A deep learning model for anti-inflammatory peptides identification based on deep variational autoencoder and contrastive learning.

As a class of biologically active molecules with significant immunomodulatory and anti-inflammatory effects, anti-inflammatory peptides have important application value in the medical and biotechnology fields due to their unique biological functions. Research on the identification of anti-inflammatory peptides provides important theoretical foundations and practical value for a deeper understanding of the biological mechanisms of inflammation and immune regulation, as well as for the development of new drugs and biotechnological applications. Therefore, it is necessary to develop more advanced computational models for identifying anti-inflammatory peptides. In this study, we propose a deep learning model named DAC-AIPs based on variational autoencoder and contrastive learning for accurate identification of anti-inflammatory peptides. In the sequence encoding part, the incorporation of multi-hot encoding helps capture richer sequence information. The autoencoder, composed of convolutional layers and linear layers, can learn latent features and reconstruct features, with variational inference enhancing the representation capability of latent features. Additionally, the introduction of contrastive learning aims to improve the model's classification ability. Through cross-validation and independent dataset testing experiments, DAC-AIPs achieves superior performance compared to existing state-of-the-art models. In cross-validation, the classification accuracy of DAC-AIPs reached around 88%, which is 7% higher than previous models. Furthermore, various ablation experiments and interpretability experiments validate the effectiveness of DAC-AIPs. Finally, a user-friendly online predictor is designed to enhance the practicality of the model, and the server is freely accessible at http://dac-aips.online .

Identification and Molecular Mechanism of Anti-inflammatory Peptides Isolated from Jack Bean Protein Hydrolysates: in vitro Studies with Human Intestinal Caco-2BBe Cells.

Jack bean (JB), Canavalia ensiformis (L.) DC, is a commonly cultivated legume in Indonesia. It is rich in protein, which can be hydrolyzed, making it potentially a good source of bioactive peptides. Intestinal inflammation is associated with several diseases, and the production of interleukin-8 (IL-8) in intestinal epithelial cells induced by tumor necrosis factor (TNF)-α has an important role in inflammatory reaction. The present study investigated the anti-inflammatory effects of peptides generated from enzymatic hydrolysis of JB protein on human intestinal Caco-2BBe cells. Additionally, in silico approaches were used to identify potential bioactive peptides. JB protein hydrolysate (JBPH) prepared using pepsin and pancreatin reduced the IL-8 expression at protein and mRNA levels in Caco-2BBe cells stimulated with TNF-α. Immunoblot analysis showed that the JBPH reduced the TNF-α-induced phosphorylation of c-Jun-NH(2)-terminal kinase, nuclear factor kappa B (NF-κB), and p38 proteins. Anti-inflammatory activity was observed in the 30% acetonitrile fraction of JBPH separated on a Sep-Pak C18 column. An ultrafiltration method revealed that relatively small peptides (< 3 kDa) had a potent inhibitory effect on the IL-8 production. Purification of the peptides by reversed-phase and anion-exchange high performance chromatography produced three peptide fractions with anti-inflammatory activities. A combination of mass spectrometry analysis and in silico approaches identified the potential anti-inflammatory peptides. Peptides derived from JB protein reduces the TNF-α-induced inflammatory response in Caco-2BBe cells via NF-κB and mitogen-activated protein kinase signaling pathways. Our results may lead to a novel therapeutic approach to promote intestinal health.

Anti-inflammatory peptide therapeutics and the role of sulphur containing amino acids (cysteine and methionine) in inflammation suppression: A review.

