RAPD: a database of recombinantly-produced antimicrobial peptides

Development strategies and application of antimicrobial peptides as future alternatives to in-feed antibiotics

The use of in-feed antibiotics has been widely restricted due to the significant environmental pollution and food safety concerns they have caused. Antimicrobial peptides (AMPs) have attracted widespread attention as potential future alternatives to in-feed antibiotics owing to their demonstrated antimicrobial activity and environment friendly characteristics. However, the challenges of weak bioactivity, immature stability, and low production yields of natural AMPs impede practical application in the feed industry. To address these problems, efforts have been made to develop strategies for approaching the AMPs with enhanced properties. Herein, we summarize approaches to improving the properties of AMPs as potential alternatives to in-feed antibiotics, mainly including optimization of structural parameters, sequence modification, selection of microbial hosts, fusion expression, and industrially fermentation control. Additionally, the potential for application of AMPs in animal husbandry is discussed. This comprehensive review lays a strong theoretical foundation for the development of in-feed AMPs to achieve the public health globally.

Antimicrobial peptides: An alternative to traditional antibiotics

As antibiotic-resistant bacteria and genes continue to emerge, the identification of effective alternatives to traditional antibiotics has become a pressing issue. Antimicrobial peptides are favored for their safety, low residue, and low resistance properties, and their unique antimicrobial mechanisms show significant potential in combating antibiotic resistance. However, the high production cost and weak activity of antimicrobial peptides limit their application. Moreover, traditional laboratory methods for identifying and designing new antimicrobial peptides are time-consuming and labor-intensive, hindering their development. Currently, novel technologies, such as artificial intelligence (AI) are being employed to develop and design new antimicrobial peptide resources, offering new opportunities for the advancement of antimicrobial peptides. This article summarizes the basic characteristics and antimicrobial mechanisms of antimicrobial peptides, as well as their advantages and limitations, and explores the application of AI in antimicrobial peptides prediction amd design. This highlights the crucial role of AI in enhancing the efficiency of antimicrobial peptide research and provides a reference for antimicrobial drug development.

Developing anti-microbial peptide database version 1 to provide comprehensive and exhaustive resource of manually curated AMPs

Anti-Microbial Peptide Database version 1 (AMPDB v1) is a meticulously curated resource that aims to address the limitations of existing databases in the field of antimicrobial research. We have utilized the latest technology and put our best efforts into adding all relevant tools to cater to the needs of our users. AMPDB v1 is a derived database, built upon information gathered from the available resources and boasts a significant size of 59,122 entries which are classified into 88 classes. All the information in this resource was curated manually. Sequence alignment and protein feature calculation tools were integrated into the database in the form of web applications, to make them easy to use, quick, and responsive in real-time. We have included multiple types of browsing and searching options to enhance the user experience, from simple text search to a completely customizable advanced search page with intuitive options that let the user combine multiple options together to make a powerful search query. The database is accessible by a web browser at https://bblserver.org.in/ampdb/ .

Exploratory data analysis of physicochemical parameters of natural antimicrobial and anticancer peptides: Unraveling the patterns and trends for the rational design of novel peptides

Introduction

Peptide-based research has attained new avenues in the antibiotics and cancer drug resistance era. The basis of peptide design research lies in playing with or altering physicochemical parameters. Here in this work, we have done exploratory data analysis (EDA) of physicochemical parameters of antimicrobial peptides (AMPs) and anticancer peptides (ACPs), two promising therapeutics for microbial and cancer drug resistance to deduce patterns and trends.

Methods

Briefly, we have captured the natural AMPs and ACPs data from the APD3 database. After cleaning the data manually and by CD-HIT web server, further data analysis has been done using Python-based packages, modlAMP and Pandas. We have extracted the descriptive statistics of 10 physicochemical parameters of AMPs and ACPs to build a comprehensive dataset containing all major parameters. The global analysis of datasets has been done using modlAMP to find the initial patterns in global data. The subsets of AMPs and ACPs were curated based on the length of the peptides and were analyzed by Pandas package to deduce the graphical profile of AMPs and ACPs.

Results

EDA of AMPs and ACPs shows selectivity in the length and amino acid compositions. The distribution of physicochemical parameters in defined quartile ranges was observed in the descriptive statistical and graphical analysis. The preferred length range of AMPs and ACPs was found to be 21-30 amino acids, whereas few outliers in each parameter were evident after EDA analysis.

Conclusion

The derived patterns from natural AMPs and ACPs can be used for the rational design of novel peptides. The statistical and graphical data distribution findings will help in combining the different parameters for potent design of novel AMPs and ACPs.

Antimicrobial Peptides: Challenging Journey to the Pharmaceutical, Biomedical, and Cosmeceutical Use

Antimicrobial peptides (AMPs), or host defence peptides, are short proteins in various life forms. Here we discuss AMPs, which may become a promising substitute or adjuvant in pharmaceutical, biomedical, and cosmeceutical uses. Their pharmacological potential has been investigated intensively, especially as antibacterial and antifungal drugs and as promising antiviral and anticancer agents. AMPs exhibit many properties, and some of these have attracted the attention of the cosmetic industry. AMPs are being developed as novel antibiotics to combat multidrug-resistant pathogens and as potential treatments for various diseases, including cancer, inflammatory disorders, and viral infections. In biomedicine, AMPs are being developed as wound-healing agents because they promote cell growth and tissue repair. The immunomodulatory effects of AMPs could be helpful in the treatment of autoimmune diseases. In the cosmeceutical industry, AMPs are being investigated as potential ingredients in skincare products due to their antioxidant properties (anti-ageing effects) and antibacterial activity, which allows the killing of bacteria that contribute to acne and other skin conditions. The promising benefits of AMPs make them a thrilling area of research, and studies are underway to overcome obstacles and fully harness their therapeutic potential. This review presents the structure, mechanisms of action, possible applications, production methods, and market for AMPs.

