Peptide Drug Development Research Articles

Photoinduced C(sp3)‐H Bicyclopentylation Enabled by an Electron Donor–Acceptor Complex‐Mediated Chemoselective Three‐Component Radical Relay

The photoredox electron donor–acceptor (EDA) complex‐mediated radical coupling reaction has gained prominence in the field of organic synthesis, finding widespread application in two‐component coupling reactions. However, EDA complex‐promoted multi‐component reactions are not well developed with only a limited number of examples have been reported. Herein, we report a photoinduced and EDA complex‐promoted highly chemoselective three‐component radical arylalkylation of [1.1.1]propellane, which allows the direct functionalization of C(sp3)–H with bicyclo[1.1.1]pentanes (BCP)‐aryl groups under mild conditions. A variety of unnatural α‐amino acids, featuring structurally diversified 1,3‐disubstituted BCP moieties, were synthesized in a single‐step process. Notably, leveraging the high tension release of [1.1.1]propellane, the highly unstable transient aryl radical undergoes rapid conversion into a relatively stable tertiary alkyl transient radical, and consequently, the competing side‐reaction of two‐component coupling was entirely suppressed. The strategic use of this transient radical conversion approach would be useful for the design of diverse EDA complex‐mediated multi‐component reactions. It is noteworthy that the highly chemoselective late‐stage incorporation of the 1,3‐disubstituted BCP pharmacophores into peptides was achieved both in liquid‐phase and solid‐phase reactions. This advancement is anticipated to have significant application potential in the future development of peptide drugs.

Photoinduced C(sp3)-H Bicyclopentylation Enabled by an Electron Donor-Acceptor Complex-Mediated Chemoselective Three-Component Radical Relay.

The photoredox electron donor-acceptor (EDA) complex-mediated radical coupling reaction has gained prominence in the field of organic synthesis, finding widespread application in two-component coupling reactions. However, EDA complex-promoted multi-component reactions are not well developed with only a limited number of examples have been reported. Herein, we report a photoinduced and EDA complex-promoted highly chemoselective three-component radical arylalkylation of [1.1.1]propellane, which allows the direct functionalization of C(sp3)-H with bicyclo[1.1.1]pentanes (BCP)-aryl groups under mild conditions. A variety of unnatural α-amino acids, featuring structurally diversified 1,3-disubstituted BCP moieties, were synthesized in a single-step process. Notably, leveraging the high tension release of [1.1.1]propellane, the highly unstable transient aryl radical undergoes rapid conversion into a relatively stable tertiary alkyl transient radical, and consequently, the competing side-reaction of two-component coupling was entirely suppressed. The strategic use of this transient radical conversion approach would be useful for the design of diverse EDA complex-mediated multi-component reactions. It is noteworthy that the highly chemoselective late-stage incorporation of the 1,3-disubstituted BCP pharmacophores into peptides was achieved both in liquid-phase and solid-phase reactions. This advancement is anticipated to have significant application potential in the future development of peptide drugs.

Therapeutic stapled peptides: Efficacy and molecular targets

Peptide stapling, by employing a stable, preformed alpha-helical conformation, results in the production of peptides with improved membrane permeability and enhanced proteolytic stability, compared to the original peptides, and provides an effective solution to accelerate the rapid development of peptide drugs. Various reviews present peptide stapling chemistries, anchoring residues and one- or two-component cyclization, however, therapeutic stapled peptides have not been systematically summarized, especially focusing on various disease-related targets. This review highlights the latest advances in therapeutic peptide drug development facilitated by the application of stapling technology, including different stapling techniques, synthetic accessibility, applicability to biological targets, potential for solving biological problems, as well as the current status of development. Stapled peptides as therapeutic drug candidates have been classified and analysed mainly by receptor- and ligand-based stapled peptide design against various diseases, including cancer, infectious diseases, inflammation, and diabetes. This review is expected to provide a comprehensive reference for the rational design of stapled peptides for different diseases and targets to facilitate the development of therapeutic peptides with enhanced pharmacokinetic and biological properties.

