Therapeutic Peptides Research Articles

Stabilizing Scaffold for Short Peptides Based on Knottins.

Bombesin (BBN) is a short peptide with a high affinity for receptors that are expressed on the surface of various types of cancer cells. However, a full length BBN molecule has low in vivo stability. In our study, we propose the use of peptide toxins, derived from animal and plant toxins, as scaffold molecules to enhance the bioavailability and stability of bombesin. These peptides possess a unique structure known as an inhibitory cystine knot. We synthesized structures in which short bombesin was incorporated into various domains of arthropod and plant toxins using solid-phase peptide synthesis. The stability under different conditions was assessed through high-performance liquid chromatography, and binding to cell cultures expressing the bombesin receptor was analyzed. Additionally, toxicity to cell cultures was evaluated using fluorescence microscopy. The data obtained demonstrated that placing the short peptide between the first and second cysteine residues in arachnid toxins results in increased in vitro stability and bioavailability, as well as low cytotoxicity. Arachnid toxins with an inhibitory cystine knot can be considered as a scaffold for increasing the stability of therapeutic peptides.

Recommendation for Clarifying FDA Policy in Evaluating "Sameness" of Higher Order Structure for Generic Peptide Therapeutics.

Recognizing the approach of a dramatic expansion of peptide therapeutics reaching the marketplace in recent years, led by GLP-1 receptor agonists such as semaglutide and liraglutide, the Center for Drug Evaluation and Research (CDER) branch of the US Food and Drug Administration (FDA) issued a final guidance in 2021 that was intended to assist generic drug producers in meeting Abbreviated New Drug Application (ANDA) obligations to establish "sameness" of their active peptide drug relative to that produced by innovator companies. Research and a published report by FDA scientists on best practices followed, which promulgated the use of nuclear magnetic resonance (NMR) and principal component analysis (PCA) and established a quantitative standard by which "sameness" of higher order structure for the applicant's peptide drug could be judged. A key requirement is that drug product samples be analyzed directly and non-invasively, a condition which in practice restricts sample modification to the addition of a small amount of deuterium oxide to allow signal lock and spectral data alignment (as required for NMR analysis). In the study described herein, data are presented to illustrate that 1) relatively small differences in sample pH can cause significant shifting of certain proton resonances, 2) that such resonance shifting is readily reversible and due to the degree of protonation of specific amino acid residues (rather than reflecting differences in higher order structure), and 3) that small differences in pH variability between sample cohorts can frequently cause failure to meet the quantitative benchmark established by the agency. Methodology is presented by which drug sample pHs can be aligned with minimal impact, and a recommendation is made that minor sample pH adjustments be allowed in assessing "sameness" of peptide drug higher order structure.

IMFP-LG: Identification of Novel Multi-Functional Peptides by Using Protein Language Models and Graph-Based Deep Learning.

Functional peptides are short amino acid fragments that have a wide range of beneficial functions for living organisms. The majority of previous research focused on mono-functional peptides, but a growing number of multi-functional peptides have been discovered. Although there have been enormous experimental efforts to assay multi-functional peptides, only a small fraction of millions of known peptides have been explored. Effective and precise techniques for identifying multi-functional peptides can facilitate their discovery and mechanistic understanding. In this article, we presented a method iMFP-LG for identifying multi-functional peptides based on protein language models (pLMs) and graph attention networks (GATs). Comparison results showed that iMFP-LG outperforms state-of-the-art methods on both multi-functional bioactive peptides and multi-functional therapeutic peptides datasets. The interpretability of iMFP-LG was also illustrated by visualizing attention patterns in pLMs and GATs. Regarding the outstanding performance of iMFP-LG on the identification of multi-functional peptides, we employed iMFP-LG to screen novel candidate peptides with both ACP and AMP functions from millions of known peptides in the UniRef90. As a result, 8 candidate peptides were identified, and 1 candidate that exhibits both antibacterial and anticancer effects was confirmed through molecular structure alignment and biological experiments. We anticipate that iMFP-LG can assist in the discovery of multi-functional peptides and contribute to the advancement of peptide drug design.