Secretory Expression and Application of Antilipopolysaccharide Factor 3 in Chlamydomonas reinhardtii

Anti-lipopolysaccharide factor is a class of antimicrobial peptides with lipopolysaccharide-binding structural domains, which has a broad antimicrobial spectrum, high antimicrobial activities, and broad application prospects in terms of the aquaculture industry. However, the low yield of natural antimicrobial peptides and their poor expression activity in bacteria and yeast have hindered their exploration and utilization. Therefore, in this study, the extracellular expression system of Chlamydomonas reinhardtii, by fusing the target gene with the signal peptide, was used to express anti-lipopolysaccharide factor 3 (ALFPm3) from Penaeus monodon in order to obtain highly active ALFPm3. Transgenic C. reinhardtii T-JiA2, T-JiA3, T-JiA5, and T-JiA6, were verified using DNA-PCR, RT-PCR, and immunoblot. Additionally, the IBP1-ALFPm3 fusion protein could be detected not only within the cells but also in the culture supernatant. Moreover, the extracellular secretion containing ALFPm3 was collected from algal cultures, and then its bacterial inhibitory activity was analyzed. The results showed that the extracts from T-JiA3 had an inhibition rate of 97% against four common aquaculture pathogenic bacteria, including Vibrio harveyi, Vibrio anguillarum, Vibrio alginolyticus, and Vibrio parahaemolyticus. The highest inhibition rate of 116.18% was observed in the test against V. anguillarum. Finally, the minimum inhibition concentration (MIC) of the extracts from T-JiA3 to V. harveyi, V. anguillarum, V. alginolyticus, and V. parahaemolyticus were 0.11 μg/μL, 0.088 μg/μL, 0.11 μg/μL, and 0.011 μg/μL, respectively. This study supports the foundation of the expression of highly active anti-lipopolysaccharide factors using the extracellular expression system in C. reinhardtii, providing new ideas for the expression of highly active antimicrobial peptides.

Milk-Derived Antimicrobial Peptides: Overview, Applications, and Future Perspectives

The growing consumer awareness towards healthy and safe food has reformed food processing strategies. Nowadays, food processors are aiming at natural, effective, safe, and low-cost substitutes for enhancing the shelf life of food products. Milk, besides being a rich source of nutrition for infants and adults, serves as a readily available source of precious functional peptides. Due to the existence of high genetic variability in milk proteins, there is a great possibility to get bioactive peptides with varied properties. Among other bioactive agents, milk-originated antimicrobial peptides (AMPs) are gaining interest as attractive and safe additive conferring extended shelf life to minimally processed foods. These peptides display broad-spectrum antagonistic activity against bacteria, fungi, viruses, and protozoans. Microbial proteolytic activity, extracellular peptidases, food-grade enzymes, and recombinant DNA technology application are among few strategies to tailor specific peptides from milk and enhance their production. These bioprotective agents have a promising future in addressing the global concern of food safety along with the possibility to be incorporated into the food matrix without compromising overall consumer acceptance. Additionally, in conformity to the current consumer demands, these AMPs also possess functional properties needed for value addition. This review attempts to present the basic properties, synthesis approaches, action mechanism, current status, and prospects of antimicrobial peptide application in food, dairy, and pharma industry along with their role in ensuring the safety and health of consumers.

The future of recombinant host defense peptides

The antimicrobial resistance crisis calls for the discovery and production of new antimicrobials. Host defense peptides (HDPs) are small proteins with potent antibacterial and immunomodulatory activities that are attractive for translational applications, with several already under clinical trials. Traditionally, antimicrobial peptides have been produced by chemical synthesis, which is expensive and requires the use of toxic reagents, hindering the large-scale development of HDPs. Alternatively, HDPs can be produced recombinantly to overcome these limitations. Their antimicrobial nature, however, can make them toxic to the hosts of recombinant production. In this review we explore the different strategies that are used to fine-tune their activities, bioengineer them, and optimize the recombinant production of HDPs in various cell factories.

Expression strategies for the efficient synthesis of antimicrobial peptides in plastids

Antimicrobial peptides (AMPs) kill microbes or inhibit their growth and are promising next-generation antibiotics. Harnessing their full potential as antimicrobial agents will require methods for cost-effective large-scale production and purification. Here, we explore the possibility to exploit the high protein synthesis capacity of the chloroplast to produce AMPs in plants. Generating a large series of 29 sets of transplastomic tobacco plants expressing nine different AMPs as fusion proteins, we show that high-level constitutive AMP expression results in deleterious plant phenotypes. However, by utilizing inducible expression and fusions to the cleavable carrier protein SUMO, the cytotoxic effects of AMPs and fused AMPs are alleviated and plants with wild-type-like phenotypes are obtained. Importantly, purified AMP fusion proteins display antimicrobial activity independently of proteolytic removal of the carrier. Our work provides expression strategies for the synthesis of toxic polypeptides in chloroplasts, and establishes transplastomic plants as efficient production platform for antimicrobial peptides.

