Peptide Drugs Research Articles

Peptide Drugs: Current Status and it's Applications in the Treatment of Various Diseases.

Peptides represent a class of natural molecules with diverse physiological functions, including hormone regulation, neurotransmission, and immune modulation. In recent years, peptide- based therapeutics have gained significant attention in pharmaceutical research and development due to their high specificity, efficacy, and relatively low toxicity. This review provides an overview of the current landscape of peptide drug development, highlighting the challenges faced in their formulation and delivery and the innovative strategies employed to overcome these hurdles. The review explores the wide range of applications of peptide drugs in treating various diseases, including HIV, multiple sclerosis, osteoporosis, chronic pain, diabetes, and cancer. Examples of FDA-approved peptide drugs and ongoing clinical trials are presented, showcasing the continuous advancements in peptide-based therapeutics across different therapeutic areas. This review underscores the promising potential of peptide drugs as targeted and effective treatments for a multitude of medical conditions, offering improved therapeutic outcomes and enhanced patient care.

Mechanistic Insight into the Role of Peptides Secreted from Bacillus clausii and Future Opportunities.

Bacillus clausii is a commercial spore probiotic known to treat multiple diseases. An increased interest in exploring the nutraceutical and probiotic properties of various microorganisms has made researchers explore more about these bacteria. The current trends in the healthcare industry are majorly focused on devising new therapies to avoid drug and pathogen resistance in patients. Antimicrobial peptides have been considered a source of antibiotics for a long time. Still, getting new therapies into the market is a big challenge. Members of the genus Bacillus have been reported to have a broad spectrum of antimicrobial peptides. One of the least explored species under this genus is Bacillus clausii, concerning peptide drug therapy. The applications of Bacillus clausii in treating or preventing gut dysbiosis and respiratory infections have been largely supported in the past two decades. Yet research is lacking in explaining the pathways at molecular levels in targeting pathogens. In this mini-review, we are going to summarise the research that has been reported so far about peptide extraction from Bacillus clausii, their mode of action and advantages to mankind, and the challenges lying in the isolation of peptides.

Discovery of Highly Bioactive Peptides through Hierarchical Structural Information and Molecular Dynamics Simulations.

Peptide drugs play an essential role in modern therapeutics, but the computational design of these molecules is hindered by several challenges. Traditional methods like molecular docking and molecular dynamics (MD) simulation, as well as recent deep learning approaches, often face limitations related to computational resource demands, complex binding affinity assessments, extensive data requirements, and poor model interpretability. Here, we introduce PepHiRe, an innovative methodology that utilizes the hierarchical structural information in peptide sequences and employs a novel strategy called Ladderpath, rooted in algorithmic information theory, to rapidly generate and enhance the efficiency and clarity of novel peptide design. We applied PepHiRe to develop BH3-like peptide inhibitors targeting myeloid cell leukemia-1, a protein associated with various cancers. By analyzing just eight known bioactive BH3 peptide sequences, PepHiRe effectively derived a hierarchy of subsequences used to create new BH3-like peptides. These peptides underwent screening through MD simulations, leading to the selection of five candidates for synthesis and subsequent in vitro testing. Experimental results demonstrated that these five peptides possess high inhibitory activity, with IC50 values ranging from 28.13 ± 7.93 to 167.42 ± 22.15 nM. Our study explores a white-box model driven technique and a structured screening pipeline for identifying and generating novel peptides with potential bioactivity.

Palladium(II)-Catalyzed Site-Selective C(sp3)-H Alkenylation of Oligopeptides.

An innovative palladium-catalyzed alkenylation of peptides and vinyl iodides has been developed. This method does not require the introduction of a directing group and uses carboxylic acid groups as endogenous directing groups. It is noteworthy that two key building blocks for the ilamycins and CXCR7 modulators were prepared using our methodology. In addition, the free carboxylic acid residue can be linked to a variety of other compounds, providing a novel approach to the synthesis of peptide drugs in the future.