Rapid prediction of key residues for foldability by machine learning model enables the design of highly functional libraries with hyperstable constrained peptide scaffolds.

Peptides are an emerging modality for developing therapeutics that can either agonize or antagonize cellular pathways associated with disease, yet peptides often suffer from poor chemical and physical stability, which limits their potential. However, naturally occurring disulfide-constrained peptides (DCPs) and de novo designed Hyperstable Constrained Peptides (HCPs) exhibiting highly stable and drug-like scaffolds, making them attractive therapeutic modalities. Previously, we established a robust platform for discovering peptide therapeutics by utilizing multiple DCPs as scaffolds. However, we realized that those libraries could be further improved by considering the foldability of peptide scaffolds for library design. We hypothesized that specific sequence patterns within the peptide scaffolds played a crucial role in spontaneous folding into a stable topology, and thus, these sequences should not be subject to randomization in the original library design. Therefore, we developed a method for designing highly diverse DCP libraries while preserving the inherent foldability of each scaffold. To achieve this, we first generated a large-scale dataset from yeast surface display (YSD) combined with shotgun alanine scan experiments to train a machine-learning (ML) model based on techniques used for natural language understanding. Then we validated the ML model with experiments, showing that it is able to not only predict the foldability of peptides with high accuracy across a broad range of sequences but also pinpoint residues critical for foldability. Using the insights gained from the alanine scanning experiment as well as prediction model, we designed a new peptide library based on a de novo-designed HCP, which was optimized for enhanced folding efficiency. Subsequent panning trials using this library yielded promising hits having good folding properties. In summary, this work advances peptide or small protein domain library design practices. These findings could pave the way for the efficient development of peptide-based therapeutics in the future.

IAmyP: A Multi-view Learning for Amyloidogenic Hexapeptides Identification Based on Sequence Least Squares Programming.

The development of peptide drug is hindered by the risk of amyloidogenic aggregation; if peptides tend to aggregate in this manner, they may be unsuitable for drug design. Computational methods aimed at predicting amyloidogenic sequences often face challenges in extracting high-quality features, and their predictive performance can be enchanced. To surmount these challenges, iAmyP was introduced as a specialized computational tool designed for predicting amyloidogenic hexapeptides. Utilizing multi-view learning, iAmyP incorporated sequence, structural, and evolutionary features, performing feature selection and feature fusion through recursive feature elimination and attention mechanisms. This amalgamation of features and subsequent feature selection and fusion lead to optimal performance facilitated by an optimization algorithm based on sequence least squares programming. Notably, iAmyP exhibited robust generalization for peptides with lengths of 7-10 amino acids. The role of hydrophobic amino acids in the aggregation process is critical, and a thorough analysis have significantly enhanced our insight into their significance in amyloidogenic hexapeptides. This tool represented an advancement in the development of peptide therapeutics by providing an understanding of amyloidogenic aggregation, establishing itself as a valuable framework for assessing amyloidogenic sequences. The data and code can be freely accessed at https://github.com/xialab-ahu/iAmyP .

Analysis and Prediction of Chymotrypsin Substrate Preferences through Large Data Acquisition with Target-Free mRNA Display.

Oral delivery of peptide therapeutics is limited by degradation by gut proteases like chymotrypsin. Existing databases of peptidases are limited in size and do not enable systematic analyses of protease substrate preferences, especially for non-natural amino acids. Thus, stability optimization of hit compounds is time and resource intensive. To accelerate the stability optimization of peptide ligands, we generated large datasets of chymotrypsin-resistant peptides via mRNA display to create a predictive model for chymotrypsin-resistant sequences. Through analysis of enriched motifs, we recapitulate known chymotrypsin cleavage sites, reveal positionally dependent effects of monomers on peptide cleavage, and report previously unidentified protective and destabilizing residues. We then developed a machine-learning-based modelpredicting peptide resistance to chymotrypsin cleavage and validated both model performance and the NGS experimental data by measuring chymotrypsin half-lives for a subset of peptides. Finally, we simulated stability predictions on non-natural amino acids through a leucine hold-out model and observed robust performance. Overall, we demonstrate the utility of mRNA display as a tool for big data generation and show that pairing mRNA display with machine learning yields valuable predictions for chymotrypsin cleavage. Expansion of this workflow to additional proteases could provide complementary predictive models that focus future peptide drug discovery efforts.