A New Combination: Anti Glypican-3 scFv and Diphtheria Toxin with the Best Flexible Linker

Along with all cancer treatments, including chemotherapy, radiotherapy, and surgery, targeting therapy is a new treatment manner. Immunotoxins are new recombinant structures that kill cancer cells by targeting specific antigens. Immunotoxins are composed of two parts: toxin moiety, which disrupts protein synthesis process, and antigen binding moiety that bind to antigens on the surface of cancer cells. Glypican 3 (GPC3) is an oncofetal antigen on the surface of Hepatocellular carcinoma (HCC) cells. In this study, truncated Diphtheria toxin (DT389) was fused to humanized scFv YP7 by one, two and three repeats of GGGGS linkers (DT389-(GGGGS)_1-3YP7). In-silico and experimental investigation were performed to find out how many repeats of linker between toxin and scFv moieties are sufficient. Results of in-silico investigations revealed that the difference in the number of linkers does not have a significant effect on the main structures of the immunotoxin; however, the three-dimensional structure of two repeats of linker had a more appropriate structure compared to others with one and three linker replications. In addition, with enhancing the number of linkers, the probability of protein solubility has increased. Generally, the bioinformatics results of DT389-(GGGGS)₂-YP7 structure showed that expression and folding is suitable; and YP7 scFv has appropriate orientation to bind GPC3. The experimental investigations indicated that the fusion protein was expressed as near to 50% soluble. Due to the high binding affinity of YP7 scFv and the proven potency of diphtheria in inhibiting protein synthesis, the proposed DT389-(GGGGS)₂-YP7 immunotoxin is expected to function well in inhibiting HCC.

Successful use of Nicotiana tabacum hairy roots for the recombinant production of Cecropin A peptide

Cecropin A, as an antimicrobial peptide (AMP), is possible to use in medical and agricultural fields as a new and safe biocontrol agent. Therefore, it is highly necessary to find a cost-effective and scalable approach to generate a large scale of it. In this research, the Agrobacterium rhizogenes strain ATCC 15834 was used to transfer the Cecropin A gene to the Nicotiana tabacum. After confirmation of transgenic hairy roots, the antibacterial activity of purified Cecropin A peptide was measured using the agar gel diffusion method. Successful transforming of Cecropin A was confirmed at the RNA and protein levels in hairy root cells using RT-PCR and enzyme-linked immunosorbent assay (ELISA), respectively. The highest Cecropin A amount was detected in line 4 of the transgenic lines using ELISA in comparison with the nontransgenic line. Subsequently, the antimicrobial activity of Cecropin A extracted from line 4 showed the highest inhibition activity against Aspergillus niger. Besides, this activity was stable against Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Candida albicans pathogens after 7 days. The recombinant production of Cecropin A AMP had a yield of 63.81 μg/g of fresh weight. According to a significant yield, this system can be used to produce the Cecropin A peptide for pharmacological and food science applications.

An overview of databases and bioinformatics tools for plant antimicrobial peptides

Antimicrobial peptides (AMPs) are small, ribosomally synthesized proteins found in nearly all forms of life. In plants, AMPs play a central role in plant defense due to their distinct physicochemical properties. Due to their broad-spectrum antimicrobial activity and rapid killing action, plant AMPs have become important candidates for the development of new drugs to control plant and animal pathogens that are resistant to multiple drugs. Further research is required to explore the potential uses of these natural compounds. Computational strategies have been increasingly used to understand key aspects of antimicrobial peptides. These strategies will help to minimize the time and cost of "wet-lab" experimentation. Researchers have developed various tools and databases to provide updated information on AMPs. However, despite the increased availability of antimicrobial peptide resources in biological databases, finding AMPs from plants can still be a difficult task. The number of plant AMP sequences in current databases is still small and yet often redundant. To facilitate further characterization of plant AMPs, we have summarized information on the location, distribution, and annotations of plant AMPs available in the most relevant databases for AMPs research. We also mapped and categorized the bioinformatics tools available in these databases. We expect that this will allow researchers to advance in the discovery and development of new plant AMPs with potent biological properties. We hope to provide insights to further expand the application of AMPs in the fields of biotechnology, pharmacy, and agriculture.

Expression, Purification and Characterization of a Novel Hybrid Peptide CLP with Excellent Antibacterial Activity

CLP is a novel hybrid peptide derived from CM4, LL37 and TP5, with significantly reduced hemolytic activity and increased antibacterial activity than parental antimicrobial peptides. To avoid host toxicity and obtain high-level bio-production of CLP, we established a His-tagged SUMO fusion expression system in Escherichia coli. The fusion protein can be purified using a Nickel column, cleaved by TEV protease, and further purified in flow-through of the Nickel column. As a result, the recombinant CLP with a yield of 27.56 mg/L and a purity of 93.6% was obtained. The purified CLP exhibits potent antimicrobial activity against gram+ and gram- bacteria. Furthermore, the result of propidium iodide staining and scanning electron microscopy (SEM) showed that CLP can induce the membrane permeabilization and cell death of Enterotoxigenic Escherichia coli (ETEC) K88. The analysis of thermal stability results showed that the antibacterial activity of CLP decreases slightly below 70 °C for 30 min. However, when the temperature was above 70 °C, the antibacterial activity was significantly decreased. In addition, the antibacterial activity of CLP was stable in the pH range from 4.0 to 9.0; however, when pH was below 4.0 and over 9.0, the activity of CLP decreased significantly. In the presence of various proteases, such as pepsin, papain, trypsin and proteinase K, the antibacterial activity of CLP remained above 46.2%. In summary, this study not only provides an effective strategy for high-level production of antimicrobial peptides and evaluates the interference factors that affect the biological activity of hybrid peptide CLP, but also paves the way for further exploration of the treatment of multidrug-resistant bacterial infections.