BACKGROUND: Inflammation serves as our body's immune response to combat infections, pathogens, viruses, and external stimuli. Inflammation can be classified into two types: acute inflammation and chronic inflammation. Non-steroidal anti-inflammatory medications (NSAIDs) are used to treat both acute and chronic inflammatory disorders. However, these treatments have various side effects such as reduced healing efficiency, peptic ulcers, gastrointestinal toxicities, etc. METHOD: This review assesses the potential of anti-inflammatory peptides (AIPs) derived from various natural sources, such as algae, fungi, plants, animals, and marine organisms. Focusing on peptides rich in cysteines and methionine, sulphur-containing amino acids known for their role in suppression of inflammation. RESULT: Due to their varied biological activity, ability to penetrate cells, and low cytotoxicity, bioactive peptides have garnered interest as possible therapeutic agents. The utilisation of AIPs has shown great potential in the treatment of disorders associated with inflammation. AIPs can be obtained from diverse natural sources such as algae, fungi, plants, and animals. Cysteine and methionine are sulphur-containing amino acids that aid in the elimination of free radicals, hence assisting in the treatment of inflammatory diseases. CONCLUSION: This review specifically examines several sources of AIPs including peptides that contain numerous cysteines and methionine. In addition, the biological characteristics of these amino acids and advancements in peptide delivery are also discussed.

IF-AIP: A machine learning method for the identification of anti-inflammatory peptides using multi-feature fusion strategy.

BACKGROUND: The most commonly used therapy currently for inflammatory and autoimmune diseases is nonspecific anti-inflammatory drugs, which have various hazardous side effects. Recently, some anti-inflammatory peptides (AIPs) have been found to be a substitute therapy for inflammatory diseases like rheumatoid arthritis and Alzheimer's. Therefore, the identification of these AIPs is an emerging topic that is equally important. METHODS: In this work, we have proposed an identification model for AIPs using a voting classifier. We used eight different feature descriptors and five conventional machine-learning classifiers. The eight feature encodings were concatenated to get a hybrid feature set. The five baseline models trained on the hybrid feature set were integrated via a voting classifier. Finally, a feature selection algorithm was used to select the optimal feature set for the construction of our final model, named IF-AIP. RESULTS: We tested the proposed model on two independent datasets. On independent data 1, the IF-AIP model shows an improvement of 3%-5.6% in terms of accuracies and 6.7%-10.8% in terms of MCC compared to the existing methods. On the independent dataset 2, our model IF-AIP shows an overall improvement of 2.9%-5.7% in terms of accuracy and 8.3%-8.6% in terms of MCC score compared to the existing methods. A comparative performance analysis was conducted between the proposed model and existing methods using a set of 24 novel peptide sequences. Notably, the IF-AIP method exhibited exceptional accuracy, correctly identifying all 24 peptides as AIPs. The source code, pre-trained models, and all datasets are made available at https://github.com/Mir-Saima/IF-AIP.

Prevention and potential repair of colitis: Beneficial effects and regulatory mechanisms of food-derived anti-inflammatory peptides.

Intestinal inflammatory diseases are increasingly prevalent worldwide, and their pathogenesis is still not fully understood. As of late, studies have discovered that food-derived peptides have specific anti-inflammatory activity and can play a positive role in intestinal health. At the same time, it has broad application prospects in the prevention and treatment of colitis because of its wide source, fast absorption, and high safety. This article reviews the structure-activity and quantity-effect relationships of food-derived peptides for their anti-inflammatory effects. It then discusses their mechanism of action in inhibiting colitis from four aspects. Food-derived anti-inflammatory peptides can delay the progression of the disease by stimulating innate immunity, inhibiting inflammation, and promoting wound healing. Further experiments showed that food-derived anti-inflammatory peptides could prevent and treat colitis through four mechanisms: (a) regulation of inflammatory cytokines; (b) regulation of inflammatory pathways; (c) regulation of intestinal epithelial barrier; (d) regulation of intestinal flora balance. However, due to the treatment of colitis having limitations, there is an urgent to develop food-derived anti-inflammatory peptides as a treatment or adjunctive treatment for colitis. This review highlights the positive effects of food-derived peptides on colitis and anticipates the appearance of mitigating peptides for the therapy of colitis.

Evaluation of Anti-Oxinflammatory and ACE-Inhibitory Properties of Protein Hydrolysates Obtained from Edible Non-Mulberry Silkworm Pupae (Antheraea assama and Philosomia ricinii).