Oxytocin Analogues for the Oral Treatment of Abdominal Pain.

Abdominal pain presents an onerous reality for millions of people affected by gastrointestinal disorders such as irritable bowel syndrome (IBS) and inflammatory bowel diseases (IBD). The oxytocin receptor (OTR) has emerged as a new analgesic drug target with OTR expression upregulated on colon-innervating nociceptors in chronic visceral hypersensitivity states, accessible via luminal delivery. However, the low gastrointestinal stability of OTR's endogenous peptide ligand oxytocin (OT) is a bottleneck for therapeutic development. Here, we report the development of potent and fully gut-stable OT analogues, laying the foundation for a new area of oral gut-specific peptide therapeutics. Ligand optimisation guided by structure-gut-stability-activity relationships yielded highly stable analogues (t1/2>24 h, compared to t1/2<10 min of OT in intestinal fluid) equipotent to OT (~3 nM) and with enhanced OTR selectivity. Intra-colonic administration of the lead ligand significantly reduced colonic mechanical hypersensitivity in a concentration-dependent manner in a mouse model of chronic abdominal pain. Moreover, oral administration of the lead ligand also displayed significant analgesia in this abdominal pain mouse model. The generated ligands and employed strategies could pave the way to a new class of oral gut-specific peptides to study and combat chronic gastrointestinal disorders, an area with substantial unmet medical needs.

Therapeutic Peptides Encapsulated into Lipid-Based Nanovesicles: Scaling from Lab to Plant

Lipid-based peptide-encapsulated nanovesicles represent a cutting-edge approach in drug delivery systems, offering enhanced stability, targeted delivery, and controlled release of therapeutic peptides. This review explores the comprehensive science and techniques behind the robust formulation and analytical methods for these nanovesicles, spanning from lab-scale research to large- scale manufacturing. Critical aspects include lipid selection, detailing how the choice of lipids impacts the stability and efficacy of the nanovesicles, and various peptide encapsulation techniques, emphasizing methods to achieve high encapsulation efficiency and controlled release. Key processes in vesicle formation, such as thin film hydration, sonication, and microfluidics, are discussed to highlight their roles in producing nanovesicles with consistent size and morphology. The importance of stability studies, including physical, chemical, and thermal assessments, is underscored. Analytical techniques such as Dynamic Light Scattering (DLS), Zeta Potential measurement, High-Performance Liquid Chromatography (HPLC), and Mass Spectrometry (MS) are detailed, showcasing their crucial roles in characterizing nanovesicles and ensuring their quality, safety, and efficacy for pharmaceutical use. The review addresses the challenges and solutions associated with scaling up production, including maintaining consistent product quality, optimizing manufacturing processes, and controlling production costs. It also navigates the regulatory landscape, discussing the stringent guidelines set by agencies such as the FDA and EMA and the necessity of strategic regulatory planning to facilitate market approval. This comprehensive review aims to serve as an in-depth resource for experts in the field, aiding in the translation of lipid-based peptide-encapsulated nanovesicle formulations from bench to bedside, ultimately enhancing therapeutic outcomes and expanding treatment options for various disease. Key Words: Peptide, Amino acid, Degradation, Pharmacokinetics, Peptide encapsulation, drug delivery systems, Peptide Characterization

FGL2172-220 peptides improve the antitumor effect of HCMV-IE1mut vaccine against glioblastoma by modulating immunosuppressive cells in the tumor microenvironment

