Unified QSAR approach to antimicrobials. 4. Multi-target QSAR modeling and comparative multi-distance study of the giant components of antiviral drug–drug complex networks

One limitation of almost all antiviral Quantitative Structure–Activity Relationships (QSAR) models is that they predict the biological activity of drugs against only one species of virus. Consequently, the development of multi-tasking QSAR models (mt-QSAR) to predict drugs activity against different species of virus is of the major vitally important. These mt-QSARs offer also a good opportunity to construct drug–drug Complex Networks (CNs) that can be used to explore large and complex drug-viral species databases. It is known that in very large CNs we can use the Giant Component (GC) as a representative sub-set of nodes (drugs) and but the drug–drug similarity function selected may strongly determines the final network obtained. In the three previous works of the present series we reported mt-QSAR models to predict the antimicrobial activity against different fungi [Gonzalez-Diaz, H.; Prado-Prado, F. J.; Santana, L.; Uriarte, E. Bioorg. Med. Chem. 2006, 14, 5973], bacteria [Prado-Prado, F. J.; Gonzalez-Diaz, H.; Santana, L.; Uriarte E. Bioorg. Med. Chem. 2007, 15, 897] or parasite species [Prado-Prado, F.J.; González-Díaz, H.; Martinez de la Vega, O.; Ubeira, F.M.; Chou K.C. Bioorg. Med. Chem. 2008, 16, 5871]. However, including these works, we do not found any report of mt-QSAR models for antivirals drug, or a comparative study of the different GC extracted from drug–drug CNs based on different similarity functions. In this work, we used Linear Discriminant Analysis (LDA) to fit a mt-QSAR model that classify 600 drugs as active or non-active against the 41 different tested species of virus. The model correctly classifies 143 of 169 active compounds (specificity = 84.62%) and 119 of 139 non-active compounds (sensitivity = 85.61%) and presents overall training accuracy of 85.1% (262 of 308 cases). Validation of the model was carried out by means of external predicting series, classifying the model 466 of 514, 90.7% of compounds. In order to illustrate the performance of the model in practice, we develop a virtual screening recognizing the model as active 92.7%, 102 of 110 antivirus compounds. These compounds were never use in training or predicting series. Next, we obtained and compared the topology of the CNs and their respective GCs based on Euclidean, Manhattan, Chebychey, Pearson and other similarity measures. The GC of the Manhattan network showed the more interesting features for drug–drug similarity search. We also give the procedure for the construction of Back-Projection Maps for the contribution of each drug sub-structure to the antiviral activity against different species.     

Unified QSAR approach to antimicrobials. Part 3: first multi-tasking QSAR model for input-coded prediction, structural back-projection, and complex networks clustering of antiprotozoal compounds

Several pathogen parasite species show different susceptibilities to different antiparasite drugs. Unfortunately, almost all structure-based methods are one-task or one-target Quantitative Structure-Activity Relationships (ot-QSAR) that predict the biological activity of drugs against only one parasite species. Consequently, multi-tasking learning to predict drugs activity against different species by a single model (mt-QSAR) is vitally important. In the two previous works of the present series we reported two single mt-QSAR models in order to predict the antimicrobial activity against different fungal (Bioorg. Med. Chem.2006, 14, 5973-5980) or bacterial species (Bioorg. Med. Chem.2007, 15, 897-902). These mt-QSARs offer a good opportunity (unpractical with ot-QSAR) to construct drug-drug similarity Complex Networks and to map the contribution of sub-structures to function for multiple species. These possibilities were unattended in our previous works. In the present work, we continue this series toward other important direction of chemotherapy (antiparasite drugs) with the development of an mt-QSAR for more than 500 drugs tested in the literature against different parasites. The data were processed by Linear Discriminant Analysis (LDA) classifying drugs as active or non-active against the different tested parasite species. The model correctly classifies 212 out of 244 (87.0%) cases in training series and 207 out of 243 compounds (85.4%) in external validation series. In order to illustrate the performance of the QSAR for the selection of active drugs we carried out an additional virtual screening of antiparasite compounds not used in training or predicting series; the model recognized 97 out of 114 (85.1%) of them. We also give the procedures to construct back-projection maps and to calculate sub-structures contribution to the biological activity. Finally, we used the outputs of the QSAR to construct, by the first time, a multi-species Complex Networks of antiparasite drugs. The network predicted has 380 nodes (compounds), 634 edges (pairs of compounds with similar activity). This network allows us to cluster different compounds and identify on average three known compounds similar to a new query compound according to their profile of biological activity. This is the first attempt to calculate probabilities of antiparasitic action of drugs against different parasites.     