Food-derived bioactive peptides (BAPs) obtained from edible insect-protein hold multiple activities promising the potential to target complex pathological mechanisms responsible for chronic health conditions such as hypertension development. In this study, enzymatic protein hydrolysates from non-mulberry edible silkworm Antheraea assama (Muga) and Philosomia ricini (Eri) pupae, specifically Alcalase (A. assama) and Papain (P. ricini) hydrolysates obtained after 60 and 240 min, exhibited the highest ACE-inhibitory and antioxidant properties. The hydrolysates' fractions (<3, 3-10 and >10 kDa), specifically Alc_M60min_F3 (≤3 kDa) and Pap_E240min_F3 (≤3 kDa), showed the highest antioxidant and ACE-inhibitory activities, respectively. Further RP-HPLC purified sub-fractions F4 and F6 showed the highest ACE inhibition as well as potent anti-oxinflammatory activities in lipopolysaccharide (LPS)-treated endothelial cells. Indeed, F4 and F6 ACE-inhibitory peptide fractions were effective in preventing p65 nuclear translocation after 3 h of LPS stimulation along with the inhibition of p38 MAPK phosphorylation in HUVEC cells. In addition, pretreatment with F4 and F6 ACE-inhibitory peptide fractions significantly prevented the LPS-induced upregulation of COX-2 expression and IL-1ß secretion, while the expression of NRF2 (nuclear factor erythroid 2-related factor 2)-regulated enzymes such as HO-1 and NQO1 was induced by both peptide fractions. The derived peptides from edible pupae protein hydrolysates have potentialities to be explored as nutritional approaches against hypertension and related cardiovascular diseases.

Proteomics Characterization of Food-Derived Bioactive Peptides with Anti-Allergic and Anti-Inflammatory Properties.

Bioactive peptides are found in foods and dietary supplements and are responsible for health benefits with applications in human and animal medicine. The health benefits include antihypertensive, antimicrobial, antithrombotic, immunomodulatory, opioid, antioxidant, anti-allergic and anti-inflammatory functions. Bioactive peptides can be obtained by microbial action, mainly by the gastrointestinal microbiota from proteins present in food, originating from either vegetable or animal matter or by the action of different gastrointestinal proteases. Proteomics can play an important role in the identification of bioactive peptides. High-resolution mass spectrometry is the principal technique used to detect and identify different types of analytes present in complex mixtures, even when available at low concentrations. Moreover, proteomics may provide the characterization of epitopes to develop new food allergy vaccines and the use of immunomodulating peptides to induce oral tolerance toward offending food allergens or even to prevent allergic sensitization. In addition, food-derived bioactive peptides have been investigated for their anti-inflammatory properties to provide safer alternatives to nonsteroidal anti-inflammatory drugs (NSAIDs). All these bioactive peptides can be a potential source of novel drugs and ingredients in food and pharmaceuticals. The following review is focused on food-derived bioactive peptides with antiallergic and anti-inflammatory properties and summarizes the new insights into the use of proteomics for their identification and quantification.

Anti-inflammatory action of ark shell (Scapharca subcrenata) protein hydrolysate in LPS-stimulated RAW264.7 murine macrophages.

