APD3: the antimicrobial peptide database as a tool for research and education.

Natural antimicrobial peptides (AMPs) are gene-coded defense molecules discovered in all the three life domains: Eubacteria, Archaea, and Eukarya. The latter covers protists, fungi, plants, and animals. It is now recognized that amino acid composition, peptide sequence, and post-translational modifications determine to a large extent the structure and function of AMPs. This article systematically describes post-translational modifications of natural AMPs annotated in the antimicrobial peptide database (http://aps.unmc.edu/AP). Currently, 1147 out of 1755 AMPs in the database are modified and classified into more than 17 types. Through chemical modifications, the peptides fold into a variety of structural scaffolds that target bacterial surfaces or molecules within cells. Chemical modifications also confer desired functions to a particular peptide. Meanwhile, these modifications modulate other peptide properties such as stability. Elucidation of the relationship between AMP property and chemical modification inspires peptide engineering. Depending on the objective of our design, peptides may be modified in various ways so that the desired features can be enhanced whereas unwanted properties can be minimized. Therefore, peptide design plays an essential role in developing natural AMPs into a new generation of therapeutic molecules.

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Antimicrobial peptides for the prevention and treatment of dental caries: A concise review

This article is written for the 2020 tool issue of Protein Science. It briefly introduces the widely used antimicrobial peptide database, initially online in 2003. After a description of the main features of each database version and some recent additions, the focus is on the peptide design parameters for each of the four unified classes of natural antimicrobial peptides (AMPs). The amino acid signature in AMPs varies substantially, leading to a variety of structures for functional and mechanistic diversity. Also, Nature is a master of combinatorial chemistry by deploying different amino acids onto the same structural scaffold to tune peptide functions. In addition, the single-domain AMPs may be posttranslationally modified, self-assembled, or combined with other AMPs for function. Elucidation of the design principles of natural AMPs will facilitate future development of novel molecules for various applications.

Database screening and in vivo efficacy of antimicrobial peptides against methicillin-resistant Staphylococcus aureus USA300

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.

In silico analysis was used to evaluate storage proteins from plant tubers as potential precursors of bioactive peptides after simulated gastrointestinal digestion. Proteins derived from potato (patatins), sweet potato (sporamins), yam (dioscorins) and taro (tarin) were subjected to in silico gastrointestinal digestion with a combination of pepsin, chymotrypsin and trypsin in the BIOPEP database which led to the release of 387 peptide fragments which were predicted to have bioactivities such as dipeptidyl peptidase IV (DPP-IV), angiotensin converting enzyme (ACE), antioxidative and antithrombotic activities. Prediction of antimicrobial activity of the released peptides using the collection of antimicrobial peptides (CAMP) database indicated 28 peptides as potential antimicrobial peptides (AMPs) with varied percentage similarity with known AMPs in antimicrobial peptide database (APD). Furthermore, 32 peptides with potential anticancer activity were predicted using the AntiCP database while nine peptides were predicted to be bioactive according to peptideRanker but the precise bioactivity was not identified. The potato-derived proteins seem to be the richest source of DPP-IV inhibitory and antimicrobial peptides while yam-derived proteins yielded the highest amount of antihypertensive and anticancer peptides. The data suggests that storage proteins from the selected plants could release an array of non-toxic and species-specific bioactive peptides with health promoting effects suggesting that these tubers might serve as functional foods.

In 2023, the Antimicrobial Peptide Database (currently available at https://aps.unmc.edu) is 20-years-old. The timeline for the APD expansion in peptide entries, classification methods, search functions, post-translational modifications, binding targets, and mechanisms of action of antimicrobial peptides (AMPs) has been summarized in our previous Protein Science paper. This article highlights new database additions and findings. To facilitate antimicrobial development to combat drug-resistant pathogens, the APD has been re-annotating the data for antibacterial activity (active, inactive, and uncertain), toxicity (hemolytic and nonhemolytic AMPs), and salt tolerance (salt sensitive and insensitive). Comparison of the respective desired and undesired AMP groups produces new knowledge for peptide design. Our unification of AMPs from the six life kingdoms into "natural AMPs" enabled the first comparison with globular or transmembrane proteins. Due to the dominance of amphipathic helical and disulfide-linked peptides, cysteine, glycine, and lysine in natural AMPs are much more abundant than those in globular proteins. To include peptides predicted by machine learning, a new "predicted" group has been created. Remarkably, the averaged amino acid composition of predicted peptides is located between the lower bound of natural AMPs and the upper bound of synthetic peptides. Synthetic peptides in the current APD, with the highest cationic and hydrophobic amino acid percentages, are mostly designed with varying degrees of optimization. Hence, natural AMPs accumulated in the APD over 20 years have laid the foundation for machine learning prediction. We discuss future directions for peptide discovery. It is anticipated that the APD will continue to play a role in research and education.