Multi-target spectral moment QSAR versus ANN for antiparasitic drugs against different parasite species

There are many of pathogen parasite species with different susceptibility profile to antiparasitic drugs. Unfortunately, almost QSAR models predict the biological activity of drugs against only one parasite species. Consequently, predicting the probability with which a drug is active against different species with a single unify model is a goal of the major importance. In so doing, we use Markov Chains theory to calculate new multi-target spectral moments to fit a QSAR model that predict by the first time a mt-QSAR model for 500 drugs tested in the literature against 16 parasite species and other 207 drugs no tested in the literature using spectral moments. The data was processed by linear discriminant analysis (LDA) classifying drugs as active or non-active against the different tested parasite species. The model correctly classifies 311 out of 358 active compounds (86.9%) and 2328 out of 2577 non-active compounds (90.3%) in training series. Overall training performance was 89.9%. Validation of the model was carried out by means of external predicting series. In these series the model classified correctly 157 out 190, 82.6% of antiparasitic compounds and 1151 out of 1277 non-active compounds (90.1%). Overall predictability performance was 89.2%. In addition we developed four types of non Linear Artificial neural networks (ANN) and we compared with the mt-QSAR model. The improved ANN model had an overall training performance was 87%. The present work report the first attempts to calculate within a unify framework probabilities of antiparasitic action of drugs against different parasite species based on spectral moment analysis.     

Unified QSAR approach to antimicrobials. Part 2: predicting activity against more than 90 different species in order to halt antibacterial resistance

There are many different kinds of pathogenic bacteria species with very different susceptibility profiles to different antibacterial drugs. One limitation of QSAR models is that they consider the biological activity of drugs against only one species of bacteria. In a previous paper, we developed a unified Markov model to describe the biological activity of different drugs tested in the literature against some antimicrobial species. Consequently, predicting the probability with which a drug is active against different species of bacteria with a single unified model is a goal of major importance. The work described here develops the unified Markov model to describe the biological activity of more than 70 drugs from the literature tested against 96 species of bacteria. We applied linear discriminant analysis (LDA) to classify drugs as active or inactive against the different tested bacterial species. The model correctly classified 199 out of 237 active compounds (83.9%) and 168 out of 200 inactive compounds (84%). Overall training predictability was 84% (367 out of 437 cases). Validation of the model was carried out using an external predicting series, with the model classifying 202 out of 243 (i.e., 83.13%) of the compounds. In order to show how the model functions in practice, a virtual screening was carried out and the model recognized as active 84.5% (480 out of 568) antibacterial compounds not used in the training or predicting series. The current study is an attempt to calculate within a unified framework the probabilities of antibacterial action of drugs against many different species.     

Trichoplaxin — A new membrane-active antimicrobial peptide from placozoan cDNA

A method based on the use of signal peptide sequences from antimicrobial peptide (AMP) precursors was used to mine a placozoa expressed sequence tag database and identified a potential antimicrobial peptide from Trichoplax adhaerens. This peptide, with predicted sequence FFGRLKSVWSAVKHGWKAAKSR is the first AMP from a placozoan species, and was named trichoplaxin. It was chemically synthesized and its structural properties, biological activities and membrane selectivity were investigated. It adopts an α-helical structure in contact with membrane-like environments and is active against both Gram-negative and Gram-positive bacterial species (including MRSA), as well as yeasts from the Candida genus. The cytotoxic activity, as assessed by the haemolytic activity against rat erythrocytes, U937 cell permeabilization to propidium iodide and MCF7 cell mitochondrial activity, is significantly lower than the antimicrobial activity. In tests with membrane models, trichoplaxin shows high affinity for anionic prokaryote-like membranes with good fit in kinetic studies. Conversely, there is a low affinity for neutral eukaryote-like membranes and absence of a dose dependent response. With high selectivity for bacterial cells and no homologous sequence in the UniProt, trichoplaxin is a new potential lead compound for development of broad-spectrum antibacterial drugs.     