LAMP2: a major update of the database linking antimicrobial peptides

Antimicrobial peptides (AMPs) have been regarded as a potential weapon to fight against drug-resistant bacteria, which is threating the globe. Thus, more and more AMPs had been designed or identified. There is a need to integrate them into a platform for researchers to facilitate investigation and analyze existing AMPs. The AMP database has become an important tool for the discovery and transformation of AMPs as agents. A database linking antimicrobial peptides (LAMPs), launched in 2013, serves as a comprehensive tool to supply exhaustive information of AMP on a single platform. LAMP2, an updated version of LAMP, holds 23 253 unique AMP sequences and expands to link 16 public AMP databases. In the current version, there are more than 50% (12 236) sequences only linking a single database and more than 45% of AMPs linking two or more database links. Additionally, updated categories based on primary structure, collection, composition, source and function have been integrated into LAMP2. Peptides in LAMP2 have been integrated in 8 major functional classes and 38 functional activities. More than 89% (20 909) of the peptides are experimentally validated peptides. A total of 1924 references were extracted and regarded as the evidence for supporting AMP activity and cytotoxicity. The updated version will be helpful to the scientific community.

Biotechnological Insights on the Expression and Production of Antimicrobial Peptides in Plants

The emergence of drug-resistant pathogens poses a serious critical threat to global public health and requires immediate action. Antimicrobial peptides (AMPs) are a class of short peptides ubiquitously found in all living forms, including plants, insects, mammals, microorganisms and play a significant role in host innate immune system. These peptides are considered as promising candidates to treat microbial infections due to its distinct advantages over conventional antibiotics. Given their potent broad spectrum of antimicrobial action, several AMPs are currently being evaluated in preclinical/clinical trials. However, large quantities of highly purified AMPs are vital for basic research and clinical settings which is still a major bottleneck hindering its application. This can be overcome by genetic engineering approaches to produce sufficient amount of diverse peptides in heterologous host systems. Recently plants are considered as potential alternatives to conventional protein production systems such as microbial and mammalian platforms due to their unique advantages such as rapidity, scalability and safety. In addition, AMPs can also be utilized for development of novel approaches for plant protection thereby increasing the crop yield. Hence, in order to provide a spotlight for the expression of AMP in plants for both clinical or agricultural use, the present review presents the importance of AMPs and efforts aimed at producing recombinant AMPs in plants for molecular farming and plant protection so far.

Ensemble-AMPPred: Robust AMP Prediction and Recognition Using the Ensemble Learning Method with a New Hybrid Feature for Differentiating AMPs

Antimicrobial peptides (AMPs) are natural peptides possessing antimicrobial activities. These peptides are important components of the innate immune system. They are found in various organisms. AMP screening and identification by experimental techniques are laborious and time-consuming tasks. Alternatively, computational methods based on machine learning have been developed to screen potential AMP candidates prior to experimental verification. Although various AMP prediction programs are available, there is still a need for improvement to reduce false positives (FPs) and to increase the predictive accuracy. In this work, several well-known single and ensemble machine learning approaches have been explored and evaluated based on balanced training datasets and two large testing datasets. We have demonstrated that the developed program with various predictive models has high performance in differentiating between AMPs and non-AMPs. Thus, we describe the development of a program for the prediction and recognition of AMPs using MaxProbVote, which is an ensemble model. Moreover, to increase prediction efficiency, the ensemble model was integrated with a new hybrid feature based on logistic regression. The ensemble model integrated with the hybrid feature can effectively increase the prediction sensitivity of the developed program called Ensemble-AMPPred, resulting in overall improvements in terms of both sensitivity and specificity compared to those of currently available programs.

Graph-based data integration from bioactive peptide databases of pharmaceutical interest: toward an organized collection enabling visual network analysis

MOTIVATION

Bioactive peptides have gained great attention in the academy and pharmaceutical industry since they play an important role in human health. However, the increasing number of bioactive peptide databases is causing the problem of data redundancy and duplicated efforts. Even worse is the fact that the available data is non-standardized and often dirty with data entry errors. Therefore, there is a need for a unified view that enables a more comprehensive analysis of the information on this topic residing at different sites.

RESULTS

After collecting web pages from a large variety of bioactive peptide databases, we organized the web content into an integrated graph database (starPepDB) that holds a total of 71 310 nodes and 348 505 relationships. In this graph structure, there are 45 120 nodes representing peptides, and the rest of the nodes are connected to peptides for describing metadata. Additionally, to facilitate a better understanding of the integrated data, a software tool (starPep toolbox) has been developed for supporting visual network analysis in a user-friendly way; providing several functionalities such as peptide retrieval and filtering, network construction and visualization, interactive exploration and exporting data options.

AVAILABILITY AND IMPLEMENTATION

Both starPepDB and starPep toolbox are freely available at http://mobiosd-hub.com/starpep/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Antimicrobial Peptides - Small but Mighty Weapons for Plants to Fight Phytopathogens

Antimicrobial Peptides (AMPs) have diverse structures, varied modes of actions, and can inhibit the growth of a wide range of pathogens at low concentrations. Plants are constantly under attack by a wide range of phytopathogens causing massive yield losses worldwide. To combat these pathogens, nature has armed plants with a battery of defense responses including Antimicrobial Peptides (AMPs). These peptides form a vital component of the two-tier plant defense system. They are constitutively expressed as part of the pre-existing first line of defense against pathogen entry. When a pathogen overcomes this barrier, it faces the inducible defense system, which responds to specific molecular or effector patterns by launching an arsenal of defense responses including the production of AMPs. This review emphasizes the structural and functional aspects of different plant-derived AMPs, their homology with AMPs from other organisms, and how their biotechnological potential could generate durable resistance in a wide range of crops against different classes of phytopathogens in an environmentally friendly way without phenotypic cost.

Collection of antimicrobial peptides database and its derivatives: Applications and beyond

Collection of antimicrobial peptides (CAMP), CAMPSign, and ClassAMP are open-access resources that have been developed to enhance research on antimicrobial peptides (AMPs). Comprehensive information on AMPs and machine learning-based predictive models are made available for users through these resources. As of date, CAMP_R3 has 10,247 sequences, 757 structures, and 114 family-specific signatures of AMPs along with associated tools for AMP sequence and structure analysis. CAMPSign uses family-specific sequence conservation, in the form of patterns and hidden Markov models for identification of AMPs. ClassAMP can be used to classify AMPs as antibacterial, antifungal, or antiviral based on sequence information. Here we describe CAMP and its derivatives and illustrate, with a few examples, the contribution of these online resources to the advancement of our current understanding of AMPs.