The large variety of antimicrobial peptide (AMP) databases developed to date are characterized by a substantial overlap of data and similarity of sequences. Our goals are to analyze the levels of redundancy for all available AMP databases and use this information to build a new non-redundant sequence database. For this purpose, a new software tool is introduced. A comparative study of 25 AMP databases reveals the overlap and diversity among them and the internal diversity within each database. The overlap analysis shows that only one database (Peptaibol) contains exclusive data, not present in any other, whereas all sequences in the LAMP_Patent database are included in CAMP_Patent. However, the majority of databases have their own set of unique sequences, as well as some overlap with other databases. The complete set of non-duplicate sequences comprises 16 990 cases, which is almost half of the total number of reported peptides. On the other hand, the diversity analysis identifies the most and least diverse databases and proves that all databases exhibit some level of redundancy. Finally, we present a new parallel-free software, named Dover Analyzer, developed to compute the overlap and diversity between any number of databases and compile a set of non-redundant sequences. These results are useful for selecting or building a suitable representative set of AMPs, according to specific needs.

Amphibians are widely distributed on different continents, except for the polar regions. They are important sources for the isolation, purification and characterization of natural compounds, including peptides with various functions. Innate immune antimicrobial peptides (AMPs) play a critical role in warding off invading pathogens, such as bacteria, fungi, parasites, and viruses. They may also have other biological functions such as endotoxin neutralization, chemotaxis, anti-inflammation, and wound healing. This article documents a bioinformatic analysis of over 1000 amphibian antimicrobial peptides registered in the Antimicrobial Peptide Database (APD) in the past 18 years. These anuran peptides were discovered in Africa, Asia, Australia, Europe, and America from 1985 to 2019. Genomic and peptidomic studies accelerated the discovery pace and underscored the necessity in establishing criteria for peptide entry into the APD. A total of 99.9% of the anuran antimicrobial peptides are less than 50 amino acids with an average length of 24 and a net charge of +2.5. Interestingly, the various amphibian peptide families (e.g., temporins, brevinins, esculentins) can be connected through multiple length-dependent relationships. With an increase in length, peptide net charge increases, while the hydrophobic content decreases. In addition, glycine, leucine, lysine, and proline all show linear correlations with peptide length. These correlations improve our understanding of amphibian peptides and may be useful for prediction and design of new linear peptides with potential applications in treating infectious diseases, cancer and diabetes.