Melectin MAPs: the influence of dendrimerization on antimicrobial and hemolytic activity

The recently described antimicrobial peptide melectin (MEP, GFLSILKKVLPKVMAHMK-NH₂) exhibits high antimicrobial activity against Gram-positive and Gram-negative bacteria. Here we describe the synthesis and biological activities of 23 new analogues of MEP. We studied the influence of dimerization and tetramerization (MAP-constructs of MEP) on the antimicrobial and hemolytic activities, as well as the role of Met in positions 14 and 17 of the peptide chain. Oxidation of the Met to Met(O) and Met(O₂) decreases antimicrobial activity of all tested bacteria if the peptide is in the monomeric form, however, only to Staphylococcus aureus if in the form of dimer or tetramer. Dimerization and tetramerization increase the undesirable hemolytic activity of the peptides. Interestingly, substitution of Leu for Val in position 6 leads to the decrease of hemolytic activity. Introduction of the isosteric amino acid Nle into positions 14 or 17 or both leads to slight increase of hemolytic activity under preservation of high antimicrobial activities. Unfortunately, dimerization again leads to an increase of hemolytic activity.     

Methyl-Hydroxylamine as an Efficacious Antibacterial Agent That Targets the Ribonucleotide Reductase Enzyme

The emergence of multidrug-resistant bacteria has encouraged vigorous efforts to develop antimicrobial agents with new mechanisms of action. Ribonucleotide reductase (RNR) is a key enzyme in DNA replication that acts by converting ribonucleotides into the corresponding deoxyribonucleotides, which are the building blocks of DNA replication and repair. RNR has been extensively studied as an ideal target for DNA inhibition, and several drugs that are already available on the market are used for anticancer and antiviral activity. However, the high toxicity of these current drugs to eukaryotic cells does not permit their use as antibacterial agents. Here, we present a radical scavenger compound that inhibited bacterial RNR, and the compound''s activity as an antibacterial agent together with its toxicity in eukaryotic cells were evaluated. First, the efficacy of N-methyl-hydroxylamine (M-HA) in inhibiting the growth of different Gram-positive and Gram-negative bacteria was demonstrated, and no effect on eukaryotic cells was observed. M-HA showed remarkable efficacy against Mycobacterium bovis BCG and Pseudomonas aeruginosa. Thus, given the M-HA activity against these two bacteria, our results showed that M-HA has intracellular antimycobacterial activity against BCG-infected macrophages, and it is efficacious in partially disassembling and inhibiting the further formation of P. aeruginosa biofilms. Furthermore, M-HA and ciprofloxacin showed a synergistic effect that caused a massive reduction in a P. aeruginosa biofilm. Overall, our results suggest the vast potential of M-HA as an antibacterial agent, which acts by specifically targeting a bacterial RNR enzyme.     

Evaluation of antimicrobial activity of bacterial symbionts isolated from wild field cockroach Blattella vaga from Saudi Arabia

Drug-resistant pathogens form the main threat to global health during the current century. Annually, a lot of patients die in hospitals due to infection with one or more drug-resistant bacteria especially Staphylococcus aureus (MRSA). In the absence of new effective antimicrobial drugs, the number of deaths said to be increased. Searching for new antibiotics in our backyard form a part of scientist strategies to solve such serious health problem. Insects consider one of such interesting sources of the new era of antimicrobial drugs. Cockroaches as an example can live and adapt in a polluted area for a long time, so through this work field cockroach, Blattella vaga was collected from two semi-wild areas around Riyadh, Saudi Arabia for isolation of gut bacteria searching for new antimicrobial agents. Three species of bacteria were identified from field cockroach gut: Bacillus licheniformis, Bacillus subtilis, and Kocuria rosea. The three species were isolated, purified, and tested for their antimicrobial activity against four drug-resistant pathogens (three bacteria: Salmonella enterica (ATCC25566), Staphylococcus aureus (MRSA) (Clinical strain), and Streptococcus mutans (RCMB 017(1) ATCC ® 25175™) and one fungus: Candida albicans (RCMB005003(1) ATCC® 10231™)). The results show no antimicrobial activity of Bacillus subtilis and very good activity Bacillus licheniformis and Kocuria rosea. Bacillus licheniformis gives very effective activity against Candida albicans while Kocuria rosea is effective against MRSA and Streptococcus mutans. None of the gut isolated bacteria show any activity against Salmonella enterica. Such results revealed that the metabolites of these bacteria could be used as substitutes to the already used antibiotics to overcome the problem of multidrug-resistant human pathogens.     