Natural ACE inhibitory peptides discovery from Spirulina (Arthrospira platensis) strain C1

Bioactive peptides from natural sources are utilized as food supplements for disease prevention and are increasingly becoming targets for drug discovery due to their specificity, efficacy and the absence of undesirable side effects, among others. Hence, the 'SpirPep' platform was developed to facilitate the in silico-based bioactive peptide discovery of these highly sought-after biomolecules from Spirulina(Arthrospira platensis) and to select the protease (thermolysin) used for in vitro digestion. Analysis of the predicted and experimentally-derived peptides suggested that they were mainly involved in ACE inhibition; thus, an ACEi assay was used to study the ACE inhibitory activity of five candidate peptides (SpirPep1-5), chosen from common peptides with multifunctional bioactivity and 100% bioactive peptide coverage, originating from phycobiliproteins. Results showed that SpirPep1 inhibited the activity of ACE with IC₅₀ of 1.748 mM and was non-toxic to fibroblasts of African green monkey kidney and human dermal skin. The molecular docking and MD simulation analysis revealed SpirPep1 had significantly lower binding scores than others and showed greater specificity to ACE. The non-bonded interaction energy of SpirPep1 and ACE was -883 kJ/mol. The SpirPep1 indirectly bound to ACE via the ACE substrate binding sites residues (D121, E123, S516, and S517) found in natural ACE inhibitory peptides (angiotensin II and bradykinin potentiating peptides). In addition, two unreported substrate binding sites including R124 and S219 were found. These results indicate that 'SpirPep' platform could increase the success rate for natural bioactive peptide discovery.

FeptideDB: A web application for new bioactive peptides from food protein

BACKGROUND

Bioactive peptides derived from food are important sources for alternative medicine and possess therapeutic activity. Several biochemical methods have been achieved to isolate bioactive peptides from food, which are tedious and time consuming. In silico methods are an alternative process to reduce cost and time with respect to bioactive peptide production. In this paper, FeptideDB was used to collect bioactive peptide (BP) data from both published research articles and available bioactive peptide databases. FeptideDB was developed to assist in forecasting bioactive peptides from food by combining peptide cleavage tools and database matching. Furthermore, this application was able to predict the potential of cleaved peptides from 'enzyme digestion module' to identify new ACE (angiotensin converting enzyme) inhibitors using an automatic molecular docking approach.

RESULTS

The FeptideDB web application contains tools for generating all possible peptides cleaved from input protein by various available enzymes. This database was also used for analysis and visualization to assist in bioactive peptide discovery. One module of FeptideDB has the ability to create 3-dimensional peptide structures to further predict inhibitors for the target protein, ACE (angiotensin converting enzyme).

CONCLUSIONS

FeptideDB is freely available to researchers who are interested in exploring bioactive peptides. The FeptideDB interface is easy to use, allowing users to rapidly retrieve data based on desired search criteria. FeptideDB is freely available at http://www4g.biotec.or.th/FeptideDB/. Ultimately, FeptideDB is a computational aid for assessing peptide bioactivities.

Heterologous Machine Learning for the Identification of Antimicrobial Activity in Human-Targeted Drugs

The emergence of microbes resistant to common antibiotics represent a current treat to human health. It has been recently recognized that non-antibiotic labeled drugs may promote antibiotic-resistance mechanisms in the human microbiome by presenting a secondary antibiotic activity; hence, the development of computer-assisted procedures to identify antibiotic activity in human-targeted compounds may assist in preventing the emergence of resistant microbes. In this regard, it is worth noting that while most antibiotics used to treat human infectious diseases are non-peptidic compounds, most known antimicrobials nowadays are peptides, therefore all computer-based models aimed to predict antimicrobials either use small datasets of non-peptidic compounds rendering predictions with poor reliability or they predict antimicrobial peptides that are not currently used in humans. Here we report a machine-learning-based approach trained to identify gut antimicrobial compounds; a unique aspect of our model is the use of heterologous training sets, in which peptide and non-peptide antimicrobial compounds were used to increase the size of the training data set. Our results show that combining peptide and non-peptide antimicrobial compounds rendered the best classification of gut antimicrobial compounds. Furthermore, this classification model was tested on the latest human-approved drugs expecting to identify antibiotics with broad-spectrum activity and our results show that the model rendered predictions consistent with current knowledge about broad-spectrum antibiotics. Therefore, heterologous machine learning rendered an efficient computational approach to classify antimicrobial compounds.

Antimicrobial Peptides: Recent Insights on Biotechnological Interventions and Future Perspectives

With the unprecedented rise of drug-resistant pathogens, particularly antibiotic-resistant bacteria, and no new antibiotics in the pipeline over the last three decades, the issue of antimicrobial resistance has emerged as a critical public health threat. Antimicrobial Peptides (AMP) have garnered interest as a viable solution to this grave issue and are being explored for their potential antimicrobial applications. Given their low bioavailability in nature, tailoring new AMPs or strategizing approaches for increasing the yield of AMPs, therefore, becomes pertinent. The present review focuses on biotechnological interventions directed towards enhanced AMP synthesis and revisits existing genetic engineering and synthetic biology strategies for production of AMPs. This review further underscores the importance and potential applications of advanced gene editing technologies for the synthesis of novel AMPs in future.