Research Progress on Peptide Drugs for Type 2 Diabetes and the Possibility of Oral Administration

Diabetes is a global disease that can lead to a range of complications. Currently, the treatment of type 2 diabetes focuses on oral hypoglycemic drugs and insulin analogues. Studies have shown that drugs such as oral metformin are useful in the treatment of diabetes but can limit the liver’s ability to release sugar. The development of glucose-lowering peptides has provided new options for the treatment of type 2 diabetes. Peptide drugs have low oral utilization due to their easy degradation, short half-life, and difficulty passing through the intestinal mucosa. Therefore, improving the oral utilization of peptide drugs remains an urgent problem. This paper reviews the research progress of peptide drugs in the treatment of diabetes mellitus and proposes that different types of nano-formulation carriers, such as liposomes, self-emulsifying drug delivery systems, and polymer particles, should be combined with peptide drugs for oral administration to improve their absorption in the gastrointestinal tract.

Structure-Activity Relationships and Target Selectivity of Phenylsulfonylamino-Benzanilide Inhibitors Based on S1647 at the SLC10 Carriers ASBT, NTCP, and SOAT.

The intestinal bile acid carrier ASBT (SLC10A2), the hepatic bile acid carrier NTCP (SLC10A1), and the steroid sulfate carrier SOAT (SLC10A6), all members of the solute carrier family SLC10, are established drug targets. The ASBT inhibitors odevixibat, maralixibat, and elobixibat are used to treat intrahepatic cholestasis, cholestatic pruritus, and obstipation. The peptide drug bulevirtide blocks binding of the hepatitis B and D viruses to NTCP and thereby inhibits the virus's entry into hepatocytes. Experimental SOAT inhibitors have antiproliferative effects on hormone-dependent breast cancer cells. The phenylsulfonylamino-benzanilide S1647 is an inhibitor of ASBT and SOAT. The present study aimed to comparatively analyze a set of newly synthesized and commercially available S1647 derivatives for their transport inhibition against ASBT, NTCP, and SOAT. Structure-activity relationships were systematically analyzed regarding potency and target specificity to elucidate whether this compound class is worth being further developed in preclinical studies for pharmacological ASBT, NTCP, and/or SOAT inhibition.

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.

Intersecting Peptidomics and Bioactive Peptides in Drug Therapeutics

Abstract: Peptidomics is the study of total peptides that describe the functions, structures, and interactions of peptides within living organisms. It comprises bioactive peptides derived naturally or synthetically designed that exhibit various therapeutic properties against microbial infections, cancer progression, inflammation, etc. With the current state of the art, Bioinformatics tools and techniques help analyse large peptidomics data and predict peptide structure and functions. It also aids in designing peptides with enhanced stability and efficacy. Peptidomics studies are gaining importance in therapeutics as they offer increased target specificity with the least side effects. The molecular size and flexibility of peptides make them a potential drug candidate for designing protein-protein interaction inhibitors. These features increased their drug potency with the considerable increase in the number of peptide drugs available in the market for various health commodities. The present review extensively analyses the peptidomics field, focusing on different bioactive peptides and therapeutics, such as anticancer peptide drugs. Further, the review provides comprehensive information on in silico tools available for peptide research. The importance of personalised peptide medicines in disease therapy is discussed along with the case study. Further, the major limitations of peptide drugs and the different strategies to overcome those limitations are reviewed.

Navigating a 1E+60 Chemical Space of Peptide/Peptoid Oligomers.

Herein we report a virtual library of 1E+60 members, a common estimate for the size of the drug-like chemical space. The library consists of linear or cyclic oligomers forming molecules within the size range of peptide drugs. We demonstrate ligand-based virtual screening using a genetic algorithm.

DsAMP and dsAMPGAN: Deep Learning Networks for Antimicrobial Peptides Recognition and Generation.

Antibiotic resistance is a growing public health challenge. Antimicrobial peptides (AMPs) effectively target microorganisms through non-specific mechanisms, limiting their ability to develop resistance. Therefore, the prediction and design of new AMPs is crucial. Recently, deep learning has spurred interest in computational approaches to peptide drug discovery. This study presents a novel deep learning framework for AMP classification, function prediction, and generation. We developed discoverAMP (dsAMP), a robust AMP predictor using CNN Attention BiLSTM and transfer learning, which outperforms existing classifiers. In addition, dsAMPGAN, a Generative Adversarial Network (GAN)-based model, generates new AMP candidates. Our results demonstrate the superior performance of dsAMP in terms of sensitivity, specificity, Matthew correlation coefficient, accuracy, precision, F1 score, and area under the ROC curve, achieving >95% classification accuracy with transfer learning on a small dataset. Furthermore, dsAMPGAN successfully synthesizes AMPs similar to natural ones, as confirmed by comparisons of physical and chemical properties. This model serves as a reliable tool for the identification of novel AMPs in clinical settings and supports the development of AMPs to effectively combat antibiotic resistance.