Potential anti-inflammatory effects of ark shell (Scapharca subcrenata) protein hydrolysates were investigated. Ark shell protein hydrolysates were prepared using Alcalase® and pepsin and were designated ASAH and ASPH, respectively. The nitric oxide (NO) inhibitory activity of ASAH and ASPH was determined in lipopolysaccharides (LPS)-stimulated RAW264.7 murine macrophages, and the results showed that ASAH inhibited better NO inhibitory activity than ASPH. ASAH suppressed inflammatory mediator, a prostaglandin E2, secretion of pro-inflammatory cytokines (TNF-α, IL-1ß, and IL-6), and production of reactive oxygen species (ROS) dose dependently. It inhibited the protein expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) and simulated heme oxygenase-1 (HO-1) protein expression. However, the pharmacological approach revealed that pretreatment with zinc protoporphyrin ІX (ZnPP), an inhibitor of HO-1, reversed the anti-inflammatory effect of ASAH. Moreover, ASAH upregulated phosphorylation of mitogen-activated protein kinases (MAPKs) including ERK1/2, JNK1/2, and p38 MAPK. To find out the role of MAPKs phosphorylation, MAPKs inhibitors were used, and the results showed that ASAH-mediated HO-1 protein expression and Nrf2 nuclear translocation were abolished. Taken all together, this study revealed that ASAH has a potential anti-inflammatory activity through regulation of the MAPK-dependent HO-1/Nrf2 pathway. PRACTICAL APPLICATIONS: Food-derived marine bioactive peptides, due to their pivotal role in biological activities, are gaining much attention recently. However, the anti-inflammatory activities of ark shell protein hydrolysates still remain to be investigated. This study investigated that ASAH shows potential anti-inflammatory activities through regulation of the MAPK-dependent HO-1/Nrf2 pathway in RAW264.7 murine macrophages. These findings indicated that ASAH may be used as a dietary supplement, functional food, and medicinal drug for the management of inflammation and inflammation-associated diseases.

Purification and characterization of antioxidative and antimicrobial peptides from lactic-fermented sheep milk.

This study aims to identify antioxidant and antimicrobial peptides from sheep milk produced using Lactobacillus plantarum (KGL3A). It was inferred that antioxidative and antimicrobial activities increased with increasing incubation time, and antioxidative properties (ABTS assay, superoxide free radical & hydroxyl free radical scavenging activity were 34.5, 34.7, and 29.2% respectively) and antimicrobial properties against Escherichia coli, S. typhimurium, E. faecalis, & B. cereus were 11.3, 12.7, 13.3, & 12.3 mm. However, inoculation of culture at a level of 2.5% and 48 h fermentation give the highest proteolysis activities. Fermented sheep milk fractions of 3 & 10 kDa were analysed for antioxidative and antimicrobial activity, and the 10 kDa permeate showed the highest ABTS assay. The hydroxyl free radical scavenging activity was greatest in 10 kDa retentate and superoxide free radical scavenging activity was observed in 3 kDa permeate (34.7, 43.4, and 34.6%, respectively). Antimicrobial activity of 10 kDa retentate against B. cereus & E. coli (13.3 mm) was greater than 3 and 10 kDa retentate against S. typhimurium (13 mm) and 3 kDa retentate against E. faecalis (13.7 mm). The molecular weight of the protein was estimated using SDS-PAGE. On electrophoresis on a 2-D gel, 6 peptides were identified using RP-LC/MS. BIOPEP, a database for antioxidative and antimicrobial peptides, validated the antioxidative & antimicrobial activities of several peptides in sheep's milk that has been fermented. Sheep milk fermented using Lactobacillus could be considered a novel source of antioxidative and antimicrobial proteins. Supplementary Information: The online version contains supplementary material available at 10.1007/s13197-022-05493-2.

YAP9/A20 complex suppresses proinflammatory responses and provides novel anti-inflammatory therapeutic potentials.

Innate anti-inflammatory mechanisms are essential for immune homeostasis and can present opportunities to intervene inflammatory diseases. In this report, we found that YAP isoform 9 (YAP9) is an essential negative regulator of the potent inflammatory stimuli such as TNFα, IL-1ß, and LPS. YAP9 constitutively interacts with another anti-inflammatory regulator A20 (TNFAIP3) to suppress inflammatory responses, but A20 and YAP can function only in the presence of the other. YAP9 uses a short stretch of amino acids in the proline-rich domain (PRD) and transactivation domain (TAD) suppress the inflammatory signaling while A20 mainly uses the zinc finger domain 7 (ZF7). Cell-penetrating synthetic PRD, TAD, and ZF7 peptides act as YAP9 and A20 mimetics respectively to suppress the proinflammatory responses at the cellular level and in mice. Our data uncover a novel anti-inflammatory axis and anti-inflammatory agents that can be developed to treat acute or chronic conditions where TNFα, IL-1ß, or LPS plays a key role in initiating and/or perpetuating inflammation.

