicate that PG-1 forms channel-like structures with loosely attached subunits when reconstituted in anionic lipid bilayers. AFM images show the presence of channel-like structures when PG-1 is reconstituted in dioleoylphosphatidylserine/palmitoyloleoyl phosphatidylethanolamine bilayers or added to preformed bilayers. Planar lipid bilayer electrical recordings show multiple single channel conductances that are consistent with the heterogeneous oligomeric channel structures seen in AFM images. PG-1 channel formation seems to be lipid-dependent: PG-1 does not easily show ion channel electrical activity in phosphatidylcholine membranes, but readily shows channel activity in membranes rich in phosphatidylethanolamine or phosphatidylserine. The combined results support a model wherein the beta-hairpin PG-1 peptide acts as an antibiotic by altering cell ionic homeostasis through ion channel formation in cell membranes.

Inhibitory effect of gallic acid and its esters on 2,2'-azobis(2-amidinopropane)hydrochloride (AAPH)-induced hemolysis and depletion of intracellular glutathione in erythrocytes

The protective effect of gallic acid and its esters, methyl, propyl, and lauryl gallate, against 2,2'-azobis(2-amidinopropane)hydrochloride (AAPH)-induced hemolysis and depletion of intracellular glutathione (GSH) in erythrocytes was studied. The inhibition of hemolysis was dose-dependent, and the esters were significantly more effective than gallic acid. Gallic acid and its esters were compared with regard to their reactivity to free radicals, using the DPPH and AAPH/pyranine free-cell assays, and no significant difference was obtained. Gallic acid and its esters not only failed to inhibit the depletion of intracellular GSH in erythrocytes induced by AAPH but exacerbated it. Similarly, the oxidation of GSH by AAPH or horseradish peroxidase/H(2)O(2) in cell-free systems was exacerbated by gallic acid or gallates. This property could be involved in the recent findings on pro-apoptotic and pro-oxidant activities of gallates in tumor cells. We provide evidence that lipophilicity and not only radical scavenger potency is an important factor regarding the efficiency of antihemolytic substances.

Computer-based analysis, visualization, and interpretation of antimicrobial peptide activities

This chapter describes a computer-based method for analyzing the quantitative structure-activity relationships (QSAR) of antimicrobial peptides. Quantitative or qualitative activity measurements and known peptide sequences are used as input for the analysis. The analysis steps consist of the preprocessing which specifically deals with dilution series from an assay with luminescent bacteria, transformation of quantitative activity values into activity classes, a feature extraction method using molecular descriptors for amino acids, feature selection methods, visualization strategies, the classifier model design for discrimination of active and inactive peptides, and the in silico design of promising new peptide candidates.

Identification of novel antibacterial peptides by chemoinformatics and machine learning

The rise of antibiotic resistant pathogens is one of the most pressing global health issues. Discovery of new classes of antibiotics has not kept pace; new agents often suffer from cross-resistance to existing agents of similar structure. Short, cationic peptides with antimicrobial activity are essential to the host defenses of many organisms and represent a promising new class of antimicrobials. This paper reports the successful in silico screening for potent antibiotic peptides using a combination of QSAR and machine learning techniques. On the basis of initial high-throughput measurements of activity of over 1400 random peptides, artificial neural network models were built using QSAR descriptors and subsequently used to screen an in silico library of approximately 100,000 peptides. In vitro validation of the modeling showed 94% accuracy in identifying highly active peptides. The best peptides identified through screening were found to have activities comparable or superior to those of four conventional antibiotics and superior to the peptide most advanced in clinical development against a broad array of multiresistant human pathogens.

Use of artificial intelligence in the design of small peptide antibiotics effective against a broad spectrum of highly antibiotic-resistant superbugs

Increased multiple antibiotic resistance in the face of declining antibiotic discovery is one of society's most pressing health issues. Antimicrobial peptides represent a promising new class of antibiotics. Here we ask whether it is possible to make small broad spectrum peptides employing minimal assumptions, by capitalizing on accumulating chemical biology information. Using peptide array technology, two large random 9-amino-acid peptide libraries were iteratively created using the amino acid composition of the most active peptides. The resultant data was used together with Artificial Neural Networks, a powerful machine learning technique, to create quantitative in silico models of antibiotic activity. On the basis of random testing, these models proved remarkably effective in predicting the activity of 100,000 virtual peptides. The best peptides, representing the top quartile of predicted activities, were effective against a broad array of multidrug-resistant "Superbugs" with activities that were equal to or better than four highly used conventional antibiotics, more effective than the most advanced clinical candidate antimicrobial peptide, and protective against Staphylococcus aureus infections in animal models.