Repurposing Salicylanilide Anthelmintic Drugs to Combat Drug Resistant Staphylococcus aureus

Staphylococcus aureus is a Gram-positive bacterium that has become the leading cause of hospital acquired infections in the US. Repurposing Food and Drug Administration (FDA) approved drugs for antimicrobial therapy involves lower risks and costs compared to de novo development of novel antimicrobial agents. In this study, we examined the antimicrobial properties of two commercially available anthelmintic drugs. The FDA approved drug niclosamide and the veterinary drug oxyclozanide displayed strong in vivo and in vitro activity against methicillin resistant S. aureus (minimum inhibitory concentration (MIC): 0.125 and 0.5 μg/ml respectively; minimum effective concentration: ≤ 0.78 μg/ml for both drugs). The two drugs were also effective against another Gram-positive bacteria Enterococcus faecium (MIC 0.25 and 2 μg/ml respectively), but not against the Gram-negative species Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter aerogenes. The in vitro antimicrobial activity of niclosamide and oxyclozanide were determined against methicillin, vancomycin, linezolid or daptomycin resistant S. aureus clinical isolates, with MICs at 0.0625-0.5 and 0.125-2 μg/ml for niclosamide and oxyclozanide respectively. A time-kill study demonstrated that niclosamide is bacteriostatic, whereas oxyclozanide is bactericidal. Interestingly, oxyclozanide permeabilized the bacterial membrane but neither of the anthelmintic drugs exhibited demonstrable toxicity to sheep erythrocytes. Oxyclozanide was non-toxic to HepG2 human liver carcinoma cells within the range of its in vitro MICs but niclosamide displayed toxicity even at low concentrations. These data show that the salicylanilide anthelmintic drugs niclosamide and oxyclozanide are suitable candidates for mechanism of action studies and further clinical evaluation for treatment of staphylococcal infections.     

Stepwise identification of potent antimicrobial peptides from human genome

The increasing incidence of hospital acquired infections caused by antibiotic resistant pathogens has led to an increase in morbidity and mortality, finding alternative antibiotics unaffected by resistance mechanisms is fundamentally important for treating this problem. Naturally occurring proteins usually carry short peptide fragments that exhibit noticeable biological activity against a wide variety of microorganisms such as bacteria, fungi and protozoa. Traditional discovery of such antimicrobially active fragments (i.e. antimicrobial peptides, AMPs) from protein repertoire is either random or led by chance. Here, we report the use of a rational protocol that combines in silico prediction and in vitro assay to identify potential AMPs with high activity and low toxicity from the entire human genome. In the procedure, a three-step inference strategy is first proposed to perform genome-wide analysis to infer AMPs in a high-throughput manner. By employing this strategy we are able to screen more than one million peptide candidates generated from various human proteins, from which we identify four highly promising samples, and subsequently their antibacterial activity on five strains as well as cytotoxicity on human myoblasts are tested experimentally. As a consequence, two high-activity, low-toxicity peptides are discovered, which could be used as the structural basis to further develop new antibiotics. In addition, from 1491 known AMPs we also derive a quantitative measure called antibacterial propensity index (API) for 20 naturally occurring amino acids, which shows a significant allometric correlation with the theoretical minimal inhibitory concentration of putative peptides against Gram-positive and Gram-negative bacteria. This study may provide a proof-of-concept paradigm for the genome-wide discovery of novel antimicrobial peptides by using a combination of in silico and in vitro analyses.     

Bacteriocins: perspective for the development of novel anticancer drugs

Antimicrobial peptides (AMPs) from prokaryotic source also known as bacteriocins are ribosomally synthesized by bacteria belonging to different eubacterial taxonomic branches. Most of these AMPs are low molecular weight cationic membrane active peptides that disrupt membrane by forming pores in target cell membranes resulting in cell death. While these peptides known to exhibit broad-spectrum antimicrobial activity, including antibacterial and antifungal, they displayed minimal cytotoxicity to the host cells. Their antimicrobial efficacy has been demonstrated in vivo using diverse animal infection models. Therefore, we have discussed some of the promising peptides for their ability towards potential therapeutic applications. Further, some of these bacteriocins have also been reported to exhibit significant biological activity against various types of cancer cells in different experimental studies. In fact, differential cytotoxicity towards cancer cells as compared to normal cells by certain bacteriocins directs for a much focused research to utilize these compounds as novel therapeutic agents. In this review, bacteriocins that demonstrated antitumor activity against diverse cancer cell lines have been discussed emphasizing their biochemical features, selectivity against extra targets and molecular mechanisms of action.