Downstream processing of Cry4AaCter-induced inclusion bodies containing insect-derived antimicrobial peptides produced in Escherichia coli

The Cry4AaCter tag is a pull-down tag which promotes the formation of inclusion bodies (IBs) that can be resolubilized in an alkaline buffer. Here, we used the Cry4AaCter tag to create a platform for the production of antimicrobial peptides (AMPs) in Escherichia coli featuring a uniform resolubilization process independent of the peptide fused to the pull-down tag. The Cry4AaCter tag conserves the bioactivity of fusion proteins and thus allows the purification of simple AMPs and more complex AMPs stabilized by disulfide bonds. We developed a downstream process (DSP) for the purification of IBs containing the mutated Galleria mellonella insect metalloprotease inhibitor IMPI(I38V), which has a globular structure stabilized by five disulfide bonds. IMPI(I38V) is a potent inhibitor of the M4 metalloproteases used as virulence factors by several human pathogens. We used a single crossflow filtration for the washing and resolubilization of the Cry4AaCter-induced IBs and obtained bioactive IMPI(I38V) after tag removal. We achieved a 68-fold higher protein yield using our IB system compared to an alternative DSP approach in which a GST-fusion strategy was used to produce soluble IMPI(I38V). The Cry4AaCter-based process was transferable to gloverin (another G. mellonella AMP) and the visible marker green fluorescent protein, which accumulated in fluorescent IBs, confirming it is a broadly applicable strategy for the recovery of functional proteins.

Recombinant production of a chimeric antimicrobial peptide in E. coli and assessment of its activity against some avian clinically isolated pathogens

Over the last decades, poultry industry faced to the rapid emergence of multidrug-resistant bacteria as a global concern. Antimicrobial peptide (AMPs) known as potential antibiotic alternative and were considered as a new antimicrobial agent. Current methods of production and purification of AMPs have several limitations such as: costly, time-consuming and killing the producing host cells in recombinant form. In the present study, a chimeric peptide derived from camel lactoferrin was produced in Escherichia coli periplasmic space using a pET-based expression system and its antibacterial activity was determined on some avian pathogens in vitro. A carboxy-terminal polyhistidine tag was used for purification by Ni²⁺ affinity chromatography with an average yield of 0.42 g/L. The His-tagged chimeric peptide showed different range of antimicrobial activity against clinically isolated avian pathogens with low chicken blood hemolysis activity and high serum stability. Overall, the results of this investigation showed the recombinant chimeric peptide was successfully expressed in pET-based expression system and could be considered as a proper alternative for some currently used antibiotics in poultry industry and drugs veterinary medicine.

SpirPep: an in silico digestion-based platform to assist bioactive peptides discovery from a genome-wide database

Background

Bioactive peptides, including biological sources-derived peptides with different biological activities, are protein fragments that influence the functions or conditions of organisms, in particular humans and animals. Conventional methods of identifying bioactive peptides are time-consuming and costly. To quicken the processes, several bioinformatics tools are recently used to facilitate screening of the potential peptides prior their activity assessment in vitro and/or in vivo. In this study, we developed an efficient computational method, SpirPep, which offers many advantages over the currently available tools.

Results

The SpirPep web application tool is a one-stop analysis and visualization facility to assist bioactive peptide discovery. The tool is equipped with 15 customized enzymes and 1–3 miscleavage options, which allows in silico digestion of protein sequences encoded by protein-coding genes from single, multiple, or genome-wide scaling, and then directly classifies the peptides by bioactivity using an in-house database that contains bioactive peptides collected from 13 public databases. With this tool, the resulting peptides are categorized by each selected enzyme, and shown in a tabular format where the peptide sequences can be tracked back to their original proteins. The developed tool and webpages are coded in PHP and HTML with CSS/JavaScript. Moreover, the tool allows protein-peptide alignment visualization by Generic Genome Browser (GBrowse) to display the region and details of the proteins and peptides within each parameter, while considering digestion design for the desirable bioactivity. SpirPep is efficient; it takes less than 20 min to digest 3000 proteins (751,860 amino acids) with 15 enzymes and three miscleavages for each enzyme, and only a few seconds for single enzyme digestion. Obviously, the tool identified more bioactive peptides than that of the benchmarked tool; an example of validated pentapeptide (FLPIL) from LC-MS/MS was demonstrated. The web and database server are available at http://spirpepapp.sbi.kmutt.ac.th.

Conclusion

SpirPep, a web-based bioactive peptide discovery application, is an in silico-based tool with an overview of the results. The platform is a one-stop analysis and visualization facility; and offers advantages over the currently available tools. This tool may be useful for further bioactivity analysis and the quantitative discovery of desirable peptides.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2143-0) contains supplementary material, which is available to authorized users.

Antimicrobial peptides with selective antitumor mechanisms: prospect for anticancer applications

In the last several decades, there have been significant advances in anticancer therapy. However, the development of resistance to cancer drugs and the lack of specificity related to actively dividing cells leading to toxic side effects have undermined these achievements. As a result, there is considerable interest in alternative drugs with novel antitumor mechanisms. In addition to the recent approach using immunotherapy, an effective but much cheaper therapeutic option of pharmaceutical drugs would still provide the best choice for cancer patients as the first line treatment. Ribosomally synthesized cationic antimicrobial peptides (AMPs) or host defense peptides (HDP) display broad-spectrum activity against bacteria based on electrostatic interactions with negatively charged lipids on the bacterial surface. Because of increased proportions of phosphatidylserine (negatively charged) on the surface of cancer cells compared to normal cells, cationic amphipathic peptides could be an effective source of anticancer agents that are both selective and refractory to current resistance mechanisms. We reviewed herein the prospect for AMP application to cancer treatment, with a focus on modes of action of cationic AMPs.