Deciphering ACE2-RBD binding affinity through peptide scanning: A molecular dynamics simulation approach

Rapid discovery of target information for protein-protein interactions (PPIs) is significant in drug design, diagnostics, vaccine development, antibody therapy, etc. Peptide microarray is an ideal tool for revealing epitope information of PPIs. In this work, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) spike receptor-binding domain (RBD) and the host cell receptor angiotensin-converting enzyme 2 (ACE2) were introduced as a model to study the epitope information of RBD-specific binding to ACE2 via a combination of theoretical calculations and experimental validation. Through dock and molecular dynamics simulations, it was found that among the 22 peptide fragments that consist of RBD, #14 (YNYLYRLFRKSNLKP) has the highest binding strength. Subsequently, the experiments of peptide microarray constructed based on plasmonic materials chip also confirmed the theoretical calculation data. Compared to other methods, such as phage display technology and surface plasmon resonance (SPR), this method is rapid and cost-effective, providing insights into the investigation of pathogen invasion processes and the timely development of peptide drugs and other fields.

Function and Mechanism of Antiviral Wasp Venom Peptide Protopolybia-MP III and Its Derivatives against HSV-1.

Viruses are one of the leading causes of human disease, and many highly pathogenic viruses still have no specific treatment drugs. Therefore, producing new antiviral drugs is an urgent matter. In our study, we first found that the natural wasp venom peptide Protopolybia-MP III had a significant inhibitory effect on herpes simplex virus type 1 (HSV-1) replication in vitro by using quantitative real-time PCR (qPCR), Western blotting, and plaque-forming assays. Immunofluorescence analysis showed Protopolybia-MP III could enter cells, and it inhibited multiple stages of the HSV-1 life cycle, including the attachment, entry/fusion, and post-entry stages. Furthermore, ultracentrifugation and electron microscopy detected that Protopolybia-MP III significantly suppressed HSV-1 virion infectivity at different temperatures by destroying the integrity of the HSV-1 virion. Finally, by comparing the antiviral activity of Protopolybia-MP III and its mutants, a series of peptides with better anti-HSV-1 activity were identified. Overall, this work found the function and mechanism of the antiviral wasp venom peptide Protopolybia-MP III and its derivatives against HSV-1 and laid the foundation for the research and development of wasp venom-derived antiviral candidate peptide drugs.

Characterizing the D-Amino Acid Position in Peptide Epimers by Using Higher-Energy Collisional Dissociation Tandem Mass Spectrometry: A Case Study of Liraglutide.

D-amino acid-containing peptides (DAACPs) occur in biological and artificial environments. Since the importance of DAACPs has been recognized, various mass spectrometry-based analytical approaches have been developed. However, the capability of higher-energy collisional dissociation (HCD) fragmentation to characterize DAACP sites has not been evaluated. In this study, we compared the normalized spectra intensity under different conditions of HCD and used liraglutide along with its DAACPs as examples. Our results indicated that the difference in the intensity of y ions between DAACPs and all-L liraglutide could not only distinguish them but also localize the sites of D-amino acids in the DAACPs. Our data demonstrate the potential of using HCD for the site characterization of DAACPs, which may have great impact in biological studies and peptide drug development.

Solid-phase peptide synthesis in 384-well plates.

Newer solid-phase peptide synthesis and release strategies enable the production of short peptides with high purity, allowing direct screening for desired bioactivity without prior chromatographic purification. However, the maximum number of peptides that can currently be synthesized per microplate reactor is 96, allowing the parallel synthesis of 384 peptides in modern devices that have space for 4 microplate reactors. To synthesize larger numbers of peptides, we modified a commercially available peptide synthesizer to enable the production of peptides in 384-well plates, which allows the synthesis of 1,536 peptides in one run (4× 384 peptides). We report new hardware components and customized software that allowed for the synthesis of 1,536 short peptides in good quantity (average > 0.5μmol), at high concentration (average > 10 mM), and decent purity without purification (average > 80%). The high-throughput peptide synthesis, which we developed with peptide drug development in mind, may be widely used for peptide library synthesis and screening, antibody epitope scanning, epitope mimetic development, or protease/kinase substrate screening.

Efficient Computational Framework for Target-Specific Active Peptide Discovery: A Case Study on IL-17C Targeting Cyclic Peptides.