ABSTRACT Glioblastoma multiforme (GBM) is a highly aggressive primary brain tumor characterized by poor prognosis and lack of effective treatments. In recent years, peptide vaccines that use sequences based on tumor-specific or tumor-associated antigens to activate immune responses against tumor cells have emerged as a new therapeutic strategy. In this study, we developed a novel therapeutic polypeptide vaccine targeting the tumor-associated antigen Fibrinogen-Like Protein 2 (FGL2), whose dominant epitope peptide was tandemly linked to the C-terminus of HCMV-IE1mut via a linker. We used this vaccine to compare the therapeutic efficacy of HCMV-IE1mut alone versus HCMV-IE1mut-FGL2172-220 and investigate the potential mechanism of action of HCMV-IE1mut-FGL2172-220 in glioma treatment. An in situ GBM model (GL261-IE1-luc cells) was used to determine the efficacy of the vaccine. Treatment with HCMV-IE1mut-FGL2172-220 exerted antitumor effects and extended the survival of the GL261 animal model. We observed reduced proportions of microglia, regulatory T cells (Treg), and myeloid-derived suppressor cells (MDSC) in the tumor microenvironment (TME) by immunofluorescence. Flow cytometry showed that compared to HCMV-IE1mut alone, treatment with HCMV-IE1mut-FGL2172-220 increased the proportion of CD8+ T cells and tissue-resident memory T cells (TRM). ELISA analysis showed that it improved the secretion of tumor-specific IFN-γ and TNF-α by these cells and downregulated the expression of IL-6 and IL-10. Our study demonstrates that the long-peptide FGL2172-220 improves the antitumor efficacy of HCMV-IE1mut, possibly by reshaping immune cells in the glioma microenvironment. These findings lay the groundwork for the development of therapeutic antigenic peptide vaccines to improve antitumor effects for cancer.

Bone-Targeted Fluoropeptide Nanoparticle Inhibits NF-κB Signaling to Treat Osteosarcoma and Tumor-Induced Bone Destruction.

Osteosarcoma is a malignant bone cancer usually characterized by symptoms of bone loss due to pathologically enhanced osteoclast activity. Activated osteoclasts enhance bone resorption and promote osteosarcoma cell progression by secreting various cytokines. Intercepting the detrimental interplay between osteoclasts and osteosarcoma cells is considered as an option for osteosarcoma treatment. Here, a bone-targeted fluoropeptide nanoparticle that can inhibit the nuclear factor kappa B (NF-κB) signaling in both osteoclasts and osteosarcoma to address the above issue is developed. The NF-κB essential modulator binding domain (NBD) peptide is conjugated with a fluorous tag to improve its proteolytic stability and intracellular penetration. The NBD peptide is efficiently delivered into cells after fluorination to induce apoptosis of osteocarcoma cells, and inhibits osteoclasts differentiation. The fluorous-tagged NBD peptide is further co-assembled with an oligo (aspartic acid) terminated fluoropeptide to form bone-targeted peptide nanoparticles for osteosarcoma treatment. The targeted nanoparticles efficiently inhibited tumor progression and osteosarcoma-induced bone destruction in vivo. This co-assembled fluoropeptide nanoplatform proposed in this study offers a promising approach for targeted and intracellular delivery of peptide therapeutics in the treatment of various diseases.

Neo-Glycolipid Oximes as Intestinal Permeation Enhancers for Peptide Hormone PYY3-36.

Herein, we describe the design and synthesis of 16 neo-glycolipids that are potential permeation enhancers for oral drug delivery of peptide therapeutics. These amphiphilic neo-glycolipids are composed of fatty acids and various carbohydrates (D-glucose, lactose, cellobiose, maltose) via an oxime linker. The ability of the synthesized neo-glycolipids to enhance permeation of fluorescein-labelled dextran (4 kDa) or 3H-mannitol across intestinal epithelium was investigated in vitro using monolayers of human epithelial Caco-2 cells. Their effects were compared with (pre-)clinically known enhancers as reference compounds; sodium salts of octanoic, decanoic, and dodecanoic acid, and sodium salcaprozate (SNAC). Most neo-glycolipids increased the permeation of the model compounds, proving that neo-glycolipids, which possess vastly different properties from the reference compounds, e.g., in terms of clogD and polar surface area, are effective permeation enhancers. The neo-glycolipid based on decanoic acid and glucose was more potent than related compounds based on disaccharides. Significant differences in solubility and cellular compatibility were found for neo-glyolipids based on different carbohydrates. Finally, neo-glycolipids were evaluated as permeation enhancers for the peptide hormone PYY3-36. Glucose- and maltose-derived neo-glycolipids based on decanoic and dodecanoic acid showed promising enhancements in PYY3-36 permeation while maintaining good cellular compatibility, relevant for oral delivery of obesity treatments.