New options for treatment of chronic pain syndrome

According to the World Health Organization, 12.6 million new cases of cancer were identified in 2008. In 2022, this number reached 18.1 million cases, and it is projected to increase to 26 million in 2040. Chronic pain is defined by the International Association for the Study of Pain as pain that persists or recurs for 3 months. A similar definition is given in the International Classification of Diseases, 11th revision, which for the first time includes chronic pain as an independent category with a unique code MG30. The incidence of pain syndrome in advanced terminal or metastatic stages of cancer is 64 %, during antitumor therapy – 59 %, after successful treatment – 33 %. However, side effects from opioids significantly worsen the quality of life of patients.A new type of peptide drugs can reduce the toxic effects of drug pain therapy.

Characterization of Macrocyclic Peptide Drug Interactions with Bile Salts and Biorelevant Colloids via Single Amino Acid Mutations and 1H Nuclear Magnetic Resonance (NMR) Spectroscopy

There is growing interest in the oral delivery of poorly permeable peptide drugs; however, the effect of biorelevant colloids found in the aqueous gastrointestinal environment on peptide drug solution behavior has been largely understudied. In this work, we detail the molecular level interactions between octreotide, a water-soluble macrocyclic peptide drug, and biorelevant colloids, i.e. bile salt micelles and bile salt-phospholipid mixed micelles, via dialysis membrane flux experiments and proton nuclear magnetic resonance (1H NMR) spectroscopy. A modified alanine scan was employed to generate eight mutated octreotide analogs; the impact of individual amino acid mutations on peptide dialysis membrane flux rates in micellar (trihydroxy and dihydroxy) bile salt solutions as well as fasted state simulated intestinal fluid (FaSSIF) and fed state simulated intestinal fluid (FeSSIF) was evaluated and compared against the parent peptide, octreotide. We show that octreotide interacts more strongly with dihydroxy bile salt micelles than trihydroxy bile salt micelles in solution, and in FaSSIF/FeSSIF media, octreotide mainly interacts with the phospholipid component. These interactions are largely mediated by hydrophobic interactions of octreotide's aromatic residues as well as electrostatic interactions between octreotide's basic Lys residue and terminal amine.

Exploring novel antioxidant cyclic peptides in corn protein hydrolysate: Preparation, identification and molecular docking analysis

Antioxidant cyclic peptides were successfully identified from a corn protein hydrolysate. Hydrolysate by Alcalase + Flavourzyme showed the highest cyclic peptide purity (48.36 ± 1.81 %) and higher antioxidant activities compared with other hydrolysate. The success of peptide cyclization in hydrolysate was demonstrated by thermogravimetric analysis and thin-layer chromatography (TLC) analysis. Thermogravimetric analysis showed that the thermal stability of hydrolysate after cyclization was significantly increased, which was related to the formation of cyclic peptides. Peptides with molecular weight less than 1000 Da accounted for more than 80 % in hydrolysate after cyclization. After separation using gel silica chromatography and semi-preparative reverse phase high performance liquid chromatography (RP-HPLC), 22 novel antioxidant cyclic peptides were identified by ultra performance liquid chromatography-quadrupole-time of flight mass spectrometry (UPLC-Q-TOF-MS) and orbitrap-tandem mass spectrometry (Orbitrap-MS/MS). Synthetic cyclic peptides with the same sequence were synthesized and characterized for their antioxidant activity. Molecular docking suggested that the free radical molecules could bind with the cyclic backbone and side chain of cyclic peptides through hydrogen bonding, hydrophobic interaction as well as electrostatic interaction. This study has important implications for the high-value utilization of corn protein and new cyclic peptides drugs or functional food development.