The development of potentially active peptides for specific targets is critical for the modern pharmaceutical industry's growth. In this study, we present an efficient computational framework for the discovery of active peptides targeting a specific pharmacological target, which combines a conditional variational autoencoder (CVAE) and a classifier named TCPP based on the Transformer and convolutional neural network. In our example scenario, we constructed an active cyclic peptide library targeting interleukin-17C (IL-17C) through a library-based in vitro selection strategy. The CVAE model is trained on the preprocessed peptide data sets to generate potentially active peptides and the TCPP further screens the generated peptides. Ultimately, six candidate peptides predicted by the model were synthesized and assayed for their activity, and four of them exhibited promising binding affinity to IL-17C. Our study provides a one-stop-shop for target-specific active peptide discovery, which is expected to boost up the process of peptide drug development.

Lipid-Based Nanoparticles as Oral Drug Delivery Systems: Overcoming Poor Gastrointestinal Absorption and Enhancing Bioavailability of Peptide and Protein Therapeutics.

Delivery and formulation of oral peptide and protein therapeutics have always been a challenge for the pharmaceutical industry. The oral bioavailability of peptide and protein therapeutics mainly relies on their gastrointestinal solubility and permeability which are affected by their poor membrane penetration, high molecular weight and proteolytic (chemical and enzymatic) degradation resulting in limited delivery and therapeutic efficacy. The present review article highlights the challenges and limitations of oral delivery of peptide and protein therapeutics focusing on the application, potential and importance of solid lipid nanoparticles (SLNs) and nanostructured lipid carriers (NLCs) as lipid-based drug delivery systems (LBDDSs) and their advantages and drawbacks. LBDDSs, due to their lipid-based matrix can encapsulate both lipophilic and hydrophilic drugs, and by reducing the first-pass effect and avoiding proteolytic degradation offer improved drug stability, dissolution rate, absorption, bioavailability and controlled drug release. Furthermore, their small size, high surface area and surface modification increase their mucosal adhesion, tissue-targeted distribution, physiological function and half-life. Properties such as simple preparation, high-scale manufacturing, biodegradability, biocompatibility, prolonged half-life, lower toxicity, lower adverse effects, lipid-based structure, higher drug encapsulation rate and various drug release profile compared to other similar carrier systems makes LBDDSs a promising drug delivery system (DDS). Nevertheless, undesired physicochemical features of peptide and protein drug development and discovery such as plasma stability, membrane permeability and circulation half-life remain a serious challenge which should be addressed in future.

StarPep Toolbox: an open-source software to assist chemical space analysis of bioactive peptides and their functions using complex networks.

Antimicrobial peptides (AMPs) are promising molecules to treat infectious diseases caused by multi-drug resistance pathogens, some types of cancer, and other conditions. Computer-aided strategies are efficient tools for the high-throughput screening of AMPs. This report highlights StarPep Toolbox, an open-source and user-friendly software to study the bioactive chemical space of AMPs using complex network-based representations, clustering, and similarity-searching models. The novelty of this research lies in the combination of network science and similarity-searching techniques, distinguishing it from conventional methods based on machine learning and other computational approaches. The network-based representation of the AMP chemical space presents promising opportunities for peptide drug repurposing, development, and optimization. This approach could serve as a baseline for the discovery of a new generation of therapeutics peptides. All underlying code and installation files are accessible through GitHub (https://github.com/Grupo-Medicina-Molecular-y-Traslacional/StarPep) under the Apache 2.0 license.

ACP-Dnnel: anti-coronavirus peptides' prediction based on deep neural network ensemble learning.