     

Diversity,Antimicrobial Action and Structure-Activity Relationship of Buffalo Cathelicidins

Cathelicidins are an ancient class of antimicrobial peptides (AMPs) with broad spectrum bactericidal activities. In this study, we investigated the diversity and biological activity of cathelicidins of buffalo, a species known for its disease resistance. A series of new homologs of cathelicidin4 (CATHL4), which were structurally diverse in their antimicrobial domain, was identified in buffalo. AMPs of newly identified buffalo CATHL4s (buCATHL4s) displayed potent antimicrobial activity against selected Gram positive (G+) and Gram negative (G-) bacteria. These peptides were prompt to disrupt the membrane integrity of bacteria and induced specific changes such as blebing, budding, and pore like structure formation on bacterial membrane. The peptides assumed different secondary structure conformations in aqueous and membrane-mimicking environments. Simulation studies suggested that the amphipathic design of buCATHL4 was crucial for water permeation following membrane disruption. A great diversity, broad-spectrum antimicrobial action, and ability to induce an inflammatory response indicated the pleiotropic role of cathelicidins in innate immunity of buffalo. This study suggests short buffalo cathelicidin peptides with potent bactericidal properties and low cytotoxicity have potential translational applications for the development of novel antibiotics and antimicrobial peptidomimetics.     

Effect of Axial Ligand Length on Biological and Anticancer Properties of Axially Disubstituted Silicon Phthalocyanines

In this study, three new axially disubstituted silicon phthalocyanines ( SiPc1–3 ) and their quaternized phthalocyanine derivatives ( QSiPc1–3 ) were prepared and characterized. The biological properties (antioxidant, antimicrobial, antibiofilm, and microbial cell viability activities) of the water-soluble silicon phthalocyanines were examined, as well. A 1 % DMSO diluted with pure water was used as a solvent in biological activity studies. All the compounds exhibited high antioxidant activity. They displayed efficient antimicrobial and antimicrobial photodynamic therapeutic properties against various microorganisms, especially Gram (+) bacteria. Additionally, they demonstrated high antibiofilm activities against S. aureus and P. aeruginosa. In addition, 100 % bacterial reduction was obtained for all the studied phthalocyanines against E. coli viable cells. Besides, the DNA cleavage and binding features of compounds ( QSiPc1–3 ) were studied using pBR322 DNA and CT-DNA, respectively. Furthermore, the human topoisomerase I enzyme inhibition activities of compounds QSiPc1 – 3 were studied. Anticancer properties of the water-soluble compounds were investigated using cell proliferation MTT assay. They exhibited anticarcinogenic activity against the human colon cancer cell line (DLD-1). Compounds QSiPc1 and QSiPc3 displayed a high anticarcinogenic effect on the DLD-1 cell line. The obtained results indicated that all the studied compounds may be effective biological agents and anticancer drugs after further investigations.     

Bis(N-amidinohydrazones) and N-(amidino)-N′-aryl-bishydrazones: New classes of antibacterial/antifungal agents

The emergence of multidrug-resistant bacterial and fungal strains poses a threat to human health that requires the design and synthesis of new classes of antimicrobial agents. We evaluated bis(N-amidinohydrazones) and N-(amidino)-N′-aryl-bishydrazones for their antibacterial and antifungal activities against panels of Gram-positive/Gram-negative bacteria as well as fungi. We investigated their potential to develop resistance against both bacteria and fungi by a multi-step resistance-selection method, explored their potential to induce the production of reactive oxygen species, and assessed their toxicity. In summary, we found that these compounds exhibited broad-spectrum antibacterial and antifungal activities against most of the tested strains with minimum inhibitory concentration (MIC) values ranging from <0.5 to >500 μM against bacteria and 1.0 to >31.3 μg/mL against fungi; and in most cases, they exhibited either superior or similar antimicrobial activity compared to those of the standard drugs used in the clinic. We also observed minimal emergence of drug resistance to these newly synthesized compounds by bacteria and fungi even after 15 passages, and we found weak to moderate inhibition of the human Ether-à-go-go-related gene (hERG) channel with acceptable IC₅₀ values ranging from 1.12 to 3.29 μM. Overall, these studies show that bis(N-amidinohydrazones) and N-(amidino)-N′-aryl-bishydrazones are potentially promising scaffolds for the discovery of novel antibacterial and antifungal agents.     

