Peptide-Protein Interaction Studies of Antimicrobial Peptides Targeting Middle East Respiratory Syndrome Coronavirus Spike Protein: An In Silico Approach

The novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has now been declared as a global pandemic by the World Health Organization (WHO). Several drug molecules have been proposed that can be used against the virus. As an alternative to effective drug molecules, the antiviral peptides have the potential for effective application to control the infectious disease. In this work, the anti- SARS-CoV-2 effect of dermaseptin peptide molecules produced by the skin of the frog was evaluated by using the computational method. Three numbers of antiviral dermaseptin peptides were obtained by searching the antimicrobial peptide database (APD). First, the structure prediction of peptides was done by Pep Fold 2.0 server followed by structure validation by PROCHECK program. Then, the protein-peptide docking simulations were performed using the COVID-19 docking server. The peptides' binding affinity with the SARS-CoV-2 spike protein macromolecule was evaluated along with eight negative control peptides and human angiotensin converting enzymes 2 (ACE2). The protein-peptide docking and interaction analysis resulted in finding that dermaseptin-S9 peptide molecule was the most efficient molecule among the selected peptides with a binding energy of -331.54 KJ/mole. Hence, as a follow-up study, the dermaseptin-S9 peptide molecule can be further designed to enhance its specificity and binding affinity for its better use against the SARSCoV-2 disease. HIGHLIGHTS Three numbers of antiviral dermaseptin peptides from APD database were in silico evaluated against SARS-CoV-2 spike protein. The antiviral dermaseptin -S9 peptide showed the highest binding affinity towards the SARS-CoV-2 spike protein macromolecule. The hydrophobic property of the distributed amino acids of the derrmaseptin-9 molecule might be related to the binding affinity.

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.

Identification and characterization of new putative antimicrobial peptides from scorpion Chaerilus tricostatus revealed by in silico analysis and structure modeling

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.

With the accelerating growth of antimicrobial resistance (AMR), there is an urgent need for new antimicrobial agents with low or no AMR. Antimicrobial peptides (AMPs) have been extensively studied as alternatives to antibiotics (ATAs). Coupled with the new generation of high-throughput technology for AMP mining, the number of derivatives has increased dramatically, but manual running is time-consuming and laborious. Therefore, it is necessary to establish databases that combine computer algorithms to summarize, analyze, and design new AMPs. A number of AMP databases have already been established, such as the Antimicrobial Peptides Database (APD), the Collection of Antimicrobial Peptides (CAMP), the Database of Antimicrobial Activity and Structure of Peptides (DBAASP), and the Database of Antimicrobial Peptides (dbAMPs). These four AMP databases are comprehensive and are widely used. This review aims to cover the construction, evolution, characteristic function, prediction, and design of these four AMP databases. It also offers ideas for the improvement and application of these databases based on merging the various advantages of these four peptide libraries. This review promotes research and development into new AMPs and lays their foundation in the fields of druggability and clinical precision treatment.

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.

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

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.

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 antimicrobial peptide database (APD, http://aps.unmc.edu/AP/) is an original database initially online in 2003. The APD2 (2009 version) has been regularly updated and further expanded into the APD3. This database currently focuses on natural antimicrobial peptides (AMPs) with defined sequence and activity. It includes a total of 2619 AMPs with 261 bacteriocins from bacteria, 4 AMPs from archaea, 7 from protists, 13 from fungi, 321 from plants and 1972 animal host defense peptides. The APD3 contains 2169 antibacterial, 172 antiviral, 105 anti-HIV, 959 antifungal, 80 antiparasitic and 185 anticancer peptides. Newly annotated are AMPs with antibiofilm, antimalarial, anti-protist, insecticidal, spermicidal, chemotactic, wound healing, antioxidant and protease inhibiting properties. We also describe other searchable annotations, including target pathogens, molecule-binding partners, post-translational modifications and animal models. Amino acid profiles or signatures of natural AMPs are important for peptide classification, prediction and design. Finally, we summarize various database applications in research and education.

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.

The antimicrobial peptide database (APD) has served the antimicrobial peptide field for 18 years. Because it is widely used in research and education, this article documents database milestones and key events that have transformed it into the current form. A comparison is made for the APD peptide statistics between 2010 and 2020, validating the major database findings to date. We also describe new additions ranging from peptide entries to search functions. Of note, the APD also contains antimicrobial peptides from host microbiota, which are important in shaping immune systems and could be linked to a variety of human diseases. Finally, the database has been re-programmed to the web branding and latest security compliance of the University of Nebraska Medical Center. The reprogrammed APD can be accessed at https://aps.unmc.edu.

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.

Chapter 18 - Database Resources Dedicated to Antimicrobial Peptides

Antibiotic resistance is a global issue and new anti-microbials are required. Anti-microbial peptides are important players of host innate immune systems that prevent infections. Due to their ability to eliminate drug-resistant pathogens, AMPs are promising candidates for developing the next generation of anti-microbials. The anti-microbial peptide database provides a useful tool for searching, predicting, and designing new AMPs. In the period from 2015-2019, ~500 new natural peptides have been registered. This article highlights a selected set of new AMP members with interesting properties. Teixobactin is a cell wall inhibiting peptide antibiotic, while darobactin inhibits a chaperone and translocator for outer membrane proteins. Remarkably, cOB1, a sex pheromone from commensal enterococci, restricts the growth of multidrug-resistant Enterococcus faecalis in the gut at a picomolar concentration. A novel proline-rich AMP has been found in the plant Brassica napus. A shrimp peptide MjPen- II comprises three different sequence domains: serine-rich, proline-rich, and cysteine-rich regions. Surprisingly, an amphibian peptide urumin specifically inhibits H1 hemagglutinin-bearing influenza A virus. Defensins are abundant and typically consist of three pairs of intramolecular disulfide bonds. However, rat rattusin dimerizes via forming five pairs of intermolecular disulfide bonds. While human LL-37 can be induced by vitamin D, vitamin A induces the expression of resistin-like molecule alpha (RELMα) in mice. The isolation and characterization of an alternative human cathelicidin peptide, TLN-58, substantiates the concept of one gene multiple peptides. The involvement of a fly AMP nemuri in sleep induction may promote the research on the relationship between sleep and infection control. The functional roles of AMPs continue to grow and the general term "innate immune peptides" becomes useful. These discoveries widen our view on the anti-microbial peptides and may open new opportunities for developing novel peptide therapeutics for different applications.