The ongoing COVID-19 pandemic has caused dramatic loss of human life. There is an urgent need for safe and efficient anti-coronavirus infection drugs. Anti-coronavirus peptides (ACovPs) can inhibit coronavirus infection. With high-efficiency, low-toxicity, and broad-spectrum inhibitory effects on coronaviruses, they are promising candidates to be developed into a new type of anti-coronavirus drug. Experiment is the traditional way of ACovPs' identification, which is less efficient and more expensive. With the accumulation of experimental data on ACovPs, computational prediction provides a cheaper and faster way to find anti-coronavirus peptides' candidates. In this study, we ensemble several state-of-the-art machine learning methodologies to build nine classification models for the prediction of ACovPs. These models were pre-trained using deep neural networks, and the performance of our ensemble model, ACP-Dnnel, was evaluated across three datasets and independent dataset. We followed Chou's 5-step rules. (1) we constructed the benchmark datasets data1, data2, and data3 for training and testing, and introduced the independent validation dataset ACVP-M; (2) we analyzed the peptides sequence composition feature of the benchmark dataset; (3) we constructed the ACP-Dnnel model with deep convolutional neural network (DCNN) merged the bi-directional long short-term memory (BiLSTM) as the base model for pre-training to extract the features embedded in the benchmark dataset, and then, nine classification algorithms were introduced to ensemble together for classification prediction and voting together; (4) tenfold cross-validation was introduced during the training process, and the final model performance was evaluated; (5) finally, we constructed a user-friendly web server accessible to the public at http://150.158.148.228:5000/ . The highest accuracy (ACC) of ACP-Dnnel reaches 97%, and the Matthew's correlation coefficient (MCC) value exceeds 0.9. On three different datasets, its average accuracy is 96.0%. After the latest independent dataset validation, ACP-Dnnel improved at MCC, SP, and ACC values 6.2%, 7.5% and 6.3% greater, respectively. It is suggested that ACP-Dnnel can be helpful for the laboratory identification of ACovPs, speeding up the anti-coronavirus peptide drug discovery and development. We constructed the web server of anti-coronavirus peptides' prediction and it is available at http://150.158.148.228:5000/ .

Unstructured Polypeptides as a Versatile Drug Delivery Technology.

Although polyethylene glycol (PEG), or "PEGylation" has become a widely applied approach for improving the efficiency of drug delivery, the immunogenicity and non-biodegradability of this synthetic polymer have prompted an evident need for alternatives. To overcome these caveats and to mimic PEG -or other natural or synthetic polymers- for the purpose of drug half-life extension, unstructured polypeptides are designed. Due to their tunable length, biodegradability, low immunogenicity and easy production, unstructured polypeptides have the potential to replace PEG as the preferred technology for therapeutic protein/peptide delivery. This review provides an overview of the evolution of unstructured polypeptides, starting from natural polypeptides to engineered polypeptides and discusses their characteristics. Then, it is described that unstructured polypeptides have been successfully applied to numerous drugs, including peptides, proteins, antibody fragments, and nanocarriers, for half-life extension. Innovative applications of unstructured peptides as releasable masks, multimolecular adaptors and intracellular delivery carriers are also discussed. Finally, challenges and future perspectives of this promising field are briefly presented. STATEMENT OF SIGNIFICANCE: : Polypeptide fusion technology simulating PEGylation has become an important topic for the development of long-circulating peptide or protein drugs without reduced activity, complex processes, and kidney injury caused by PEG modification. Here we provide a detailed and in-depth review of the recent advances in unstructured polypeptides. In addition to the application of enhanced pharmacokinetic performance, emphasis is placed on polypeptides as scaffolders for the delivery of multiple drugs, and on the preparation of reasonably designed polypeptides to manipulate the performance of proteins and peptides. This review will provide insight into future application of polypeptides in peptide or protein drug development and the design of novel functional polypeptides.

Improved structure-related prediction for insufficient homologous proteins using MSA enhancement and pre-trained language model.

guofei@csu.edu.cn, jj.tang@siat.ac.cn.

Cathelicidin CATH-B1 Inhibits Pseudorabies Virus Infection via Direct Interaction and TLR4/JNK/IRF3-Mediated Interferon Activation.