Antibacterial Activity of THAM Trisphenylguanide against Methicillin-Resistant Staphylococcus aureus

This study investigated the potential antibacterial activity of three series of compounds synthesized from 12 linear and branched polyamines with 2–8 amino groups, which were substituted to produce the corresponding guanides, biguanides, or phenylguanides, against Acinetobacter baumannii, Enterococcus faecalis, Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus. Antibacterial activity was measured for each compound by determining the minimum inhibitory concentration against the bacteria, and the toxicity towards mammalian cells was determined. The most effective compound, THAM trisphenylguanide, was studied in time-to-kill and cytoplasmic leakage assays against methicillin-resistant Staphylococcus aureus (MRSA, USA300) in comparison to chlorhexidine. Preliminary toxicity and MRSA challenge studies in mice were also conducted on this compound. THAM trisphenylguanide showed significant antibacterial activity (MIC ∼1 mg/L) and selectivity against MRSA relative to all the other bacteria examined. In time-to-kill assays it showed increased antimicrobial activity against MRSA versus chlorhexidine. It induced leakage of cytoplasmic content at concentrations that did not reduce cell viability, suggesting the mechanism of action may involve membrane disruption. Using an intraperitoneal mouse model of invasive MRSA disease, THAM trisphenylguanide reduced bacterial burden locally and in deeper tissues. This study has identified a novel guanide compound with selective microbicidal activity against Staphylococcus aureus, including a methicillin-resistant (MRSA) strain.     

Synthesis and evaluation of 1,3,4-oxadiazole derivatives for development as broad-spectrum antibiotics

The reality and intensity of antibiotic resistance in pathogenic bacteria calls for the rapid development of new antimicrobial drugs. In bacteria, trans-translation is the primary quality control mechanism for rescuing ribosomes arrested during translation. Because trans-translation is absent in eukaryotes but necessary to avoid ribosomal stalling and therefore essential for bacterial survival, it is a promising target either for novel antibiotics or for improving the activities of the protein synthesis inhibitors already in use. Oxadiazole derivatives display strong bactericidal activity against a large number of bacteria, but their effects on trans-translation were recently questioned. In this work, a series of new 1,3,4-oxadiazole derivatives and analogs were synthesized and assessed for their efficiency as antimicrobial agents against a wide range of gram-positive and gram-negative pathogenic strains. Despite the strong antimicrobial activity observed in these molecules, it turns out that they do not target trans-translation in vivo, but they definitely act on other cellular pathways.     

The lantibiotic nisin, a special case or not?

Nisin is a 34-residue-long peptide belonging to the group A lantibiotics with antimicrobial activity against Gram-positive bacteria. The presence of dehydrated residues and lanthionine rings (thioether bonds) in nisin, imposing structural restrains on the peptide, make it an interesting case for studying the mode of action. In addition, the relatively high activity (nM range) of nisin against Gram-positive bacteria indicates that nisin may be a special case in the large family of pore-forming peptides antibiotics. In this review, we attempted to dissect the mode of action of nisin concentrating on studies that used model membranes or biological membranes. The picture that emerges suggests that in model membrane systems, composed of only phospholipids, nisin behaves similar to the antimicrobial peptide magainin, albeit with an activity that is much lower as compared to its activity towards biological membranes. This difference can be contributed to a missing factor which nisin needs for its high activity. Novel results have identified the factor as Lipid II, a precursor in the bacterial cell wall synthesis. The special high affinity interaction of nisin with Lipid II resulting in high activity and the active role of Lipid II in the pore-formation process make nisin a special case.     