The Screening of Therapeutic Peptides for Anti-Inflammation through Phage Display Technology.

For the treatment of inflammatory illnesses such as rheumatoid arthritis and carditis, as well as cancer, several anti-inflammatory medications have been created over the years to lower the concentrations of inflammatory mediators in the body. Peptides are a class of medication with the advantages of weak immunogenicity and strong activity, and the phage display technique is an effective method for screening various therapeutic peptides, with a high affinity and selectivity, including anti-inflammation peptides. It enables the selection of high-affinity target-binding peptides from a complex pool of billions of peptides displayed on phages in a combinatorial library. In this review, we will discuss the regular process of using phage display technology to screen therapeutic peptides, and the peptides screened for anti-inflammation properties in recent years according to the target. We will describe how these peptides were screened and how they worked in vitro and in vivo. We will also discuss the current challenges and future outlook of using phage display to obtain anti-inflammatory therapeutic peptides.

Various bioactive peptides in collagen hydrolysate from salmo salar skin and the combined inhibitory effects on atherosclerosis in vitro and in vivo.

Atherosclerosis (AS) is the underlying condition in most cardiovascular diseases, which is blood vessel inflammation participated by many factors. Collagen hydrolysate from salmo salar skin (SCH) obtained in this study showed strong anti-inflammatory activity, protection of endothelial cell injury, antioxidant activity, and anti-platelet aggregation activity in vitro, exhibiting a great potential of attenuating AS. In this study, multifunctional peptides FAGPPGGDGQPGAK and IAGPAGPRGPSGPA, which mainly showed strong anti-inflammatory activity, were identified from SCH after separation of ultrafiltration and column chromatography. Moreover, SCH (contained anti-platelet peptides and anti-inflammatory peptides) was observed to inhibit arterial intima thickening and plaques formation in apolipoprotein E-deficient (ApoE-/-) mice fed with high-fat diets without side effects, exhibiting a comparable effect with aspirin. SCH showed combined effect on regulating serum biomarkers of inflammation (IL-6 and TNF-α), endothelial injury (MCP-1), platelet activation (TXB2 and PF4) and oxidative stress (MDA and CAT). This research suggested SCH as a potential dietary supplement for the primary prevention of AS.

Peptide-Based Vaccines and Therapeutics for COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been prevalent in the humans since 2019 and has given rise to a pandemic situation. With the discovery and ongoing use of drugs and vaccines against SARS-CoV-2, there is still no surety of its complete suppression of this disease or if there is a need for additional booster doses. There is an urgent need for alternative treatment strategies against COVID-19. Peptides and peptidomimetics have several advantages as therapeutic agents because of their target selectivity, better interactions, and lower toxicity. Minor structural alterations to peptides can help prevent their fast metabolism and provide long-action. This comprehensive review provides an overview of different peptide-based vaccines and therapeutics against SARS-CoV-2. It discusses the design and mechanism of action of the peptide-based vaccines, peptide immunomodulators, anti-inflammatory agents, and peptides as entry inhibitors of SARS-CoV-2. Moreover, the mechanism of action, sequences and current clinical trial studies are also summarized. The review also discusses the future aspects of peptide-based vaccines and therapeutics for COVID-19.

Identification and virtual screening of novel anti-inflammatory peptides from broccoli fermented by Lactobacillus strains.