In Silico Tools and Databases for Designing Peptide-Based Vaccine and Drugs

The prolonged conventional approaches of drug screening and vaccine designing prerequisite patience, vigorous effort, outrageous cost as well as additional manpower. Screening and experimentally validating thousands of molecules for a specific therapeutic property never proved to be an easy task. Similarly, traditional way of vaccination includes administration of either whole or attenuated pathogen, which raises toxicity and safety issues. Emergence of sequencing and recombinant DNA technology led to the epitope-based advanced vaccination concept, i.e., small peptides (epitope) can stimulate specific immune response. Advent of bioinformatics proved to be an adjunct in vaccine and drug designing. Genomic study of pathogens aid to identify and analyze the protective epitope. A number of in silico tools have been developed to design immunotherapy as well as peptide-based drugs in the last two decades. These tools proved to be a catalyst in drug and vaccine designing. This review solicits therapeutic peptide databases as well as in silico tools developed for designing peptide-based vaccine and drugs.

Computational resources and tools for antimicrobial peptides

Antimicrobial peptides (AMPs), as evolutionarily conserved components of innate immune system, protect against pathogens including bacteria, fungi, viruses, and parasites. In general, AMPs are relatively small peptides (<10 kDa) with cationic nature and amphipathic structure and have modes of action different from traditional antibiotics. Up to now, there are more than 19 000 AMPs that have been reported, including those isolated from nature sources or by synthesis. They have been considered to be promising substitutes of conventional antibiotics in the quest to address the increasing occurrence of antibiotic resistance. However, most AMPs have modest direct antimicrobial activity, and their mechanisms of action, as well as their structure-activity relationships, are still poorly understood. Computational strategies are invaluable assets to provide insight into the activity of AMPs and thus exploit their potential as a new generation of antimicrobials. This article reviews the advances of AMP databases and computational tools for the prediction and design of new active AMPs. Copyright © 2016 European Peptide Society and John Wiley & Sons, Ltd.

Preparation of Specific Polyclonal Antibody Against the Recombinant Mutacin Produced by sfGFP Fusion Protein Technology

Mutacin I, a bacteriocin produced by streptococcus mutans, displays an antimicrobial activity against many gram positive and some gram negative bacteria. Because of its medical importance, production of this short peptide in large scale for future applications is a significant challenge. This work described the improvement of a novel system to produce the recombinant mutacin using fusion protein technology.

The short peptide was expressed directly as a fusion protein with a superfolder form of the green florescent protein (sfGFP), resulting in a high yield expression of soluble sfGFP-mutacin fusion protein (30 kDa) in the cytoplasm of E. coli. Mutacin was released from the fusion by enzymatic cleavage at the tobacco etch virus (TEV) protease recognition site and separated from the carrier sfGFP by nickel affinity and gel filtration chromatography. An additional advantage of this fusion system was tested in the generation of mutacin-specific polyclonal antibodies. Specific anti-mutacin IgGs were affinity purified, and were able to recognize the mutacin-sfGFP fusion protein or the cleaved forms of mutacin.

Even though it was efficiently produced (25 mg/L) by this method, pure mutacin was devoid of antibiotic activity. Fourier transform infrared spectroscopy (FTIR) analysis revealed the absence of thioether bonds in the purified mutacin, which are critical for final structure and function of this antibiotic. Determining whether the activity of pure mutacin could be recovered by the reformation of such structures by chemical reaction needs more investigations. The development of this system will provide large quantities of mutacin for future studies and applications as broad spectrum antibacterial peptide.

A large-scale structural classification of antimicrobial peptides

Antimicrobial peptides (AMPs) are potent drug candidates against microbial organisms such as bacteria, fungi, parasites, and viruses. AMPs have abundant sequences and structures, two fundamental resources for bioinformatics researches, but analyses on how they associate with each other are either nonexistent or limited to partial classification and data. We thus present A Database of Anti-Microbial peptides (ADAM), which contains 7,007 unique sequences and 759 structures, to systematically establish comprehensive associations between AMP sequences and structures through structural folds and to provide an easy access to view their relationships. 30 distinct AMP structural fold clusters with more than one structure are detected and about a thousand AMPs are associated with at least one structural fold cluster. According to ADAM, AMP structural folds are limited—AMPs only cover about 3% of the overall protein fold space.

Engineering the heterologous expression of lanthipeptides in Escherichia coli by multigene assembly

Lantibiotics are an important class of ribosomally synthesised peptide antibiotics with a remarkable pharmacological potential. Structural variants of lantibiotics generated by peptide engineering in vivo are an important aspect for improving the peptide's efficacy, stability and bioavailability as well as production titre, which severely impacts the potential exploitation in pharmaceutical applications. Therefore, expression systems are needed which allow for a robust genetic access for ample mutagenesis experiments. Based on previous heterologous expression of the two-component lanthipeptide lichenicidin (Bliα and Bliβ) in Escherichia coli BLic5, we now employ a multigene assembly strategy for recombinant lantibiotic peptide production in the Gram-negative host. Two E. coli high copy plasmids for separate and increased expression of a two-component lantibiotic were cloned and tested for expression. From these E. coli HP expression strains, an up to 100 times increased expression was found compared with Bacillus licheniformis I89 and E. coli BLic5. Total expression yields reach 4 mg L(-1) for Bliα and 6 mg L(-1) for Bliβ. The expression system developed in this study constitutes an important cornerstone for future in vivo peptide engineering studies and is of significance for potential applications aiming at higher production titres of ribosomally synthesised, post translationally modified peptides.

Optimization of expression conditions for a novel NZ2114-derived antimicrobial peptide-MP1102 under the control of the GAP promoter in Pichia pastoris X-33

Background

The infections caused by antibiotic multidrug-resistant bacteria seriously threaten human health. To prevent and cure the infections caused by multidrug-resistant bacteria, new antimicrobial agents are required. Antimicrobial peptides are ideal therapy candidates for antibiotic-resistant pathogens. However, due to high production costs, novel methods of large-scale production are urgently needed.