Pseudorabies virus (PRV), the causative pathogen of Aujeszky's disease, is one of the most important pathogens threatening the global pig industry. Although vaccination has been used to prevent PRV infection, the virus cannot be eliminated in pigs. Thus, novel antiviral agents as complementary to vaccination are urgently needed. Cathelicidins (CATHs) are host defense peptides that play an important role in the host immune response against microbial infections. In the study, we found that the chemical synthesized chicken cathelicidin B1 (CATH-B1) could inhibit PRV regardless of whether CATH-B1 was added pre-, co-, or post-PRV infection in vitro and in vivo. Furthermore, coincubation of CATH-B1 with PRV directly inactivated virus infection by disrupting the virion structure of PRV and mainly inhibited virus binding and entry. Importantly, pretreatment of CATH-B1 markedly strengthened the host antiviral immunity, as indicated by the increased expression of basal interferon-β (IFN-β) and several IFN-stimulated genes (ISGs). Subsequently, we investigated the signaling pathway responsible for CATH-B1-induced IFN-β production. Our results showed that CATH-B1 induced phosphorylation of interferon regulatory transcription factor 3 (IRF3) and further led to production of IFN-β and reduction of PRV infection. Mechanistic studies revealed that the activation of Toll-like receptor 4 (TLR4), endosome acidification, and the following c-Jun N-terminal kinase (JNK) was responsible for CATH-B1-induced IRF3/IFN-β pathway activation. Collectively, CATH-B1 could markedly inhibit PRV infection via inhibiting virus binding and entry, direct inactivation, and regulating host antiviral response, which provided an important theoretical basis for the development of antimicrobial peptide drugs against PRV infection. IMPORTANCE Although the antiviral activity of cathelicidins could be explained by direct interfering with the viral infection and regulating host antiviral response, the specific mechanism of cathelicidins regulating host antiviral response and interfering with pseudorabies virus (PRV) infection remains elusive. In this study, we investigated the multiple roles of cathelicidin CATH-B1 against PRV infection. Our study showed that CATH-B1 could suppress the binding and entry stages of PRV infection and direct disrupt PRV virions. Remarkably, CATH-B1 significantly increased basal interferon-β (IFN-β) and IFN-stimulated gene (ISG) expression levels. Furthermore, TLR4/c-Jun N-terminal kinase (JNK) signaling was activated and involved in IRF3/IFN-β activation in response to CATH-B1. In conclusion, we elucidate the mechanisms by which the cathelicidin peptide direct inactivates PRV infection and regulates host antiviral IFN-β signaling.

Discovery and Characteristics of a Novel Antitumor Cyclopeptide Derived from Shark.

Peptides pose a challenge in drug development due to their short half-lives in vivo. In this study, we conducted in vitro degradation experiments on SAIF, which is a shark-derived peptide that we previously studied. The degradation fragments were sequenced and a truncated peptide sequence was identified. The truncated peptide was then cloned and expressed via the E. coli system with traceless cloning to form a novel cyclic peptide in vitro oxidation condition via the formation of a disulfide bond between the N- and C-termini, which was named ctSAIF. ctSAIF exhibited high anti-HCC activity and enhanced enzymatic stability in vitro, and retained antitumor activity and good biocompatibility in systemic circulation in a HCC xenograft model. Our study discovered and characterized a novel shark-derived cyclic peptide with antitumor activity, laying a foundation for its further development as an antitumor drug candidate. The study also provided a new solution for peptide drug development.

A Novel Approach for Screening Sericin-Derived Therapeutic Peptides Using Transcriptomics and Immunoprecipitation.

With the demand for more efficient and safer therapeutic drugs, targeted therapeutic peptides are well received due to their advantages of high targeting (specificity), low immunogenicity, and minimal side effects. However, the conventional methods of screening targeted therapeutic peptides in natural proteins are tedious, time-consuming, less efficient, and require too many validation experiments, which seriously restricts the innovation and clinical development of peptide drugs. In this study, we established a novel method of screening targeted therapeutic peptides in natural proteins. We also provide details for library construction, transcription assays, receptor selection, therapeutic peptide screening, and biological activity analysis of our proposed method. This method allows us to screen the therapeutic peptides TS263 and TS1000, which have the ability to specifically promote the synthesis of the extracellular matrix. We believe that this method provides a reference for screening other drugs in natural resources, including proteins, peptides, fats, nucleic acids, and small molecules.