Intranasal administration of dextran-pramlintide polyelectrolyte complex-coated nanoemulsions improves cognitive impairments in a mouse model of Alzheimer's disease

Nasal delivery has emerged as a non-invasive route to administer drugs for brain delivery. In particular, polyelectrolyte complexes-based nanocarriers have been demonstrated to be advantageous for nasal delivery of peptide drugs and vaccines. Pramlintide (Pram) is a peptide that emerges as a novel neuroprotective strategy to modify the pathogenesis of Alzheimer's disease (AD). In this study, we examined the effects of the intranasal administration of dextran-pramlintide polyelectrolyte complex-coated nanoemulsions (PEC-NEDexS/Pram) in an experimental model of AD induced by intracerebroventricular (i.c.v.) infusion of amyloid-beta (Aβ1–42) peptide in mice. PEC-NEDexS/Pram displayed droplet size lower than 200 nm and a negatively charged surface. The locomotor activity of the animals was not affected by the i.c.v. Aβ1–42 injection or Pram treatment. On the other hand, the intranasal administration of PEC-NEDexS/Pram at a dose of 100 μg/day for 14 consecutive days restored the impairment induced by Aβ1–42 injection in the discriminative learning and the short-term spatial reference memory of mice. However, Pram treatment did not alter the Aβ1–42-induced anhedonic behavior, oxidative stress parameters, or the pre-synaptic SNAP-25 and post-synaptic PSD-95 levels in the hippocampus and prefrontal cortex. These findings indicate cognitive-enhancing properties of intranasal Pram administration in an animal model of AD.

A microfluidic in vitro method predicting the fate of peptide drugs after subcutaneous administration

For many biopharmaceuticals, subcutaneous (sc) administration is the only viable route. However, there is no in vitro method available accurately predicting the absorption profiles of subcutaneously injected pharmaceuticals. In this work, we show that a recently developed microfluidics method for interaction studies (MIS) has the potential to be useful in this respect. The method utilises the responsiveness of polyelectrolyte microgel networks to oppositely charged molecules as a means to monitor the interaction between peptides and hyaluronic acid (HA), a major constituent of the subcutaneous extracellular matrix. We use the method to determine parameters describing the strength of interaction between peptide and HA as well as the peptide’s aggregation tendency and transport properties in HA networks. The results from MIS studies of the peptide drugs exenatide, pramlintide, vancomycin, polymyxin B, lanreotide, MEDI7219 and AZD2820 are compared with results from measurements with the commercially available SCISSOR system and in vivo absorption and bioavailability data from the literature. We show that both MIS and SCISSOR reveal differences in the peptides’ diffusivity and tendency to aggregate in the presence of HA. We show that MIS is particularly good at discriminating between peptides forming aggregates stabilised by non-electrostatic forces in the presence of HA, and peptides forming complexes stabilised by electrostatic interactions with HA. The method provides two parameters that can be used to quantify the peptides’ aggregation tendency, the one describing the peptide packing density in complexes with HA and the other the apparent diffusivity upon release in a medium of physiological ionic strength and pH. The order of the peptides when ranked by increasing binding strength at pH 7.4 determined with MIS is shown to be in agreement with the order when ranked by the apparent 1st order absorption rate constant (ka) after sc administration in humans: lanreotide (Autogel) < exenatide (IRF) < AZD2820 < pramlintide < lanreotide (IRF) (IRF: Immediate release formulation). A correlation is found between the 1st order release rate constant determined with SCISSOR and ka for lanreotide (Autogel), exenatide and AZD2820. A mechanism relating the magnitude of ka to the peptides’ charge is proposed.

185 (PB173): The novel peptide drug conjugate AVA6103 is a FAP-enabled preCISION™ medicine which targets Topoisomerase I to the tumor microenvironment via FAP cleavage

185 (PB173): The novel peptide drug conjugate AVA6103 is a FAP-enabled preCISION™ medicine which targets Topoisomerase I to the tumor microenvironment via FAP cleavage

A Reusable Polystyrene Support for Sustainable yet Cost-Effective Octreotide Synthesis.

The synthesis of peptide drugs has become facile with the use of supports that enable easy separation of the growing peptide. Peptide synthesis on insoluble supports typically employs excess reagents to enhance reaction efficiency and faces challenges during intramolecular cyclization. A non-crosslinked soluble polystyrene support is reported herein that improves cyclization efficiency on the support by using spacers. The support efficiency is illustrated by synthesizing octreotide drug in a scalable manner by on-support cyclization. The methodology drastically reduces the reagent waste, raw-material cost, and solvent requirement. The support can also be recovered and re-used up to 3 times making this a very sustainable method.