Results

The novel plectasin-derived antimicrobial peptide-MP1102 gene was constitutively expressed under the control of the GAP promoter. The optimum carbon source and concentration were determined, and 4% glucose (w/v) was initially selected as the best carbon source. Six media were assayed for the improved yield of recombinant MP1102 (rMP1102). The total protein and rMP1102 yield was 100.06 mg/l and 42.83 mg/l, which was accomplished via the use of medium number 1. The peptone and yeast extract from Hongrun Baoshun (HRBS, crude industrial grade, Beijing, China) more effectively improved the total protein and the yield of rMP1102 to 280.41 mg/l and 120.57 mg/l compared to 190.26 mg/l and 78.01 mg/l that resulted from Oxoid (used in the research). Furthermore, we observed that the total protein, antimicrobial activity and rMP1102 yield from the fermentation supernatant increased from 807.42 mg/l, 384,000 AU/ml, and 367.59 mg/l, respectively, in pH5.0 to 1213.64 mg/l, 153,600 AU/ml and 538.17 mg/ml, respectively in pH 6.5 in a 5-l fermenter. Accordingly, the productivity increased from 104464 AU/mg rMP1102 in pH 5.0 to a maximum of 285412 AU/mg rMP1102 in pH 6.5. Finally, the recombinant MP1102 was purified with a cation-exchange column with a yield of 376.89 mg/l, 96.8% purity, and a molecular weight of 4382.9 Da, which was consistent with its theoretical value of 4383 Da.

Conclusions

It’s the highest level of antimicrobial peptides expressed in Pichia pastoris using GAP promoter so far. These results provide an economical method for the high-level production of rMP1102 under the control of the GAP promoter.

Antimicrobial peptides: an alternative for innovative medicines?

Antimicrobial peptides are small molecules with activity against bacteria, yeasts, fungi, viruses, bacteria, and even tumor cells that make these molecules attractive as therapeutic agents. Due to the alarming increase of antimicrobial resistance, interest in alternative antimicrobial agents has led to the exploitation of antimicrobial peptides, both synthetic and from natural sources. Thus, many peptide-based drugs are currently commercially available for the treatment of numerous ailments, such as hepatitis C, myeloma, skin infections, and diabetes. Initial barriers are being increasingly overcome with the development of cost-effective, more stable peptides. Herein, we review the available strategies for their synthesis, bioinformatics tools for the rational design of antimicrobial peptides with enhanced therapeutic indices, hurdles and shortcomings limiting the large-scale production of AMPs, as well as the challenges that the pharmaceutical industry faces on their use as therapeutic agents.

A simple and low-cost platform technology for producing pexiganan antimicrobial peptide in E. coli

Antimicrobial peptides, as a new class of antibiotics, have generated tremendous interest as potential alternatives to classical antibiotics. However, the large-scale production of antimicrobial peptides remains a significant challenge. This paper reports a simple and low-cost chromatography-free platform technology for producing antimicrobial peptides in Escherichia coli (E. coli). A fusion protein comprising a variant of the helical biosurfactant protein DAMP4 and the known antimicrobial peptide pexiganan is designed by joining the two polypeptides, at the DNA level, via an acid-sensitive cleavage site. The resulting DAMP4(var)-pexiganan fusion protein expresses at high level and solubility in recombinant E. coli, and a simple heat-purification method was applied to disrupt cells and deliver high-purity DAMP4(var)-pexiganan protein. Simple acid cleavage successfully separated the DAMP4 variant protein and the antimicrobial peptide. Antimicrobial activity tests confirmed that the bio-produced antimicrobial peptide has the same antimicrobial activity as the equivalent product made by conventional chemical peptide synthesis. This simple and low-cost platform technology can be easily adapted to produce other valuable peptide products, and opens a new manufacturing approach for producing antimicrobial peptides at large scale using the tools and approaches of biochemical engineering.

Prediction of bioactive peptides using artificial neural networks

Peptides are molecules of varying complexity, with different functions in the organism and with remarkable therapeutic interest. Predicting peptide activity by computational means can help us to understand their mechanism of action and deliver powerful drug-screening methodologies. In this chapter, we describe how to apply artificial neural networks to predict antimicrobial peptide activity.

Improved methods for classification, prediction, and design of antimicrobial peptides

Peptides with diverse amino acid sequences, structures, and functions are essential players in biological systems. The construction of well-annotated databases not only facilitates effective information management, search, and mining but also lays the foundation for developing and testing new peptide algorithms and machines. The antimicrobial peptide database (APD) is an original construction in terms of both database design and peptide entries. The host defense antimicrobial peptides (AMPs) registered in the APD cover the five kingdoms (bacteria, protists, fungi, plants, and animals) or three domains of life (bacteria, archaea, and eukaryota). This comprehensive database ( http://aps.unmc.edu/AP ) provides useful information on peptide discovery timeline, nomenclature, classification, glossary, calculation tools, and statistics. The APD enables effective search, prediction, and design of peptides with antibacterial, antiviral, antifungal, antiparasitic, insecticidal, spermicidal, anticancer activities, chemotactic, immune modulation, or antioxidative properties. A universal classification scheme is proposed herein to unify innate immunity peptides from a variety of biological sources. As an improvement, the upgraded APD makes predictions based on the database-defined parameter space and provides a list of the sequences most similar to natural AMPs. In addition, the powerful pipeline design of the database search engine laid a solid basis for designing novel antimicrobials to combat resistant superbugs, viruses, fungi, or parasites. This comprehensive AMP database is a useful tool for both research and education.