Indolicidin-derived antimicrobial peptide analogs with greater bacterial selectivity and requirements for antibacterial and hemolytic activities

Indolicidin (ILPWKWPWWPWRR-NH(2)) has received attention due to its unique primary structure and biological activities. In this study, amide bonds at various positions in indolicidin were replaced with the reduced amide bonds psi[CH(2)NH] and the effect of the secondary structure on the biological activity was investigated. The circular dichroism spectra revealed that the rigidity and hydrogen bond of the amide bond between Trp(8) and Trp(9) were important for stabilizing the turn structure of indolicidin. A structure-activity study revealed that the turn structure of indolicidin was not required for antimicrobial activity and leakage activity for LUVs with a negatively charged surface. The pseudopeptide containing two reduced amide bonds showed less hemolytic activity as well as improved stability without a decrease in its antimicrobial activity. These results will provide valuable information for designing indolicidin analogs with greater bacterial selectivity and increased stability and for elucidating the role of the secondary structure of membrane-active peptides for antimicrobial and hemolytic activities.

Interaction of an artificial antimicrobial peptide with lipid membranes

Antimicrobial peptides constitute an important part of the innate immune defense and are promising new candidates for antibiotics. Naturally occurring antimicrobial peptides often possess hemolytic activity and are not suitable as drugs. Therefore, a range of new synthetic antimicrobial peptides have been developed in recent years with promising properties. But their mechanism of action is in most cases not fully understood. One of these peptides, called V4, is a cyclized 19 amino acid peptide whose amino acid sequence has been modeled upon the hydrophobic/cationic binding pattern found in Factor C of the horseshoe crab (Carcinoscorpius rotundicauda). In this work we used a combination of biophysical techniques to elucidate the mechanism of action of V4. Langmuir-Blodgett trough, atomic force microscopy, Fluorescence Correlation Spectroscopy, Dual Polarization Interference, and confocal microscopy experiments show how the hydrophobic and cationic properties of V4 lead to a) selective binding of the peptide to anionic lipids (POPG) versus zwitterionic lipids (POPC), b) aggregation of vesicles, and above a certain concentration threshold to c) integration of the peptide into the bilayer and finally d) to the disruption of the bilayer structure. The understanding of the mechanism of action of this peptide in relation to the properties of its constituent amino acids is a first step in designing better peptides in the future.

Beta-hairpin peptidomimetics: design, structures and biological activities

The folded 3D structures of peptides and proteins provide excellent starting points for the design of synthetic molecules that mimic key epitopes (or surface patches) involved in protein-protein and protein-nucleic acid interactions. Protein epitope mimetics (PEMs) may recapitulate not only the structural and conformational properties of the target epitope but also their biological activities. By transferring the epitope from a recombinant to a synthetic scaffold that can be produced by parallel combinatorial methods, it is possible to optimize properties through iterative cycles of library synthesis and screening, and even to evolve new biological activities. One very interesting scaffold is found in beta-hairpin motifs, which are used by many proteins to mediate molecular recognition events. This motif is readily amenable to PEM design, for example, by transplanting hairpin loop sequences from folded proteins onto hairpin-stabilizing templates, such as the dipeptide D-Pro-L-Pro. In addition, beta-hairpin peptidomimetics can also be exploited to mimic other types of epitopes, such as those based on alpha-helical secondary structures. The size and shape of beta-hairpin PEMs appear well suited for the design of inhibitors of both protein-protein and protein-nucleic acid interactions, endeavors that have so far proven difficult using small "drug-like" molecules. In recent work, it was shown that beta-hairpin PEMs can be designed that mimic the canonical conformations of antibody hypervariable loops, suggesting that novel small-molecule antibody mimics may be feasible. Using naturally occurring peptides as starting points, beta-hairpin mimetics have been discovered that possess antimicrobial activity, while others are potent inhibitors of the chemokine receptor CXCR4. Beta-hairpin PEMs have also been designed and optimized that mimic an alpha-helical epitope in p53 and so block its interaction with HDM2. A crystal structure of one HDM2-mimetic complex revealed how the surface of the protein had adapted to the shape of the hairpin, thereby enhancing inhibitor affinity. Small folded RNA motifs also make interesting targets for inhibitor design. For example, beta-hairpin mimetics have been designed and optimized that bind with high affinity and good selectivity to the TAR and RRE RNA motifs from HIV-1. Solution structures of the mimetics both free and bound to the RNA target provided some surprises, as well as an improved understanding of the mechanisms of binding. These mimetics represent still a relatively new family of RNA-binding molecules, but clearly one with potential for development into novel antiviral agents.