Enhanced efficacy of combined VEGFR peptide–drug conjugate and anti-PD-1 antibody in treating hepatocellular carcinoma

This study aimed to design a VEGFR-targeting peptide–drug conjugate with the ability to decrease tumor burden and suppress tumor angiogenesis, and to further evaluate the therapeutic effect of anti-PD-1 antibody in HCC therapy. A VEGFR-targeting peptide VEGF125 − 136 (QR) was conjugated with a lytic peptide (KLU) to form a peptide–drug conjugate QR-KLU. And the efficacy of QR-KLU in combination with anti-PD-1 antibody for HCC therapy in vivo and in vitro were evaluated. QR-KLU inhibited the proliferation and migration of mouse HCC cell line (Hepa1–6) cells under normoxic and hypoxic conditions in a dose-dependent manner. In the subcutaneous Hepa1–6 tumor model, QR-KLU combined with the anti-PD-1 antibody substantially inhibited tumor growth, promoted tumor necrosis, and prolonged the survival time of tumor-bearing mice. QR-KLU substantially inhibited hypoxia-induced expression of VEGF, promoted tumor vascular normalization, and increased cluster of differentiation 8+ (CD8+) T cell infiltration in the tumor. In addition, QR-KLU and anti-PD-1 antibody demonstrated a strong synergistic effect in promoting the activation of intratumoral CD8+ T cells, reducing the expression of immune-inhibitory factors, and increasing the expression of immune-stimulatory factors. This study proposed a novel approach for enhancing the efficacy of anti-PD-1 antibody using a VEGFR-targeting peptide–drug conjugate in HCC therapy.

Strategy for improving circular dichroism spectra deconvolution accuracy for macrocyclic peptides in drug discovery

Peptide therapeutics have emerged as an appealing modality in the pharmaceutical industry. Understanding peptide conformation in solution remains one of the most critical areas for peptide drug development. Circular dichroism (CD) spectroscopy is a useful technique to study the secondary structure of proteins and peptides, but the current approaches are limited to protein-focused models to predict high-order structures of peptides, and the models were built based on X-ray crystallography instead of solution-based technique, as a result, such models may have poor predictions for peptides. In this study, we present a novel CD deconvolution model to determine peptide conformation in solution. To quantitatively obtain secondary structure information using CD, a calibration model is needed beforehand to establish the relationship between each secondary structure feature and the corresponding CD response. A reference set containing the majority of cyclic peptides with known structures from solution-state NMR spectroscopy was used to build the calibration model for CD deconvolution. Improved prediction accuracy on the secondary structure determination for cyclic peptides was achieved by this model compared to the commercial standard model using commercially available platforms. This new CD deconvolution method is crucial for peptide conformational analysis in solution, and has the potential to greatly accelerate peptide drug candidate optimization in the pharmaceutical drug discovery field.

Design of Auto-Adaptive Drug Delivery System for Effective Delivery of Peptide Drugs to Overcoming Mucus and Epithelial Barriers.

Oral administration of peptide represents a promising delivery route, however, it is hindered by the harsh gastrointestinal environment, leading to low in vivo absorption. In this study, auto-adaptive protein corona-AT 1002-cationic liposomes (Pc-AT-CLs) are constructed with the characteristic of hydrophilic and electrically neutral surface properties for the encapsulation of liraglutide. BSA protein corona is used to coat AT-CLs reducing the adherence of mucus, and may fall off after penetrating the mucus layer. Transmucus transport experiment demonstrated that the mucus penetration amount of Pc-AT-CLs are 1.45 times that of AT-CLs. After penetrating the mucus layer, AT-CLs complete transmembrane transport by the dual action of AT and cationic surface properties. Transmembrane transport experiment demonstrated that the apparent permeability coefficient (Papp) of AT-CLs is 2.03 times that of CLs. In vivo tests demonstrated that Pc-AT-CLs exhibited a significant hypoglycemic effect and enhanced the relative bioavailability comparing to free liraglutide. Pc-AT-CLs protect liraglutide from degradation, facilitate its absorption, and ultimately improve its oral bioavailability.