Identification and Characterization of Novel Lipophilic Antimicrobial Peptides Derived from Naturally Occurring Proteins

Microbes are increasingly developing defensive mechanisms against known drugs via mutations. There are signs of emergence of superbugs immune to most known antibiotics available. The need for a new class of drugs to counteract this problem is of paramount importance for continued general well being of mankind. A new class of drugs, antimicrobial peptides, has not been fully exploited primarily due to high cytotoxicity, poor lipophilicity preventing systemic distribution and stability. We have synthesised 9-amino acid residue cationic peptides RH01 and RH02 lipidated with myristoyl and octyl groups respectively. These peptides exhibited potent antimicrobial activity and low cytotoxicity. The lipopeptide RH01 has antimicrobial activity against a broad range of microorganisms including bacteria, yeast and filamentous fungi with greatest activity toward Gram-positive bacteria, including S. aureus MRSA stain, MIC’s ranging between 2–8 μM. The MIC for Gram-negative bacteria was higher ranging from between 30–250 μM. RH01 also had antimicrobial activity towards fungi showing good activity against the pathogenic yeast Candida albicans but was less active towards the filamentous fungi Aspergillus niger. The antimicrobial activity of RH01 as a measure of Ki₍₅₀₎ for E. coli and S. aureus was 35–60 μM and 3–7 μM, respectively. In-house data showed the compound is bactericidal even at higher bacteria concentration. The octylated lipopeptide RH02 has similar activities towards S. aureus (3.3 μM) and E coli (53.3 μM) as the myristolated RH01. There was no haemolytic activity of the lipopeptide RH01 towards human blood. Acute intravenous toxicity study in mice showed that both RH01 and RH02 induced no macroscopic abnormalities at their highest non-lethal dose of 75 mg/kg and 150 mg/kg bodyweight, respectively.Australian Peptide Conference Issue.     

Prediction of Antimicrobial Activity of Synthetic Peptides by a Decision Tree Model

Antimicrobial resistance is a persistent problem in the public health sphere. However, recent attempts to find effective substitutes to combat infections have been directed at identifying natural antimicrobial peptides in order to circumvent resistance to commercial antibiotics. This study describes the development of synthetic peptides with antimicrobial activity, created in silico by site-directed mutation modeling using wild-type peptides as scaffolds for these mutations. Fragments of antimicrobial peptides were used for modeling with molecular modeling computational tools. To analyze these peptides, a decision tree model, which indicated the action range of peptides on the types of microorganisms on which they can exercise biological activity, was created. The decision tree model was processed using physicochemistry properties from known antimicrobial peptides available at the Antimicrobial Peptide Database (APD). The two most promising peptides were synthesized, and antimicrobial assays showed inhibitory activity against Gram-positive and Gram-negative bacteria. Colossomin C and colossomin D were the most inhibitory peptides at 5 μg/ml against Staphylococcus aureus and Escherichia coli. The methods described in this work and the results obtained are useful for the identification and development of new compounds with antimicrobial activity through the use of computational tools.     

Duckweed (Lemna minor) as a model plant system for the study of human microbial pathogenesis

Background

Plant infection models provide certain advantages over animal models in the study of pathogenesis. However, current plant models face some limitations, e.g., plant and pathogen cannot co-culture in a contained environment. Development of such a plant model is needed to better illustrate host-pathogen interactions.

Methodology/Principal Findings

We describe a novel model plant system for the study of human pathogenic bacterial infection on a large scale. This system was initiated by co-cultivation of axenic duckweed (Lemna minor) plants with pathogenic bacteria in 24-well polystyrene cell culture plate. Pathogenesis of bacteria to duckweed was demonstrated with Pseudomonas aeruginosa and Staphylococcus aureus as two model pathogens. P. aeruginosa PAO1 caused severe detriment to duckweed as judged from inhibition to frond multiplication and chlorophyll formation. Using a GFP-marked PAO1 strain, we demonstrated that bacteria colonized on both fronds and roots and formed biofilms. Virulence of PAO1 to duckweed was attenuated in its quorum sensing (QS) mutants and in recombinant strains overexpressing the QS quenching enzymes. RN4220, a virulent strain of S. aureus, caused severe toxicity to duckweed while an avirulent strain showed little effect. Using this system for antimicrobial chemical selection, green tea polyphenols exhibited inhibitory activity against S. aureus virulence. This system was further confirmed to be effective as a pathogenesis model using a number of pathogenic bacterial species.

Conclusions/Significance

Our results demonstrate that duckweed can be used as a fast, inexpensive and reproducible model plant system for the study of host-pathogen interactions, could serve as an alternative choice for the study of some virulence factors, and could also potentially be used in large-scale screening for the discovery of antimicrobial chemicals.