Feasibility of a direct binding electrochemiluminescence assay to detect anti-drug antibodies against therapeutic peptides

Feasibility of a direct binding electrochemiluminescence assay to detect anti-drug antibodies against therapeutic peptides

Peptides as Targeting Agents and Therapeutics: A Brief Overview.

The controllability and specificity of peptides make them ideal for targeting therapeutic delivery systems and as therapeutic agents that interfere with the essential functions of pathogens and tumors. Peptides can also mimic natural protein structures or parts thereof, agonize receptors, and be conjugated to other molecules that will self-assemble. In this short Review, we discuss research from the last ten years into peptide use in three arenas: the treatment of cancer, the treatment of pathogens, and the targeting of specific organs and organelles. These studies demonstrate the successful application of targeting and therapeutic peptides in vitro and in vivo and show the promising range of applications peptides can have going forward.

310-Helix stabilization and screw sense control via stereochemically configured 4-atom hydrocarbon staples

The 310-helix is a crucial secondary structure in proteins, playing an essential role in various protein–protein interactions, yet stabilizing it in biologically relevant peptides remains challenging. In this study, we investigated the potential of 4-atom hydrocarbon staples to stabilize 310-helices in peptides. Using ring-closing metathesis, we demonstrated that the staple’s configuration is critical for both the stabilization and screw sense control of 310-helices. Circular dichroism spectroscopy revealed that the Ri,i+3S(4) staple—a 4-atom cross-link with (R)-configuration at the i position, (S)-configuration at the i + 3 position, and flanked by methyl groups—strongly induces right-handed 310-helices, especially in sequences with proteinogenic l-amino acids. Furthermore, multiple staples effectively stabilized longer peptides, underscoring the versatility of this approach for applications in peptide therapeutics and biomolecular engineering.

TPpred-SC: multi-functional therapeutic peptide prediction based on multi-label supervised contrastive learning

TPpred-SC: multi-functional therapeutic peptide prediction based on multi-label supervised contrastive learning

Chitosan-melanin complex microsphere: A potential colonic delivery system for protein drugs

The characteristics and performance of chitosan-based colon delivery systems are significantly influenced by the method of preparation. Insect chitosan-melanin complex (CMC) may offer superior attributes over traditional shrimp and crab chitosan (CS) for colon-targeted administration. This study used dung beetle CMC as the carrier matrix and comprehensively examined the impact of various crosslinking techniques on the colonic drug delivery efficacy of microspheres, encompassing drug loading, swelling, drug release behavior, adhesion, enzymatic degradation, and absorption enhancement. The results indicate that F-TPPLC microspheres, crosslinked with a combination of formaldehyde and sodium tripolyphosphate, exhibit superior drug loading capabilities, optimal swelling behavior, and controlled in vitro drug release profiles in the colonic environment, along with excellent adhesion and enzymatic degradation properties within intestinal tract. Notably, these F-TPPLC microspheres increase paracellular permeability, possibly by disrupting the calcium-dependent adhesion junctions. In comparison to commercial CS, CMC demonstrates superior drug encapsulation efficiency, enhanced colonic drug release, adhesion, and absorption promotion, rendering it a favorable candidate as a carrier in colon-targeted drug delivery systems. Consequently, F-TPPLC microspheres derived from CMC are highly suitable for colon drug delivery applications and show promising potential for the oral delivery of peptide and protein-based therapeutics to the colon.

Evolutionary Sequences and Structural Information-driven Reconstruction of New Insulin-like Growth Factor-I Peptide Variants.