Spectroscopic (FT-IR, FT-Raman, UV) and microbiological studies of di-substituted benzoates of alkali metals

The FT-IR, FT-Raman and UV spectra of 3,5-dihydroxybenzoic and 3,5-dichlorobenzoic acids as well as lithium, sodium, potassium, rubidium, caesium 3,5-dihydroxy- and 3,5-dichlorobenzoates were recorded, assigned and compared. The theoretical geometries, Mulliken atomic charges, IR wavenumbers were obtained in B3LYP/6-311++G** level. On the basis of the gathered experimental and theoretical data the effect of metals and substituents on the electronic system of studied compounds were investigated. Moreover, the antimicrobiological activity of studied compounds against two species of bacteria: Bacillus subtilis, Staphylococus aureus and one species of yeast: Candida albicans were studied after 24 and 48 h of incubation. The attempt was made, to find out whether there is any correlation between the first principal component and the degree of growth inhibition exhibited by studied compounds in relation to selected microorganisms.

Peptoids that mimic the structure, function, and mechanism of helical antimicrobial peptides

Antimicrobial peptides (AMPs) and their mimics are emerging as promising antibiotic agents. We present a library of "ampetoids" (antimicrobial peptoid oligomers) with helical structures and biomimetic sequences, several members of which have low-micromolar antimicrobial activities, similar to cationic AMPs like pexiganan. Broad-spectrum activity against six clinically relevant BSL2 pathogens is also shown. This comprehensive structure-activity relationship study, including circular dichroism spectroscopy, minimum inhibitory concentration assays, hemolysis and mammalian cell toxicity studies, and specular x-ray reflectivity measurements shows that the in vitro activities of ampetoids are strikingly similar to those of AMPs themselves, suggesting a strong mechanistic analogy. The ampetoids' antibacterial activity, coupled with their low cytotoxicity against mammalian cells, make them a promising class of antimicrobials for biomedical applications. Peptoids are biostable, with a protease-resistant N-substituted glycine backbone, and their sequences are highly tunable, because an extensive diversity of side chains can be incorporated via facile solid-phase synthesis. Our findings add to the growing evidence that nonnatural foldamers will emerge as an important class of therapeutics.

Short linear cationic antimicrobial peptides: screening, optimizing, and prediction

The problem of pathogenic antibiotic-resistant bacteria such as Staphylococcus aureus and Pseudomonas aeruginosa is worsening, demonstrating the urgent need for new therapeutics that are effective against multidrug-resistant bacteria. One potential class of substances is cationic antimicrobial peptides. More than 1000 natural occurring peptides have been described so far. These peptides are short (less than 50 amino acids long), cationic, amphiphilic, demonstrate different three-dimensional structures, and appear to have different modes of action. A new screening assay was developed to characterize and optimize short antimicrobial peptides. This assay is based on peptides synthesized on cellulose, combined with a bacterium, where a luminescence gene cassette was introduced. With help of this method tens of thousands of peptides can be screened per year. Information gained by this high-throughput screening can be used in quantitative structure-activity relationships (QSAR) analysis. QSAR analysis attempts to correlate chemical structure to measurement of biological activity using statistical methods. QSAR modeling of antimicrobial peptides to date has been based on predicting differences between peptides that are highly similar. The studies have largely addressed differences in lactoferricin and protegrin derivatives or similar de novo peptides. The mathematical models used to relate the QSAR descriptors to biological activity have been linear models such as principle component analysis or multivariate linear regression. However, with the development of high-throughput peptide synthesis and an antibacterial activity assay, the numbers of peptides and sequence diversity able to be studied have increased dramatically. Also, "inductive" QSAR descriptors have been recently developed to accurately distinguish active from inactive drug-like activity in small compounds. "Inductive" QSAR in combination with more complex mathematical modeling algorithms such as artificial neural networks (ANNs) may yield powerful new methods for in silico identification of novel antimicrobial peptides.

Inhibition of malaria parasite blood stages by tyrocidines, membrane-active cyclic peptide antibiotics from Bacillus brevis

Tyrothricin, a complex mixture of antibiotic peptides from Bacillus brevis, was reported in 1944 to have antimalarial activity rivalling that of quinine in chickens infected with Plasmodium gallinaceum. We have isolated the major components of tyrothricin, cyclic decapeptides collectively known as the tyrocidines, and tested them against the human malaria parasite Plasmodium falciparum using standard in vitro assays. Although the tyrocidines differ from each other by conservative amino acid substitutions in only three positions, their observed 50% parasite inhibitory concentrations (IC(50)) spanned three orders of magnitude (0.58 to 360 nM). Activity correlated strictly with increased apparent hydrophobicity and reduced total side-chain surface area and the presence of ornithine and phenylalanine in key positions. In contrast, mammalian cell toxicity and haemolytic activities of the respective peptides were considerably less variable (2.6 to 28 microM). Gramicidin S, a structurally analogous antimicrobial peptide, was less active (IC(50)=1.3 microM) and selective than the tyrocidines. It exerted its parasite inhibition by rapid and selective lysis of infected erythrocytes as judged by fluorescence and light microscopy. The tyrocidines, however, did not cause an overt lysis of infected erythrocytes, but an inhibition of parasite development and life-cycle progression.