Evolution of Peptide Biopharmaceuticals

Peptides are small molecule substances involved in numerous essential physiological functions such as human growth and development, stress, regulation of the emotional state, sexual behavior, and immune responses. Their mechanisms of action are based on receptor-ligand interaction, which leads to highly selective effects. These properties and low toxicity allow them to be considered potent drugs. The production of peptide preparations became possible at the beginning of the 20th century after a method for the selective synthesis of peptides was developed. However, after the successful synthesis of the first peptide drugs, many issues related to increasing stability, bioavailability, half-life, and the ability to move through cell membranes remained unresolved. The review considers the historical path of development of the synthesis and production of peptides, as well as modern approaches to the creation of peptide drugs and their use in biopharmaceutics, including the development of original peptide drugs in Russia.

NeuroPred-PLM: an interpretable and robust model for neuropeptide prediction by protein language model.

Neuropeptides are a diverse and complex class of signaling molecules that regulate a variety of biological processes. Neuropeptides provide many opportunities for the discovery of new drugs and targets for the treatment of a wide range of diseases, and thus, computational tools for the rapid and accurate large-scale identification of neuropeptides are of great significance for peptide research and drug development. Although several machine learning-based prediction tools have been developed, there is room for improvement in the performance and interpretability of the proposed methods. In this work, we developed an interpretable and robust neuropeptide prediction model, named NeuroPred-PLM. First, we employed a language model (ESM) of proteins to obtain semantic representations of neuropeptides, which could reduce the complexity of feature engineering. Next, we adopted a multi-scale convolutional neural network to enhance the local feature representation of neuropeptide embeddings. To make the model interpretable, we proposed a global multi-head attention network that could be used to capture the position-wise contribution to neuropeptide prediction via the attention scores. In addition, NeuroPred-PLM was developed based on our newly constructed NeuroPep 2.0 database. Benchmarks based on the independent test set show that NeuroPred-PLM achieves superior predictive performance compared with other state-of-the-art predictors. For the convenience of researchers, we provide an easy-to-install PyPi package (https://pypi.org/project/NeuroPredPLM/) and a web server (https://huggingface.co/spaces/isyslab/NeuroPred-PLM).

Front Cover: Katritzky Salts for the Synthesis of Unnatural Amino Acids and Late‐Stage Functionalization of Peptides (Eur. J. Org. Chem. 12/2023)

The Front Cover shows chalkboard drawings of recent advances in the use of Katritzky salts as intermediates for the synthesis of unnatural amino acids, late-stage functionalization of peptides, and macrocyclization. Thanks to the progress made in deaminative strategies using Katritzky salts, a variety of radical alkylation methods have been developed in the peptide chemistry field. Peptide drug development will greatly benefit from the novel methodologies to expand the chemical space explored around peptides and biomolecules. Cover design realized by Yousif. More information can be found in the Review by A. M. Yousif et al.

A novel and low-toxic peptide DR3penA alleviates pulmonary fibrosis by regulating the MAPK/miR-23b-5p/AQP5 signaling axis.

Pulmonary fibrosis (PF) is a pathological change caused by repeated injuries and repair dysfunction of the alveolar epithelium. Our previous study revealed that the residues Asn3 and Asn4 of peptide DR8 (DHNNPQIR-NH2) could be modified to improve stability and antifibrotic activity, and the unnatural hydrophobic amino acids α-(4-pentenyl)-Ala and d-Ala were considered in this study. DR3penA (DHα-(4-pentenyl)-ANPQIR-NH2) was verified to have a longer half-life in serum and to significantly inhibit oxidative damage, epithelial-mesenchymal transition (EMT) and fibrogenesis in vitro and in vivo. Moreover, DR3penA has a dosage advantage over pirfenidone through the conversion of drug bioavailability under different routes of administration. A mechanistic study revealed that DR3penA increased the expression of aquaporin 5 (AQP5) by inhibiting the upregulation of miR-23b-5p and the mitogen-activated protein kinase (MAPK) pathway, indicating that DR3penA may alleviate PF by regulating MAPK/miR-23b-5p/AQP5. Safety evaluation showed that DR3penA is a peptide drug without obvious toxicity or acute side effects and has significantly improved safety compared to DR8. Thus, our findings suggest that DR3penA, as a novel and low-toxic peptide, has the potential to be a leading compound for PF therapy, which provides a foundation for the development of peptide drugs for fibrosis-related diseases.