Insulin-like growth factor-I (IGF-I) is crucial in controlling cell growth, proliferation, and apoptosis. Its strong link to the development of cancers such as breast, prostate, lung, thyroid, and colorectal has positioned the IGF-1 signalling pathway as a promising target for novel cancer therapies. When activated, the IGF-1 receptor (IGF-1R) binds to IGF-I, playing a central role in promoting tumour cell growth and survival. In this study, we combined evolutionary sequences with structural and functional data of IGF-1 to reconstruct ancestral sequences and design novel IGF-1 peptide variants. The insulin-like growth factor system exhibits a vast sequence diversity, yet it shares a similar structural topology with conserved three pairs of disulfide linkages. Our study reveals that IGF-1 is associated with the IGF system of cell surface receptors through protein-protein interactions. Reconstructed IGF-1 variants show similar structure fold to reported viral IGF-1 competitive antagonists. This new insight guides the design of novel natural IGF-1 mimic peptides. It enhances our understanding of IGF-1's functionality and opens new avenues for the development of therapeutic peptides and small molecules as anticancer agents.

Strategies for transportation of peptides across the skin for treatment of multiple diseases.

An established view in genetic engineering dictates an increase in the discovery of therapeutic peptides to enable the treatment of multiple diseases. The use of hypodermic needle for delivery of proteins and peptides occurs due to the hydrophilic nature, sensitivity toward proteolytic enzymes and high molecular weight. The non-invasive nature of the transdermal delivery technique offers multiple advantages over the invasive route to release drugs directly into the systemic circulation to enhance bioavailability, better patient compliance, reduced toxicity and local irritability. The transdermal route seems highly desirable from the pharmaco-therapeutic and patient compliance point of view, however, the lipophilic barrier of skin restricts the application. The use of several techniques like electrical methods (iontophoresis, sonophoresis etc.), chemical penetration enhancers (e.g. protease inhibitors, penetration enhancers, etc.) and nanocarriers (dendrimers, lipid nanocapsules, etc.) are utilized to improve the passage of drug molecules across the biomembranes. Additionally, such clinical interventions facilitate the physicochemical characteristics of peptides, to enable effective preservation, conveyance and release of therapeutic agents. Moreover, strategies ensure the attainment of the intended targets and enhance treatment outcomes for multiple diseases. This review article focuses on the techniques of peptide transportation across the skin to advance the delivery approaches and therapeutic efficiency.

Future Perspective: Harnessing the Power of Artificial Intelligence in the Generation of New Peptide Drugs

The expansive field of drug discovery is continually seeking innovative approaches to identify and develop novel peptide-based therapeutics. With the advent of artificial intelligence (AI), there has been a transformative shift in the generation of new peptide drugs. AI offers a range of computational tools and algorithms that enables researchers to accelerate the therapeutic peptide pipeline. This review explores the current landscape of AI applications in peptide drug discovery, highlighting its potential, challenges, and ethical considerations. Additionally, it presents case studies and future prospectives that demonstrate the impact of AI on the generation of new peptide drugs.

Comparison of Protocols to Test Peptide Stability in Blood Plasma and Cell Culture Supernatants.

Due to their high specificity, peptides are promising candidates in drug development, but fast degradation often limits their biological activity. Thus, a short half-life is one of the major challenges in the development of new peptide therapeutics. Moreover, the enzymatic cleavage of peptides can be a reason for misleading results in biological assays. Peptide stability assays typically consist of incubation, precipitation, and detection steps. However, the current methods differ greatly regarding these three steps, thus limiting the compatibility. Here, we systematically evaluate different parameters of peptide stability assays. First, we quantified and compared the analyte loss during the precipitation of plasma proteins. Especially, broadly used precipitation by strong acids was found to be unsuitable, while mixtures of organic solvents preserved more peptides for further analysis. Next, the stability of four fluorescently labeled model peptides was analyzed in blood plasma and two different cell culture supernatants. Strong variation in the degradation dynamics and patterns was found. Finally, we evaluated the role of fluorescent labeling on peptide stability and compared results to peptides with isotopic labels, underlining the individual advantages of both methods. Altogether, the data provide important parameters for analyzing and comparing the peptide stability.