Lactobacillus strains fermentation of broccoli as a good source of bioactive peptides has not been fully elucidated. In this work, the peptide composition of broccoli fermented by L. plantarum A3 and L. rhamnosus ATCC7469 was analyzed by peptidomics to study the protein digestion patterns after fermentation by different strains. Results showed that water-soluble proteins such as rubisco were abundant sources of peptides, which triggered the sustained release of peptides as the main target of hydrolysis. In addition, 17 novel anti-inflammatory peptides were identified by virtual screening. Among them, SIWYGPDRP had the strongest ability to inhibit the release of NO from inflammatory cells at a concentration of 25 µM with an inhibition rate of 52.32 ± 1.48%. RFR and KASFAFAGL had the strongest inhibitory effects on the secretion of TNF-α and IL-6, respectively. At a concentration of 25 µM, the corresponding inhibition rates were 74.61 ± 1.68% and 29.84 ± 0.63%, respectively. Molecular docking results showed that 17 peptides formed hydrogen bonds and hydrophobic interactions with inducible nitric oxide synthase (iNOS). This study is conducive to the high-value utilization of broccoli and reduction of the antibiotic use.

iAIPs: Identifying Anti-Inflammatory Peptides Using Random Forest.

Recently, several anti-inflammatory peptides (AIPs) have been found in the process of the inflammatory response, and these peptides have been used to treat some inflammatory and autoimmune diseases. Therefore, identifying AIPs accurately from a given amino acid sequences is critical for the discovery of novel and efficient anti-inflammatory peptide-based therapeutics and the acceleration of their application in therapy. In this paper, a random forest-based model called iAIPs for identifying AIPs is proposed. First, the original samples were encoded with three feature extraction methods, including g-gap dipeptide composition (GDC), dipeptide deviation from the expected mean (DDE), and amino acid composition (AAC). Second, the optimal feature subset is generated by a two-step feature selection method, in which the feature is ranked by the analysis of variance (ANOVA) method, and the optimal feature subset is generated by the incremental feature selection strategy. Finally, the optimal feature subset is inputted into the random forest classifier, and the identification model is constructed. Experiment results showed that iAIPs achieved an AUC value of 0.822 on an independent test dataset, which indicated that our proposed model has better performance than the existing methods. Furthermore, the extraction of features for peptide sequences provides the basis for evolutionary analysis. The study of peptide identification is helpful to understand the diversity of species and analyze the evolutionary history of species.

Structural and posttranslational analysis of human calcium-binding protein, spermatid-associated 1.

Recently, we detected a novel biomarker in human saliva called calcium-binding protein, spermatid-associated 1 (CABS1). CABS1 protein had previously been described only in testis, and little was known of its characteristics other than it was considered a structurally disordered protein. Levels of human CABS1 (hCABS1) in saliva correlate with stress, whereas smaller sized forms of hCABS1 in saliva are associated with resilience to stress. Interestingly, hCABS1 also has an anti-inflammatory peptide sequence near its carboxyl terminus, similar to that of a rat prohormone, submandibular rat 1. We performed phylogenetic and sequence analysis of hCABS1. We found that from 72 CABS1 sequences currently annotated in the National Center for Biotechnology Information protein database, only 14 contain the anti-inflammatory domain "TxIFELL," all of which are primates. We performed structural unfoldability analysis using PONDER and FoldIndex and discovered three domains that are highly disordered. Predictions of three-dimensional structure of hCABS1 using RaptorX, IonCom, and I-TASSER software agreed with these findings. Predicted neutrophil elastase cleavage density also correlated with hCABS1 regions of high structural disorder. Ligand binding prediction identified Ca2+ , Mg2+ , Zn2+ , leucine, and thiamine pyrophosphate, a pattern observed in enzymes associated with energy metabolism and mitochondrial localization. These new observations on hCABS1 raise intriguing questions about the interconnection between the autonomic nervous system, stress, and the immune system. However, the precise molecular mechanisms involved in the complex biology of hCABS1 remain unclear. We provide a detailed in silico analysis of relevant aspects of the structure and function of hCABS1 and postulate extracellular and intracellular roles.

PreAIP: Computational Prediction of Anti-inflammatory Peptides by Integrating Multiple Complementary Features.