Chapter 9 - An overview of antimicrobial peptides

10 - Mammalian antimicrobial peptides

Antibiotic resistance, driven by the rise of pathogens like VRE and MRSA, poses a global health threat, prompting the exploration of antimicrobial peptides (AMPs) as alternatives to traditional antibiotics. AMPs, known for their broad-spectrum activity and structural flexibility, share characteristics with intrinsically disordered proteins, which lack a rigid structure and play diverse roles in cellular processes. This study aims to quantify the intrinsic disorder and liquid–liquid phase separation (LLPS) propensity in AMPs, advancing our understanding of their antimicrobial mechanisms and potential therapeutic applications. To investigate the propensity for intrinsic disorder and LLPS in AMPs, we compared the AMPs to the human proteome. The AMP sequences were retrieved from the AMP database (APD3), while the human proteome was obtained from the UniProt database. We analyzed amino acid composition using the Composition Profiler tool and assessed intrinsic disorder using various predictors, including PONDR® and IUPred, through the Rapid Intrinsic Disorder Analysis Online (RIDAO) platform. For LLPS propensity, we employed FuzDrop, and FuzPred was used to predict context-dependent binding behaviors. Statistical analyses, such as ANOVA and χ2 tests, were performed to determine the significance of observed differences between the two groups. We analyzed over 3000 AMPs and 20,000 human proteins to investigate differences in amino acid composition, intrinsic disorder, and LLPS potential. Composition analysis revealed distinct differences in amino acid abundance, with AMPs showing an enrichment in both order-promoting and disorder-promoting amino acids compared to the human proteome. Intrinsic disorder analysis, performed using a range of predictors, consistently demonstrated that AMPs exhibit higher levels of predicted disorder than human proteins, with significant differences confirmed by statistical tests. LLPS analysis, conducted using FuzDrop, showed that AMPs had a lower overall propensity for LLPS compared to human proteins, although specific subsets of AMPs exhibited high LLPS potential. Additionally, redox-dependent disorder predictions highlighted significant differences in how AMP and human proteins respond to oxidative conditions, further suggesting functional divergences between the two proteomes. CH-CDF plot analysis revealed that AMPs and human proteins occupy distinct structural categories, with AMPs showing a greater proportion of highly disordered proteins compared to the human proteome. These findings underscore key molecular differences between AMPs and human proteins, with implications for their antimicrobial activity and potential therapeutic applications. Our study reveals that AMPs possess a significantly higher degree of intrinsic disorder and specific subsets exhibit LLPS potential, distinguishing them from the human proteome. These molecular characteristics likely contribute to their antimicrobial function and adaptability, offering valuable insights for developing novel therapeutic strategies to combat antibiotic resistance.

Because of the rapid development of multidrug resistance, conventional antibiotics cannot kill pathogenic bacteria efficiently. New antibiotic treatments such as antimicrobial peptides (AMPs) can provide a possible solution to the antibiotic-resistance crisis. However, the identification of AMPs using experimental methods is expensive and time-consuming. Meanwhile, few studies use amino acid compositions (AACs) and physicochemical properties with different sequence lengths against different organisms to predict AMPs. Therefore, the major purpose of this study is to identify AMPs on seven categories of organisms, including amphibians, humans, fish, insects, plants, bacteria, and mammals. According to the one-rule attribute evaluation, the selected features were used to construct the predictive models based on the random forest algorithm. Compared to the accuracies of iAMP-2L (a web-server for identifying AMPs and their functional types), ADAM (a database of AMP), and MLAMP (a multi-label AMP classifier), the proposed method yielded higher than 92% in predicting AMPs on each category. Additionally, the sensitivities of the proposed models in the prediction of AMPs of seven organisms were higher than that of all other tools. Furthermore, several physicochemical properties (charge, hydrophobicity, polarity, polarizability, secondary structure, normalized van der Waals volume, and solvent accessibility) of AMPs were investigated according to their sequence lengths. As a result, the proposed method is a practical means to complement the existing tools in the characterization and identification of AMPs in different organisms.

The study of antimicrobial compounds of animal origin, particularly antimicrobial peptides (AMPs), is a current research topic. However, extracting endogenous AMPs is a challenging process and requires the application of targeted enzymatic processing principles based on knowledge of the structure of prepropeptide molecules — precursors of AMPs. In this study, a search was conducted for antimicrobial peptides present in Sus scrofa and Bos taurus organisms, as well as their precursors, using The Antimicrobial Peptide Database and UniProtKB databases. In the amino acid sequences of prepropeptides, the sequences of the mature peptides were found, and cleavage sites for trypsin, bacterial collagenase (type I), and neutrophil elastase were determined. As a result of the search for antimicrobial compounds in The Antimicrobial Peptide Database, 18 antimicrobial peptides from Sus scrofa and 40 antimicrobial peptides from Bos taurus were identified. Based on the results of determining cleavage sites in AMP precursors, enzymes were ranked from less preferred to more preferred for AMP release as follows: bacterial collagenase (type I) ≤ trypsin < neutrophil elastase. This order is justified not only by the number of suitable cleavage sites and their accuracy but also by the action of enzymes within mature AMPs: it is important to consider that enzymes can “cut” the peptides themselves, thereby reducing their antimicrobial activity. The bioinformatics analysis conducted is applicable for both primary screening of raw material potential and determining of suitable enzymes for extracting antimicrobial compounds from Sus scrofa and Bos taurus organisms.