Numerous inflammatory diseases and autoimmune disorders by therapeutic peptides have received substantial consideration; however, the exploration of anti-inflammatory peptides via biological experiments is often a time-consuming and expensive task. The development of novel in silico predictors is desired to classify potential anti-inflammatory peptides prior to in vitro investigation. Herein, an accurate predictor, called PreAIP (Predictor of Anti-Inflammatory Peptides) was developed by integrating multiple complementary features. We systematically investigated different types of features including primary sequence, evolutionary and structural information through a random forest classifier. The final PreAIP model achieved an AUC value of 0.833 in the training dataset via 10-fold cross-validation test, which was better than that of existing models. Moreover, we assessed the performance of the PreAIP with an AUC value of 0.840 on a test dataset to demonstrate that the proposed method outperformed the two existing methods. These results indicated that the PreAIP is an accurate predictor for identifying AIPs and contributes to the development of AIPs therapeutics and biomedical research. The curated datasets and the PreAIP are freely available at http://kurata14.bio.kyutech.ac.jp/PreAIP/.

Recent Progress in Machine Learning-based Prediction of Peptide Activity for Drug Discovery.

Over the past decades, peptide as a therapeutic candidate has received increasing attention in drug discovery, especially for antimicrobial peptides (AMPs), anticancer peptides (ACPs) and antiinflammatory peptides (AIPs). It is considered that the peptides can regulate various complex diseases which are previously untouchable. In recent years, the critical problem of antimicrobial resistance drives the pharmaceutical industry to look for new therapeutic agents. Compared to organic small drugs, peptide- based therapy exhibits high specificity and minimal toxicity. Thus, peptides are widely recruited in the design and discovery of new potent drugs. Currently, large-scale screening of peptide activity with traditional approaches is costly, time-consuming and labor-intensive. Hence, in silico methods, mainly machine learning approaches, for their accuracy and effectiveness, have been introduced to predict the peptide activity. In this review, we document the recent progress in machine learning-based prediction of peptides which will be of great benefit to the discovery of potential active AMPs, ACPs and AIPs.

Engineering of an Anti-Inflammatory Peptide Based on the Disulfide-Rich Linaclotide Scaffold.

Inflammatory bowel diseases are a set of complex and debilitating diseases, for which there is no satisfactory treatment. Peptides as small as three amino acids have been shown to have anti-inflammatory activity in mouse models of colitis, but they are likely to be unstable, limiting their development as drug leads. Here, we have grafted a tripeptide from the annexin A1 protein into linaclotide, a 14-amino-acid peptide with three disulfide bonds, which is currently in clinical use for patients with chronic constipation or irritable bowel syndrome. This engineered disulfide-rich peptide maintained the overall fold of the original synthetic guanylate cyclase C agonist peptide, and reduced inflammation in a mouse model of acute colitis. This is the first study to show that this disulfide-rich peptide can be used as a scaffold to confer a new bioactivity.

Peptides as Therapeutic Agents for Inflammatory-Related Diseases.

Inflammation is a physiological mechanism used by organisms to defend themselves against infection, restoring homeostasis in damaged tissues. It represents the starting point of several chronic diseases such as asthma, skin disorders, cancer, cardiovascular syndrome, arthritis, and neurological diseases. An increasing number of studies highlight the over-expression of inflammatory molecules such as oxidants, cytokines, chemokines, matrix metalloproteinases, and transcription factors into damaged tissues. The treatment of inflammatory disorders is usually linked to the use of unspecific small molecule drugs that can cause undesired side effects. Recently, many efforts are directed to develop alternative and more selective anti-inflammatory therapies, several of them imply the use of peptides. Indeed, peptides demonstrated as elected lead compounds toward several targets for their high specificity as well as recent and innovative synthetic strategies. Several endogenous peptides identified during inflammatory responses showed anti-inflammatory activities by inhibiting, reducing, and/or modulating the expression and activity of mediators. This review aims to discuss the potentialities and therapeutic use of peptides as anti-inflammatory agents in the treatment of different inflammation-related diseases and to explore the importance of peptide-based therapies.